CTFR 18/224,860 CTFR 100903 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. This office action is in response to applicant’s amendment filed on 04/08/2026. Claims 1-19 are pending and examined. Response to Arguments 07-37 AIA Applicant's arguments filed 04/08/2026 with respect to 35 U.S.C. 101 have been fully considered but they are not persuasive. Applicant argued that “the claimed steps are not practically performable in the human mind in the claimed environment” and that “Even if one were to consider the claims as reciting an abstract idea at a high level, the additional limitations integrate any such idea into a practical application and recite significantly more than the alleged exception by defining a particular technical mechanism for distributed-memory QoS control.” Examiner respectfully disagrees, see 35 U.S.C 101 rejections below for a detailed analysis. The mental process abstract idea previously identified included the “selecting…” limitation, where a human could reasonably select a queue among all the queues divided according to the priorities to transmit a request. Additionally, the amended limitations include an additional abstract idea as a mental process where a human could reasonably classify a level of traffic load into a plurality of load levels. Furthermore, the additional limitations do not appear to integrate the ideas into a practical application . 07-37 AIA Applicant's arguments filed 04/08/2026 with respect to 35 U.S.C. 103 have been fully considered but they are not persuasive. Applicant argued that “the prioritization level of Kerrigan is a parameter that specifies a processing frequency ratio, and the trigger threshold of Petty is a monitoring parameter that detects changes in queue depth. Neither of these parameters directly controls a bandwidth of a queue as the throttle value of the present invention does” and that “none of the cited references disclose or suggest a configuration in which a level of the traffic load is classified into a plurality of load levels and the throttle value is adjusted by differentiated increment values according to each classified load level, as recited in the amended independent claims.” Examiner respectfully disagrees, see 35 U.S.C 103 rejections below for a detailed analysis . With regards to the mapping of the throttle value, the arguments appear to be directed to the last limitation of the independent claim. As previously stated in the previous office action, Kerrigan’s applications, services, or other software checking higher priority queues first based on a corresponding percentage of the designated prioritization level of the processing queue correlates to adjusting a bandwidth of the selected queue by using the prioritization value. The prioritization level being dynamically adjusted based on the amounts of data stored in each queue, which may be decreased when a request is transmitted to the management computing site, correlates to adjusting a bandwidth of the selected queue by using the prioritization value when the request of the selected queue is transmitted to the distributed memory. Petty’s trigger threshold attribute value which is expressed as a percentage of the maximum queue depth correlates to a throttle value corresponding to the selected queue. The queue depth high percentage attribute value of the queue correlates to bandwidth of the selected queue. The value of the trigger threshold being subtracted from the current value of the queue depth high percentage correlates to the bandwidth of the selected queue being adjusted using the throttle value. The combination of these references, rather than in isolation, is interpreted to disclose the last limitation of the independent claim. Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with Petty because trigger threshold values can be used to indicate a change in queue depth that should be considered significant trigger events. The trigger threshold value in combination with the queue depth high percentage can also be used to categorize different types of messages as trigger or non-trigger messages. With regards to the newly amended limitations, Kerrigan is interpreted to disclose the newly amended limitations. For example, the system determining there is too much prioritization based on the amount of data in a specific low priority queue being above a high watermark threshold can also include an amount of data in different low priority queues being above or below a low or high watermark threshold. Therefore, the system determining there is too much prioritization based on the amount of data in the low priority queues being above or below a high watermark threshold and reducing the prioritization level correlates to the updating comprising classifying a level of the information into a plurality of load levels . The determination of what constitutes “too much” prioritization being configurable can include “too much” prioritization indicating a low priority queue being below a high watermark threshold but above a low watermark threshold, which correlates to a first load level. This configurable indication would also trigger in scenarios where a low priority queue is above both a high watermark threshold and low watermark threshold, which correlates to a second load level higher than the first load level. The prioritization level being reduced so that the amount of data in the low priority queues transitions from above a low watermark threshold to below a low watermark threshold correlates to adjusting the prioritization value by a first increment value when the level of the information is classified into a first load level. The prioritization level being reduced so that the amount of data in the low priority queues transitions from above a high watermark threshold to below a low watermark threshold would involve a greater reduction in prioritization level than compared to the first load level and therefore correlates to adjusting the prioritization value by a second increment value greater than the first increment value when the level of the information is classified into a second load level higher than the first load level . Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to (an) abstract idea(s) without significantly more. Claim 1 and 14 recite: A priority-based scheduling method performed by a host of a memory separation network, the priority-based scheduling method comprising: receiving a traffic load of queues divided according to priorities from a distributed memory configured to perform a load monitoring function; updating a throttle value of the queues divided according to the priorities at regular intervals by using the received traffic load, wherein the updating comprises classifying a level of the traffic load into a plurality of load levels and adjusting the throttle value by a first increment value when the level of the traffic load is classified into a first load level and by a second increment value greater than the first increment value when the level of the traffic load is classified into a second load level higher than the first load level; selecting a queue to transmit a request to the distributed memory from among all the queues divided according to the priorities; and adjusting a bandwidth of the selected queue by using the throttle value when the request of the selected queue is transmitted to the distributed memory. Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 1 is a process. Claim 14 is a machine. Step 2A, Prong I: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes: (an) abstract idea(s). The ‘classifying’ limitation in #3 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “classifying” in the context of this claim encompasses a person analyzing, evaluating, or classifying a level of traffic load into a plurality of load levels, including comparison or judgement. The ‘selecting’ limitation in #5 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “selecting” in the context of this claim encompasses a person analyzing, evaluating, or selecting a queue to transmit a request according to the priorities, including comparison or judgement. Step 2A, Prong II: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. The ‘receiving’ limitation in #1 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element that is insignificant extra-solution activity . The limitation “receiving” in the context of this claim encompasses mere data gathering. See MPEP 2106.05(g). The ‘updating’ limitation in #2 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “updating” in the context of this claim encompasses merely updating a throttle value according to the priorities. See MPEP 2106.05(f). The ‘adjusting’ limitation in #4 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “adjusting” in the context of this claim encompasses merely adjusting the throttle value by a first or second increment value based on a first or second load level. See MPEP 2106.05(f). The ‘adjusting’ limitation in #6 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “adjusting” in the context of this claim encompasses merely adjusting a bandwidth using the throttle value. See MPEP 2106.05(f). Additionally, one or more of the claims recite the following additional elements: A host of a memory separation network (Claim 1) A scheduler of a host (Claim 14) One or more processors (Claim 14) A memory (Claim 14) These additional elements are recited at a high level of generality (i.e., as generic computer components) such that they amount to no more than components comprising mere instructions to apply the exception . Accordingly, these additional elements do not integrate the abstract idea(s) into a practical application because they do not impose any meaningful limits on practicing the abstract ideas(s). Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. As discussed above with respect to integration of the abstract idea(s) into a practical application, the aforementioned additional elements amount to no more than components for obtaining or gathering data and comprising mere instructions to apply the exception which is evidently seen in MPEP 2106.05(g)&(f). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Claims 2 and 15 merely further describe the traffic load of Claims 1 and 14 respectively. The claims do not include additional elements that integrate into practical application or are sufficient to amount to significantly more than the judicial exception. Claims 3 and 16 merely further describe the traffic load of Claims 2 and 15 respectively. The claims do not include additional elements that integrate into practical application or are sufficient to amount to significantly more than the judicial exception. Claims 6 and 19 merely further describe the bandwidth of the selected queue of Claims 1 and 14 respectively. The claims do not include additional elements that integrate into practical application or are sufficient to amount to significantly more than the judicial exception. Therefore, Claims 1-3, 6, 14-16 and 19 are directed to (an) abstract idea(s) without significantly more. Claim 4 and 17 recite: wherein the selecting comprises: determining whether a bandwidth size corresponding to each of all the queues divided according to priorities is greater than or equal to a certain standard; determining whether there is a request to be processed with respect to at least one queue having a bandwidth size that is greater than or equal to the certain standard; and selecting a queue having a highest priority from the at least one queue determined to have the request to be processed as a queue to transmit a request to the distributed memory. Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 4 is a process. Claim 17 is a machine. Step 2A, Prong I: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes: (an) abstract idea(s). The ‘determining’ limitation in #7 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “determining” in the context of this claim encompasses a person analyzing, evaluating, or determining whether a bandwidth size is greater than or equal to a certain standard, including comparison or judgement. The ‘determining’ limitation in #8 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “determining” in the context of this claim encompasses a person analyzing, evaluating, or determining whether there is a request to be processed, including comparison or judgement. The ‘selecting’ limitation in #9 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “selecting” in the context of this claim encompasses a person analyzing, evaluating, or selecting a queue to transmit a request to the distributed memory, including comparison or judgement. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. As discussed above with respect to integration of the abstract idea(s) into a practical application, the aforementioned additional elements amount to no more than components for obtaining or gathering data and comprising mere instructions to apply the exception which is evidently seen in MPEP 2106.05(f). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, Claims 4 and 17 are directed to (an) abstract idea(s) without significantly more. Claim 5 and 18 recite: wherein the selecting comprises: increasing a bandwidth by using the throttle value for a queue to which a corresponding bandwidth is less than the certain standard of all the queues divided according to the priorities, wherein the increased bandwidth is reflected on a next scheduling time. Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 5 is a process. Claim 18 is a machine. Step 2A, Prong II: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. The ‘increasing’ limitation in #10 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “increasing” in the context of this claim encompasses merely increasing a bandwidth using the throttle value. See MPEP 2106.05(f). Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. As discussed above with respect to integration of the abstract idea(s) into a practical application, the aforementioned additional elements amount to no more than components for obtaining or gathering data and comprising mere instructions to apply the exception which is evidently seen in MPEP 2106.05(f). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, Claims 5 and 18 are directed to (an) abstract idea(s) without significantly more. Claim 7 recites: A priority-based scheduling method performed by a host of a memory separation network, the priority-based scheduling method comprising: receiving a traffic load of queues divided according to priorities from a distributed memory configured to perform a load monitoring function; updating a throttle value of the queues divided according to the priorities at regular intervals by using the received traffic load, wherein the updating comprises classifying a level of the traffic load into a plurality of load levels and adjusting the throttle value by a first increment value when the level of the traffic load is classified into a first load level and by a second increment value greater than the first increment value when the level of the traffic load is classified into a second load level higher than the first load level; determining whether the host transmits a request to the distributed memory in an order from a highest priority; and updating a bandwidth for a queue of which a priority is lower than a priority of the queue determined to transmit the request. Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 7 is a process. Step 2A, Prong I: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes: (an) abstract idea(s). The ‘classifying’ limitation in #13 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “classifying” in the context of this claim encompasses a person analyzing, evaluating, or classifying a level of traffic load into a plurality of load levels, including comparison or judgement. The ‘determining’ limitation in #15 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “determining” in the context of this claim encompasses a person analyzing, evaluating, or determining whether the host transmits a request to the distributed memory, including comparison or judgement. Step 2A, Prong II: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. The ‘receiving’ limitation in #11 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element that is insignificant extra-solution activity . The limitation “receiving” in the context of this claim encompasses mere data gathering. See MPEP 2106.05(g). The ‘updating’ limitation in #12 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “updating” in the context of this claim encompasses merely updating a throttle value according to the priorities. See MPEP 2106.05(f). The ‘adjusting’ limitation in #14 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “adjusting” in the context of this claim encompasses merely adjusting the throttle value by a first or second increment value based on a first or second load level. See MPEP 2106.05(f). The ‘updating’ limitation in #16 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “updating” in the context of this claim encompasses merely updating a bandwidth for a queue. See MPEP 2106.05(f). Additionally, one or more of the claims recite the following additional elements: A host of a memory separation network (Claim 7) These additional elements are recited at a high level of generality (i.e., as generic computer components) such that they amount to no more than components comprising mere instructions to apply the exception . Accordingly, these additional elements do not integrate the abstract idea(s) into a practical application because they do not impose any meaningful limits on practicing the abstract ideas(s). Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. As discussed above with respect to integration of the abstract idea(s) into a practical application, the aforementioned additional elements amount to no more than components for obtaining or gathering data and comprising mere instructions to apply the exception which is evidently seen in MPEP 2106.05(g)&(f). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Claim 8 merely further describes the traffic load of Claim 7. The claim does not include additional elements that integrate into practical application or are sufficient to amount to significantly more than the judicial exception. Claim 9 merely further describes the traffic load of Claim 8. The claim does not include additional elements that integrate into practical application or are sufficient to amount to significantly more than the judicial exception. Claim 13 merely further describes the bandwidth of the selected queue of Claim 7. The claim does not include additional elements that integrate into practical application or are sufficient to amount to significantly more than the judicial exception. Therefore, Claims 7-9 and 13 are directed to (an) abstract idea(s) without significantly more. Claim 10 recites: wherein the determining comprises: determining whether to transmit a request by each of the queues divided according to the priorities, based on whether each of the queues comprises a request to be processed and a size of a bandwidth corresponding to each of the queues. Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 10 is a process. Step 2A, Prong I: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes: (an) abstract idea(s). The ‘determining’ limitation in #17 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “determining” in the context of this claim encompasses a person analyzing, evaluating, or determining whether to transmit a request based on the size of a bandwidth and whether each of the queues comprises a request, including comparison or judgement. Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. As discussed above with respect to integration of the abstract idea(s) into a practical application, the aforementioned additional elements amount to no more than components for obtaining or gathering data and comprising mere instructions to apply the exception which is evidently seen in MPEP 2106.05(f). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, Claim 10 is directed to (an) abstract idea(s) without significantly more. Claim 11 recites: wherein the determining further comprises: transmitting a request to be processed to the distributed memory when there is the request to be processed and a size of a bandwidth corresponding to each of the queues is greater than or equal to a certain standard by each of the queues divided according to the priorities; and determining whether to transmit a request by a queue having a lower priority than a queue when the queue does not comprise the request to be processed or a size of a bandwidth corresponding to the queue is less than the certain standard. Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 11 is a process. Step 2A, Prong I: Does the claim recite an abstract idea, law of nature, or natural phenomenon? Yes: (an) abstract idea(s). The ‘determining’ limitation in #19 above, as claimed and under broadest reasonable interpretation (BRI), is a mental process that covers performance of the limitation in the mind. The limitation “determining” in the context of this claim encompasses a person analyzing, evaluating, or determining whether to transmit a request by a queue having lower priority, including comparison or judgement. Step 2A, Prong II: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. The ‘transmitting’ limitation in #18 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “transmitting” in the context of this claim encompasses merely transmitting a request to be processed to the distributed memory. See MPEP 2106.05(f). Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. As discussed above with respect to integration of the abstract idea(s) into a practical application, the aforementioned additional elements amount to no more than components for obtaining or gathering data and comprising mere instructions to apply the exception which is evidently seen in MPEP 2106.05(f). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, Claim 11 is directed to (an) abstract idea(s) without significantly more. Claim 12 recites: wherein the determining further comprises: increasing a bandwidth by using the throttle value for a queue to which a corresponding bandwidth is less than the certain standard of all the queues divided according to the priorities, wherein the increased bandwidth is reflected on a next scheduling time. Step 1: Is the claim to a process, machine, manufacture, or composition of matter? Yes. Claim 12 is a process. Step 2A, Prong II: Does the claim recite additional elements that integrate the judicial exception into a practical application? No. The ‘increasing’ limitation in #20 above, as claimed and under broadest reasonable interpretation (BRI), is an additional element as “apply it” that is mere instructions to apply an exception . The limitation “increasing” in the context of this claim encompasses merely increasing a bandwidth using the throttle value. See MPEP 2106.05(f). Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. As discussed above with respect to integration of the abstract idea(s) into a practical application, the aforementioned additional elements amount to no more than components for obtaining or gathering data and comprising mere instructions to apply the exception which is evidently seen in MPEP 2106.05(f). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, Claim 12 is directed to (an) abstract idea(s) without significantly more. Claim Rejections - 35 USC § 103 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 07-21-aia AIA Claim (s) 1-2, 4, 6-8, 10-11, 13-15, 17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Kerrigan et al. (U.S. Patent No. US 20230124885 A1), hereinafter “Kerrigan” in view of Manula et al. (U.S. Patent No. US 20140181409 A1), hereinafter “Manula,” Mula et al. (U.S. Patent No. US 20230412519 A1), hereinafter “Mula” and Petty et al. (U.S. Patent No. US 6615215 B1), hereinafter “Petty.” With regards to Claim 1, Kerrigan teaches: A priority-based scheduling method performed by a host of a memory separation network (Fig. 1, paragraphs 29-30, “Although shown as an element of the management computing site 102 and the edge computing sites 104 in this embodiment, the data transfer prioritization logic 110 in other embodiments can be implemented at least in part externally to the management computing site 102 and the edge computing sites 104, for example, as a stand-alone server, set of servers or other types of systems coupled via one or more networks to the management computing site 102 and/or the edge computing sites 104. In some embodiments, the data transfer prioritization logic 110 may be implemented at least in part within one or more of the remote computing sites 106 and/or the client devices 116. The management computing site 102, the edge computing sites 104 and the remote computing sites 106 in the FIG. 1 embodiment are assumed to be implemented using at least one processing device. Each such processing device generally comprises at least one processor and an associated memory, and implements at least a portion of the functionality of the data transfer prioritization logic 110.” The processing devices which each have associated memory implementing at least a portion of the functionality of the data transfer prioritization logic across remote computing sites via a network correlates to a priority-based scheduling method performed by a host of a memory separation network) , updating a prioritization value of the queues divided according to the priorities at regular intervals by using the received information (Paragraphs 41 and 66, “The designated prioritization level may be dynamically adjusted in response to detecting one or more designated conditions. The one or more designated conditions may comprise amounts of data stored in the two or more different processing queues in the two or more sets of processing queues. The designated prioritization level may be specified by an orchestrator service in the service chain. The orchestrator service in the service chain may dynamically adjust the designated prioritization level in response to requests from a management entity operating the service chain… It should be noted that the reduction in prioritization level may be for a limited time duration (e.g., suspend or otherwise reduce prioritization for a set period of time, or until some other designated condition is reached such as the amount of data in the low priority queues being below a low watermark threshold, etc.).” The prioritization level of a queue correlates to a prioritization value of a queue. The prioritization level being dynamically adjusted in response to one or more conditions such as the amount of data stored in each queue with set time periods correlates to updating a prioritization value of the queues at regular intervals using the received information) , wherein the updating comprises classifying a level of the information into a plurality of load levels (Paragraph 66, “In step 552, the amount of prioritization increases above some designated threshold. This may correspond to the amount of prioritization increasing dramatically such that other non-prioritized data transfer is at a standstill (e.g., where the amount of data in the low priority queues is above some high watermark threshold, etc.) … In step 553, the end-user or automated system 522 determines that there is too much prioritization, and in step 554 utilizes the front-end interface 524 to communicate with the orchestration service 530 to request a reduction in prioritization level. It should be noted that the reduction in prioritization level may be for a limited time duration (e.g., suspend or otherwise reduce prioritization for a set period of time, or until some other designated condition is reached such as the amount of data in the low priority queues being below a low watermark threshold, etc.).” The system determining there is too much prioritization based on the amount of data in a specific low priority queue being above a high watermark threshold can also include an amount of data in different low priority queues being above or below a low or high watermark threshold. Therefore, the system determining there is too much prioritization based on the amount of data in the low priority queues being above or below a high watermark threshold and reducing the prioritization level correlates to the updating comprising classifying a level of the information into a plurality of load levels) and adjusting the prioritization value by a first increment value when the level of the information is classified into a first load level (Paragraphs 63 and 66, “For example, it can be useful to reduce the prioritization in the case where so much prioritization occurs that it adversely affects the overall system. The determination of what constitutes “too much” prioritization may be user-configurable or selected based on the needs of a particular use case… In step 552, the amount of prioritization increases above some designated threshold. This may correspond to the amount of prioritization increasing dramatically such that other non-prioritized data transfer is at a standstill (e.g., where the amount of data in the low priority queues is above some high watermark threshold, etc.). In step 553, the end-user or automated system 522 determines that there is too much prioritization, and in step 554 utilizes the front-end interface 524 to communicate with the orchestration service 530 to request a reduction in prioritization level… It should be noted that the reduction in prioritization level may be for a limited time duration (e.g., suspend or otherwise reduce prioritization for a set period of time, or until some other designated condition is reached such as the amount of data in the low priority queues being below a low watermark threshold, etc.).” The determination of what constitutes “too much” prioritization being configurable can include “too much” prioritization indicating a low priority queue being below a high watermark threshold but above a low watermark threshold, which correlates to a first load level. The prioritization level being reduced so that the amount of data in the low priority queues transitions from above a low watermark threshold to below a low watermark threshold correlates to adjusting the prioritization value by a first increment value when the level of the information is classified into a first load level) and by a second increment value greater than the first increment value when the level of the information is classified into a second load level higher than the first load level (Paragraphs 63 and 66, “For example, it can be useful to reduce the prioritization in the case where so much prioritization occurs that it adversely affects the overall system. The determination of what constitutes “too much” prioritization may be user-configurable or selected based on the needs of a particular use case… In step 552, the amount of prioritization increases above some designated threshold. This may correspond to the amount of prioritization increasing dramatically such that other non-prioritized data transfer is at a standstill (e.g., where the amount of data in the low priority queues is above some high watermark threshold, etc.). In step 553, the end-user or automated system 522 determines that there is too much prioritization, and in step 554 utilizes the front-end interface 524 to communicate with the orchestration service 530 to request a reduction in prioritization level… It should be noted that the reduction in prioritization level may be for a limited time duration (e.g., suspend or otherwise reduce prioritization for a set period of time, or until some other designated condition is reached such as the amount of data in the low priority queues being below a low watermark threshold, etc.).” The determination of what constitutes “too much” prioritization being configurable can include “too much” prioritization indicating a low priority queue being below a high watermark threshold but above a low watermark threshold, which correlates to a first load level. This configurable indication would also trigger in scenarios where a low priority queue is above both a high watermark threshold and low watermark threshold, which correlates to a second load level higher than the first load level. The prioritization level being reduced so that the amount of data in the low priority queues transitions from above a high watermark threshold to below a low watermark threshold would involve a greater reduction in prioritization level than compared to the first load level and therefore correlates to adjusting the prioritization value by a second increment value greater than the first increment value when the level of the information is classified into a second load level higher than the first load level) ; selecting a queue to transmit a request to the distributed memory from among all the queues divided according to the priorities (Fig. 1, Paragraphs 26 and 41, “If requests are directed to one of the core-hosted services 108-C, the edge computing devices or edge nodes at the edge computing sites 104 will forward such requests to the management computing site 102. The management computing site 102 will service the requests, and provide responses (if applicable) back to the edge computing sites 104, which will in turn provide the responses back to the requesting client device 116… In step 202, at least a given portion of data stored in at least one of the two or more different processing queues in the first one of the two or more sets of processing queues is processed by the first one of the two or more services in the service chain. Step 202 may comprise selecting the given portion of the data stored in said at least one of the two or more different processing queues in the first one of the two or more sets of processing queues based at least in part on a designated prioritization level specifying relative frequency of selecting the given portion of the data from each of the two or more different processing queues in the first one of the two or more sets of processing queues.” A given portion of data stored in a specific queue which is selected based on a designated prioritization level correlates to selecting a queue from among all the queues divided according to the priorities. The given portion of data from the selected queue being forwarded to the management computing site to service the request correlates to selecting a queue to transmit a request to the distributed memory from among all the queues divided according to the priorities) ; and adjusting a bandwidth of the selected queue by using the prioritization value when the request of the selected queue is transmitted to the distributed memory (Paragraphs 26, 41, 64, “If requests are directed to one of the core-hosted services 108-C, the edge computing devices or edge nodes at the edge computing sites 104 will forward such requests to the management computing site 102. The management computing site 102 will service the requests, and provide responses (if applicable) back to the edge computing sites 104, which will in turn provide the responses back to the requesting client device 116… The designated prioritization level may be dynamically adjusted in response to detecting one or more designated conditions. The one or more designated conditions may comprise amounts of data stored in the two or more different processing queues in the two or more sets of processing queues. The designated prioritization level may be specified by an orchestrator service in the service chain. The orchestrator service in the service chain may dynamically adjust the designated prioritization level in response to requests from a management entity operating the service chain… A prioritization level of 90% means that applications, services or other software (e.g., IT assets 412, services 420, aggregator service 464) will check the higher priority queues first 90% of the time, and will check the normal or relatively lower priority queues first 10% of the time.” The applications, services, or other software checking higher priority queues first based on a corresponding percentage of the designated prioritization level of the processing queue correlates to adjusting a bandwidth of the selected queue by using the prioritization value. The prioritization level being dynamically adjusted based on the amounts of data stored in each queue, which may be decreased when a request is transmitted to the management computing site, correlates to adjusting a bandwidth of the selected queue by using the prioritization value when the request of the selected queue is transmitted to the distributed memory) . Kerrigan does not explicitly teach that the prioritization value is a throttle value . However, throttle values are a popular metric used to modify the bandwidth of queues as evidenced by Petty (Col. 6, lines 24-34 and 66-67, Col. 7, lines 1-3, “A trigger threshold indicates a change in queue depth that should be considered as significant to the trigger event processor 65. The value of the trigger threshold is expressed as a percentage of the maximum queue depth attribute of the queue. For example, if a queue's maximum queue depth is one thousand, then a value of one for this attribute would cause the trigger event processor 65 to re-evaluate the processing of the queue whenever its depth passes a multiple of ten messages, which equals 1 percentage of 1000 messages… If the message is determined to be a performance event low message, the trigger event processor reduces the queue depth high percentage by subtracting the value of the trigger threshold from the current value of the queue depth high percentage attribute.” The trigger threshold attribute value which is expressed as a percentage of the maximum queue depth correlates to a throttle value corresponding to the selected queue. The queue depth high percentage attribute value of the queue correlates to bandwidth of the selected queue. The value of the trigger threshold being subtracted from the current value of the queue depth high percentage correlates to the bandwidth of the selected queue being adjusted using the throttle value). Kerrigan does not explicitly teach: the priority-based scheduling method comprising: receiving a traffic load of queues divided according to priorities from a distributed memory configured to perform a load monitoring function; However, Manula teaches: the priority-based scheduling method comprising: receiving information of queues divided according to priorities from a distributed memory configured to perform a load monitoring function (Fig. 2, Paragraphs 22, 25 47, 69, 78, “Specifically, the resource pool (128) corresponds to the collection of hardware and stored data that is accessible by the host (100) and may be shared among virtual machines on the host (100) … As shown in FIG. 2, the HCA (200) may include multiple modules. Each module includes functionality to perform a task for processing a work request. The multiple modules may include one or more of … a descriptor fetch module (228) … In one or more embodiments of the invention, a queue descriptor (302) is a data structure which stores information about the location, contents and utilization of a queue (300). Specifically, each queue may have a corresponding queue descriptor… In Step 406, the descriptor fetch module fetches the queue descriptor from memory. Fetching may include reading the queue descriptor from memory and writing a copy of the queue descriptor into the appropriate cache… The production/consumption rate may calculated from expected traffic of the application using the queue, the volume of additional traffic on the network, the transmission rate of the network, the priority of the queue, and/or other factors.” The HCA including a resource pool with hardware and stored data shared among virtual machines correlates to distributed memory. The HCA including a descriptor fetch module to fetch a queue descriptor storing information about the contents and utilization of each queue correlates to receiving information of queues from a distributed memory configured to perform a load monitoring function. Each queue having an associated priority correlates to queues divided according to priorities) Kerrigan and Manula do not explicitly teach that the information of queues is a traffic load of queues . However, traffic load[s] of queues are a popular type of information associated with queues as evidenced by Mula below (Paragraphs 78-79, 84 and 87, “At 409, a time of dequeue of the task may be determined. The time of dequeue of the received task may be determined upon the task being removed or dequeued from the queue. The time of dequeue of the task may instead be a time of transmission, such as a time at which point the task is transmitted by the communication system 200 to a destination node… At 412, an estimated time duration of the task may be determined based on the time of enqueue and the time of dequeue according to each of the two or more clocks… At 415, based on the determined estimated time duration of the task according to each of the clocks, a latency of the task may be estimated. The estimated time duration of the task according to each clock may be compared to a threshold amount of time or a maximum time duration. If any one of the estimated time durations is greater than a maximum time duration, for example according to an SLA or user configuration settings, the task may be determined to be latent… In some embodiments, the computer system may be enabled to determine a latency error has occurred in response to determining a number of tasks exceed the latency threshold.” The system determining that the number of tasks has exceeded the latency threshold requires keeping track of the number of tasks which exceeded the latency threshold and therefore correlates to a traffic load of a queue). Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with the priority-based scheduling method comprising: receiving information of queues divided according to priorities from a distributed memory configured to perform a load monitoring function as taught by Manula because queue descriptors can store different possible thresholds or calculations for thresholds. These different thresholds can correspond to different observed rates of production and consumption or the number of sets of observed performance conditions. Cache control modules may then select an appropriate threshold from the queue descriptor or calculate a new value based on the observed metrics and calculations (Manula: paragraphs 79-81). Additionally, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with receiving a traffic load of queues as taught by Mula because latency errors can be detected in response to determining a number of tasks has exceeded a latency threshold. The computer system may also compare latencies of tasks of a common type to identify a source or destination of tasks and recording metadata associated with the error (Mula: paragraphs 86-88). It would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with a throttle value as taught by Petty because trigger threshold values can be used to indicate a change in queue depth that should be considered significant trigger events. The trigger threshold value in combination with the queue depth high percentage can also be used to categorize different types of messages as trigger or non-trigger messages (Petty: Col. 6, lines 24-34 and 53-67). With regards to Claim 14, the method of Claim 1 performs the same steps as the machine of Claim 14, and Claim 14 is therefore rejected using the same rationale set forth above in the rejection of Claim 1. With regards to Claim 2, Kerrigan in view of Manula, Mula and Petty teach the method of Claim 1 above. Mula further teaches: wherein the traffic load is calculated by counting cases of the number of requests recorded in the queue exceeding a preset comparison standard (Paragraphs 78-79, 84 and 87, “At 409, a time of dequeue of the task may be determined. The time of dequeue of the received task may be determined upon the task being removed or dequeued from the queue. The time of dequeue of the task may instead be a time of transmission, such as a time at which point the task is transmitted by the communication system 200 to a destination node… At 412, an estimated time duration of the task may be determined based on the time of enqueue and the time of dequeue according to each of the two or more clocks… At 415, based on the determined estimated time duration of the task according to each of the clocks, a latency of the task may be estimated. The estimated time duration of the task according to each clock may be compared to a threshold amount of time or a maximum time duration. If any one of the estimated time durations is greater than a maximum time duration, for example according to an SLA or user configuration settings, the task may be determined to be latent… In some embodiments, the computer system may be enabled to determine a latency error has occurred in response to determining a number of tasks exceed the latency threshold.” The estimated time duration of a task in the queue being compared to a threshold amount of time correlates to a request in a queue exceeding a present comparison standard. The system determining that the number of tasks has exceeded the latency threshold requires keeping track of the number of tasks which exceeded the latency threshold and therefore correlates to the traffic load being calculated by counting cases of the number of requests recorded in the queue exceeding a preset comparison standard) , Mula does not explicitly teach that each of the queues [are] divided according to the priorities of the distributed memory. However, each of the queues [being] divided according to the priorities of the distributed memory is a popular method of prioritization as evidenced by Kerrigan above (Paragraphs 21 and 40, “If requests are directed to one of the core-hosted services 108-C, the edge computing devices or edge nodes at the edge computing sites 104 will forward such requests to the management computing site 102. The management computing site 102 will service the requests, and provide responses (if applicable) back to the edge computing sites 104, which will in turn provide the responses back to the requesting client device 116… These steps are assumed to be performed by the management computing site 102 and the edge computing sites 104 utilizing the data transfer prioritization logic 110. The process begins with step 200, monitoring, by a first one of two or more services in a service chain, a first one of two or more sets of processing queues associated with the first one of the two or more services in the service chain, each of the two or more sets of processing queues comprising two or more different processing queues associated with two or more different priority levels. The two or more services in the service chain may comprise two or more microservices.” The two or more sets of processing queues which have different priority levels and are serviced by a management or edge computing site correlates to each of the queues being divided according to priorities of the distributed memory). Additionally, Manula further teaches: and the preset comparison standard comprises a greater value as distance latency between the host and the distributed memory increases (Fig. 1 and 5, paragraphs 22, 76 and 79, “Specifically, the resource pool (128) corresponds to the collection of hardware and stored data that is accessible by the host (100) and may be shared among virtual machines on the host (100)… FIG. 5 shows a flowchart for setting the queue descriptor threshold in accordance with one embodiment of the invention. The queue descriptor threshold may be set by the host in anticipation of certain needs and limitations of the system… In Step 504, the value of the threshold is calculated using the expected memory access latency and the expected production/consumption rate. In one or more embodiments of the invention, the threshold may be calculated by multiplying the memory access latency by the expected production/consumption rate by the HCA.” The HCA including a resource pool with hardware and stored data shared among virtual machines correlates to distributed memory. The memory access latency between the host and the HCA correlates to a distance latency between the host and the distributed memory. The queue descriptor threshold being calculated by multiplying the memory access latency with other values would increase as the input memory access latency value increases and therefore correlates to the preset comparison standard comprising a greater value as distance latency between the host and the distributed memory increases) . Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with and the preset comparison standard comprises a greater value as distance latency between the host and the distributed memory increases as taught by Manula because the expected access latency may be predetermined based on historical performance of memory and communication. It can reflect the expected volume of memory access requests, available caching resources, and limitations of the physical hardware. Using the expected memory access latency with the expected production or consumption rate to calculate a threshold can help to pad the threshold to account for variations in the aforementioned metrics (Manula: paragraphs 77 and 79). Additionally, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan wherein the traffic load is calculated by counting cases of the number of requests recorded in the queue exceeding a preset comparison standard as taught by Mula because latency errors can be detected in response to determining a number of tasks has exceeded a latency threshold. The computer system may also compare latencies of tasks of a common type to identify a source or destination of tasks and recording metadata associated with the error (Mula: paragraphs 86-88). With regards to Claims 8 and 15, the method of Claim 2 performs the same steps as the method and machine of Claims 8 and 15 respectively, and Claims 8 and 15 are therefore rejected using the same rationale set forth above in the rejection of Claim 2. With regards to Claim 4, Kerrigan in view of Manula, Mula and Petty teach the method of Claim 1 above. Kerrigan further teaches: wherein the selecting comprises: determining whether a bandwidth size corresponding to each of all the queues divided according to priorities is greater than or equal to a certain standard (Paragraphs 63-64 and 66, “The determination of what constitutes “too much” prioritization may be user-configurable or selected based on the needs of a particular use case. The level of prioritization can be throttled across a spectrum based on a percentage referred to herein as a prioritization level. A prioritization level of 100% means that applications, services or other software (e.g., IT assets 412, services 420, aggregator service 464) will always check higher priority queues first for data to process, so that the only time normal or relatively lower priority queues are checked is when the higher priority queues are empty… In step 551, the services 520 which process data files and objects register with the orchestration service 530 to receive updates on prioritization levels and other configurable prioritization parameters (e.g., including whether or not to enable prioritization at all). In step 552, the amount of prioritization increases above some designated threshold. This may correspond to the amount of prioritization increasing dramatically such that other non-prioritized data transfer is at a standstill (e.g., where the amount of data in the low priority queues is above some high watermark threshold, etc.). In step 553, the end-user or automated system 522 determines that there is too much prioritization, and in step 554 utilizes the front-end interface 524 to communicate with the orchestration service 530 to request a reduction in prioritization level.” The user-configurable or selected setting of what prioritization level constitutes “too much” prioritization correlates to a certain standard. The amount of prioritization for a queue increasing above some designated threshold and the end user or automated system determining that there is too much prioritization correlates to determining whether a bandwidth size corresponding to each of all the queues divided according to priorities is greater than or equal to a certain standard) ; and selecting a queue having a highest priority from the at least one queue determined to have the request to be processed as a queue to transmit a request to the distributed memory (Fig. 1, Paragraphs 26, 41 and 64, “If requests are directed to one of the core-hosted services 108-C, the edge computing devices or edge nodes at the edge computing sites 104 will forward such requests to the management computing site 102. The management computing site 102 will service the requests, and provide responses (if applicable) back to the edge computing sites 104, which will in turn provide the responses back to the requesting client device 116… In step 202, at least a given portion of data stored in at least one of the two or more different processing queues in the first one of the two or more sets of processing queues is processed by the first one of the two or more services in the service chain. Step 202 may comprise selecting the given portion of the data stored in said at least one of the two or more different processing queues in the first one of the two or more sets of processing queues based at least in part on a designated prioritization level specifying relative frequency of selecting the given portion of the data from each of the two or more different processing queues in the first one of the two or more sets of processing queues... A prioritization level of 100% means that applications, services or other software (e.g., IT assets 412, services 420, aggregator service 464) will always check higher priority queues first for data to process, so that the only time normal or relatively lower priority queues are checked is when the higher priority queues are empty.” A given portion of data stored in a specific queue which is selected based on a designated prioritization level, which specifies that higher priority queues are always checked first, correlates to selecting a queue having a highest priority from the at least one queue determined to have the request. The given portion of data from the selected queue being forwarded to the management computing site to service the request correlates to selecting a queue having a highest priority from the at least one queue determined to have the request to be processed as a queue to transmit a request to the distributed memory) . Manula further teaches: determining whether there is a request to be processed with respect to at least one queue having a utilization size that is greater than or equal to the certain standard (Fig. 4 and 6, paragraphs 72, 83, and 85, “In Step 412, the measured utilization of the queue is compared against the threshold. In Step 414, a determination is made whether the calculated utilization exceeds the threshold… In Step 600, the threshold is identified by the cache control module as having been exceeded. Step 600 may be performed the same or similar to Step 414 of FIG. 4, described above… In Step 604, a determination is made as to whether the available entries indicated by the queue descriptor in the cache are depleted. Specifically, an HCA module may attempt to obtain the next available entry based on the position of the software and hardware pointer.” The measured utilization of a queue being determined to exceed a threshold correlates to at least one queue having a utilization size greater than equal to the certain standard. The HCA module attempting to obtain the next available entry indicated by the queue descriptor correlates to determining whether there is a request to be processed with respect to at least one queue having a utilization size that is greater than or equal to the certain standard) ; Manula does not explicitly teach that the utilization size is a bandwidth size . However, bandwidth sizes are a popular type of metric compared to thresholds used with queues as evidenced by Kerrigan above (Paragraphs 63-64 and 66, “The determination of what constitutes “too much” prioritization may be user-configurable or selected based on the needs of a particular use case. The level of prioritization can be throttled across a spectrum based on a percentage referred to herein as a prioritization level. A prioritization level of 100% means that applications, services or other software (e.g., IT assets 412, services 420, aggregator service 464) will always check higher priority queues first for data to process, so that the only time normal or relatively lower priority queues are checked is when the higher priority queues are empty… In step 551, the services 520 which process data files and objects register with the orchestration service 530 to receive updates on prioritization levels and other configurable prioritization parameters (e.g., including whether or not to enable prioritization at all). In step 552, the amount of prioritization increases above some designated threshold. This may correspond to the amount of prioritization increasing dramatically such that other non-prioritized data transfer is at a standstill (e.g., where the amount of data in the low priority queues is above some high watermark threshold, etc.). In step 553, the end-user or automated system 522 determines that there is too much prioritization, and in step 554 utilizes the front-end interface 524 to communicate with the orchestration service 530 to request a reduction in prioritization level.” The user-configurable or selected setting of what prioritization level constitutes “too much” prioritization correlates to a certain standard. The amount of prioritization for a queue increasing above some designated threshold correlates to a bandwidth size greater than or equal to the certain standard). Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with determining whether there is a request to be processed with respect to at least one queue having a utilization size that is greater than or equal to the certain standard as taught by Manula because checking if the available entries indicated by the queue descriptor are depleted allow the HCA to determine that the queue has no remaining entries. This can signal that the current threshold is set too low, and additional incoming packets may not be stored, and could be dropped or returned to the sender until space in the queue is available (Manula: paragraph 85). With regards to Claim 17, the method of Claim 4 performs the same steps as the machine of Claim 17, and Claim 17 is therefore rejected using the same rationale set forth above in the rejection of Claim 4. With regards to Claim 6, Kerrigan in view of Manula, Mula and Petty teach the method of Claim 1 above. Petty further teaches: wherein the bandwidth of the selected queue is updated by subtracting a throttle value corresponding to the selected queue from the bandwidth (Col. 6, lines 24-34 and 66-67, Col. 7, lines 1-3, “A trigger threshold indicates a change in queue depth that should be considered as significant to the trigger event processor 65. The value of the trigger threshold is expressed as a percentage of the maximum queue depth attribute of the queue. For example, if a queue's maximum queue depth is one thousand, then a value of one for this attribute would cause the trigger event processor 65 to re-evaluate the processing of the queue whenever its depth passes a multiple of ten messages, which equals 1 percentage of 1000 messages… If the message is determined to be a performance event low message, the trigger event processor reduces the queue depth high percentage by subtracting the value of the trigger threshold from the current value of the queue depth high percentage attribute.” The trigger threshold attribute value which is expressed as a percentage of the maximum queue depth correlates to a throttle value corresponding to the selected queue. The queue depth high percentage attribute value of the queue correlates to bandwidth of the selected queue. The value of the trigger threshold being subtracted from the current value of the queue depth high percentage correlates to the bandwidth of the selected queue being updated by subtracting a throttle value corresponding to the selected queue from the bandwidth) . Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with wherein the bandwidth of the selected queue is updated by subtracting a throttle value corresponding to the selected queue from the bandwidth as taught by Petty because trigger threshold values can be used to indicate a change in queue depth that should be considered significant trigger events. The trigger threshold value in combination with the queue depth high percentage can also be used to categorize different types of messages as trigger or non-trigger messages (Petty: Col. 6, lines 24-34 and 53-67). With regards to Claims 13 and 19, the method of Claim 6 performs the same steps as the method and machine of Claims 13 and 19 respectively, and Claims 13 and 19 are therefore rejected using the same rationale set forth above in the rejection of Claim 6. With regards to Claim 7, Kerrigan teaches: A priority-based scheduling method performed by a host of a memory separation network (Fig. 1, paragraphs 29-30, “Although shown as an element of the management computing site 102 and the edge computing sites 104 in this embodiment, the data transfer prioritization logic 110 in other embodiments can be implemented at least in part externally to the management computing site 102 and the edge computing sites 104, for example, as a stand-alone server, set of servers or other types of systems coupled via one or more networks to the management computing site 102 and/or the edge computing sites 104. In some embodiments, the data transfer prioritization logic 110 may be implemented at least in part within one or more of the remote computing sites 106 and/or the client devices 116. The management computing site 102, the edge computing sites 104 and the remote computing sites 106 in the FIG. 1 embodiment are assumed to be implemented using at least one processing device. Each such processing device generally comprises at least one processor and an associated memory, and implements at least a portion of the functionality of the data transfer prioritization logic 110.” The processing devices which each have associated memory implementing at least a portion of the functionality of the data transfer prioritization logic across remote computing sites via a network correlates to a priority-based scheduling method performed by a host of a memory separation network) , updating a prioritization value of the queues divided according to the priorities at regular intervals by using the received information (Paragraphs 41 and 66, “The designated prioritization level may be dynamically adjusted in response to detecting one or more designated conditions. The one or more designated conditions may comprise amounts of data stored in the two or more different processing queues in the two or more sets of processing queues. The designated prioritization level may be specified by an orchestrator service in the service chain. The orchestrator service in the service chain may dynamically adjust the designated prioritization level in response to requests from a management entity operating the service chain… It should be noted that the reduction in prioritization level may be for a limited time duration (e.g., suspend or otherwise reduce prioritization for a set period of time, or until some other designated condition is reached such as the amount of data in the low priority queues being below a low watermark threshold, etc.).” The prioritization level of a queue correlates to a prioritization value of a queue. The prioritization level being dynamically adjusted in response to one or more conditions such as the amount of data stored in each queue with set time periods correlates to updating a prioritization value of the queues at regular intervals using the received information) , wherein the updating comprises classifying a level of the information into a plurality of load levels (Paragraph 66, “In step 552, the amount of prioritization increases above some designated threshold. This may correspond to the amount of prioritization increasing dramatically such that other non-prioritized data transfer is at a standstill (e.g., where the amount of data in the low priority queues is above some high watermark threshold, etc.) … In step 553, the end-user or automated system 522 determines that there is too much prioritization, and in step 554 utilizes the front-end interface 524 to communicate with the orchestration service 530 to request a reduction in prioritization level. It should be noted that the reduction in prioritization level may be for a limited time duration (e.g., suspend or otherwise reduce prioritization for a set period of time, or until some other designated condition is reached such as the amount of data in the low priority queues being below a low watermark threshold, etc.).” The system determining there is too much prioritization based on the amount of data in a specific low priority queue being above a high watermark threshold can also include an amount of data in different low priority queues being above or below a low or high watermark threshold. Therefore, the system determining there is too much prioritization based on the amount of data in the low priority queues being above or below a high watermark threshold and reducing the prioritization level correlates to the updating comprising classifying a level of the information into a plurality of load levels) and adjusting the prioritization value by a first increment value when the level of the information is classified into a first load level (Paragraphs 63 and 66, “For example, it can be useful to reduce the prioritization in the case where so much prioritization occurs that it adversely affects the overall system. The determination of what constitutes “too much” prioritization may be user-configurable or selected based on the needs of a particular use case… In step 552, the amount of prioritization increases above some designated threshold. This may correspond to the amount of prioritization increasing dramatically such that other non-prioritized data transfer is at a standstill (e.g., where the amount of data in the low priority queues is above some high watermark threshold, etc.). In step 553, the end-user or automated system 522 determines that there is too much prioritization, and in step 554 utilizes the front-end interface 524 to communicate with the orchestration service 530 to request a reduction in prioritization level… It should be noted that the reduction in prioritization level may be for a limited time duration (e.g., suspend or otherwise reduce prioritization for a set period of time, or until some other designated condition is reached such as the amount of data in the low priority queues being below a low watermark threshold, etc.).” The determination of what constitutes “too much” prioritization being configurable can include “too much” prioritization indicating a low priority queue being below a high watermark threshold but above a low watermark threshold, which correlates to a first load level. The prioritization level being reduced so that the amount of data in the low priority queues transitions from above a low watermark threshold to below a low watermark threshold correlates to adjusting the prioritization value by a first increment value when the level of the information is classified into a first load level) and by a second increment value greater than the first increment value when the level of the information is classified into a second load level higher than the first load level (Paragraphs 63 and 66, “For example, it can be useful to reduce the prioritization in the case where so much prioritization occurs that it adversely affects the overall system. The determination of what constitutes “too much” prioritization may be user-configurable or selected based on the needs of a particular use case… In step 552, the amount of prioritization increases above some designated threshold. This may correspond to the amount of prioritization increasing dramatically such that other non-prioritized data transfer is at a standstill (e.g., where the amount of data in the low priority queues is above some high watermark threshold, etc.). In step 553, the end-user or automated system 522 determines that there is too much prioritization, and in step 554 utilizes the front-end interface 524 to communicate with the orchestration service 530 to request a reduction in prioritization level… It should be noted that the reduction in prioritization level may be for a limited time duration (e.g., suspend or otherwise reduce prioritization for a set period of time, or until some other designated condition is reached such as the amount of data in the low priority queues being below a low watermark threshold, etc.).” The determination of what constitutes “too much” prioritization being configurable can include “too much” prioritization indicating a low priority queue being below a high watermark threshold but above a low watermark threshold, which correlates to a first load level. This configurable indication would also trigger in scenarios where a low priority queue is above both a high watermark threshold and low watermark threshold, which correlates to a second load level higher than the first load level. The prioritization level being reduced so that the amount of data in the low priority queues transitions from above a high watermark threshold to below a low watermark threshold would involve a greater reduction in prioritization level than compared to the first load level and therefore correlates to adjusting the prioritization value by a second increment value greater than the first increment value when the level of the information is classified into a second load level higher than the first load level) ; determining whether the host transmits a request to the distributed memory in an order from a highest priority (Fig. 1, Paragraphs 26 and 41, “If requests are directed to one of the core-hosted services 108-C, the edge computing devices or edge nodes at the edge computing sites 104 will forward such requests to the management computing site 102. The management computing site 102 will service the requests, and provide responses (if applicable) back to the edge computing sites 104, which will in turn provide the responses back to the requesting client device 116… In step 202, at least a given portion of data stored in at least one of the two or more different processing queues in the first one of the two or more sets of processing queues is processed by the first one of the two or more services in the service chain. Step 202 may comprise selecting the given portion of the data stored in said at least one of the two or more different processing queues in the first one of the two or more sets of processing queues based at least in part on a designated prioritization level specifying relative frequency of selecting the given portion of the data from each of the two or more different processing queues in the first one of the two or more sets of processing queues.” A given portion of data stored in a specific queue which is selected based on a designated prioritization level specifying relative frequency correlates to determining whether the host transmits a request in an order from a highest priority. The given portion of data from the selected queue being forwarded to the management computing site to service the request correlates to determining whether the host transmits a request to the distributed memory in an order from a highest priority) ; and updating a bandwidth for a queue of which a priority is lower than a priority of the queue determined to transmit the request (Paragraphs 26, 41, 64, “If requests are directed to one of the core-hosted services 108-C, the edge computing devices or edge nodes at the edge computing sites 104 will forward such requests to the management computing site 102. The management computing site 102 will service the requests, and provide responses (if applicable) back to the edge computing sites 104, which will in turn provide the responses back to the requesting client device 116… The designated prioritization level may be dynamically adjusted in response to detecting one or more designated conditions. The one or more designated conditions may comprise amounts of data stored in the two or more different processing queues in the two or more sets of processing queues. The designated prioritization level may be specified by an orchestrator service in the service chain. The orchestrator service in the service chain may dynamically adjust the designated prioritization level in response to requests from a management entity operating the service chain… A prioritization level of 90% means that applications, services or other software (e.g., IT assets 412, services 420, aggregator service 464) will check the higher priority queues first 90% of the time, and will check the normal or relatively lower priority queues first 10% of the time.” The applications, services, or other software checking higher priority queues first based on a corresponding percentage of the designated prioritization level of the processing queue correlates to updating a bandwidth of for a queue. The prioritization levels being dynamically adjusted based on the amounts of data stored in each queue, which includes both the queue selected to transmit a request and the queues not selected, correlates to adjusting a bandwidth of a queue of which a priority is lower than a priority of the queue determined to transmit the request) . Kerrigan does not explicitly teach: the priority-based scheduling method comprising: receiving a traffic load of queues divided according to priorities from a distributed memory configured to perform a load monitoring function; However, Manula teaches: the priority-based scheduling method comprising: receiving information of queues divided according to priorities from a distributed memory configured to perform a load monitoring function (Fig. 2, Paragraphs 22, 25 47, 69, 78, “Specifically, the resource pool (128) corresponds to the collection of hardware and stored data that is accessible by the host (100) and may be shared among virtual machines on the host (100) … As shown in FIG. 2, the HCA (200) may include multiple modules. Each module includes functionality to perform a task for processing a work request. The multiple modules may include one or more of … a descriptor fetch module (228) … In one or more embodiments of the invention, a queue descriptor (302) is a data structure which stores information about the location, contents and utilization of a queue (300). Specifically, each queue may have a corresponding queue descriptor… In Step 406, the descriptor fetch module fetches the queue descriptor from memory. Fetching may include reading the queue descriptor from memory and writing a copy of the queue descriptor into the appropriate cache… The production/consumption rate may calculated from expected traffic of the application using the queue, the volume of additional traffic on the network, the transmission rate of the network, the priority of the queue, and/or other factors.” The HCA including a resource pool with hardware and stored data shared among virtual machines correlates to distributed memory. The HCA including a descriptor fetch module to fetch a queue descriptor storing information about the contents and utilization of each queue correlates to receiving information of queues from a distributed memory configured to perform a load monitoring function. Each queue having an associated priority correlates to queues divided according to priorities) Kerrigan and Manula do not explicitly teach that the information of queues is a traffic load of queues . However, traffic load[s] of queues are a popular type of information associated with queues as evidenced by Mula above (Paragraphs 78-79, 84 and 87). Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with the priority-based scheduling method comprising: receiving information of queues divided according to priorities from a distributed memory configured to perform a load monitoring function as taught by Manula because queue descriptors can store different possible thresholds or calculations for thresholds. These different thresholds can correspond to different observed rates of production and consumption or the number of sets of observed performance conditions. Cache control modules may then select an appropriate threshold from the queue descriptor or calculate a new value based on the observed metrics and calculations (Manula: paragraphs 79-81). Additionally, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with receiving a traffic load of queues as taught by Mula because latency errors can be detected in response to determining a number of tasks has exceeded a latency threshold. The computer system may also compare latencies of tasks of a common type to identify a source or destination of tasks and recording metadata associated with the error (Mula: paragraphs 86-88). With regards to Claim 10, Kerrigan in view of Manula, Mula and Petty teach the method of Claim 7 above. Manula further teaches: wherein the determining comprises: determining whether to transmit a request by each of the queues, based on whether each of the queues comprises a request to be processed and a size of a utilization corresponding to each of the queues (Fig. 4 and 6, paragraphs 72, 83, and 85, “In Step 412, the measured utilization of the queue is compared against the threshold. In Step 414, a determination is made whether the calculated utilization exceeds the threshold… In Step 600, the threshold is identified by the cache control module as having been exceeded. Step 600 may be performed the same or similar to Step 414 of FIG. 4, described above… In Step 604, a determination is made as to whether the available entries indicated by the queue descriptor in the cache are depleted. Specifically, an HCA module may attempt to obtain the next available entry based on the position of the software and hardware pointer.” The HCA module attempting to obtain the next available entry indicated by the queue descriptor when the measured utilization of a queue exceeds a threshold correlates to determining whether to transmit a request by each of the queues based on whether each of the queues comprises a request to be processed and a size of a utilization corresponding to each of the queues) ; Manula does not explicitly teach that the utilization size is a bandwidth size and that each of the queues [are] divided according to the priorities . However, bandwidth sizes are a popular type of metric compared to thresholds used with queues as evidenced by Kerrigan above (Paragraphs 63-64 and 66) and each of the queues [being] divided according to the priorities is a popular method of prioritization as evidenced by Kerrigan above (Paragraphs 21 and 40). Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with wherein the determining comprises: determining whether to transmit a request by each of the queues, based on whether each of the queues comprises a request to be processed and a size of a utilization corresponding to each of the queues as taught by Manula because checking if the available entries indicated by the queue descriptor are depleted allow the HCA to determine that the queue has no remaining entries. This can signal that the current threshold is set too low, and additional incoming packets may not be stored, and could be dropped or returned to the sender until space in the queue is available (Manula: paragraph 85). With regards to Claim 11, Kerrigan in view of Manula, Mula and Petty teach the method of Claim 10 above. Manula further teaches: wherein the determining further comprises: transmitting a request to be processed when there is the request to be processed and a size of a utilization corresponding to each of the queues is greater than or equal to a certain standard by each of the queues (Fig. 4 and 6, paragraphs 72, 83, and 85, “In Step 412, the measured utilization of the queue is compared against the threshold. In Step 414, a determination is made whether the calculated utilization exceeds the threshold… In Step 600, the threshold is identified by the cache control module as having been exceeded. Step 600 may be performed the same or similar to Step 414 of FIG. 4, described above… In Step 604, a determination is made as to whether the available entries indicated by the queue descriptor in the cache are depleted. Specifically, an HCA module may attempt to obtain the next available entry based on the position of the software and hardware pointer.” The measured utilization of a queue being determined to exceed a threshold correlates to at least one queue having a utilization size greater than equal to the certain standard. The HCA module attempting to obtain the next available entry indicated by the queue descriptor when the measured utilization of a queue exceeds a threshold correlates to transmitting a request to be processed by each of the queues when there is a request to be processed and a size of a utilization corresponding to each of the queues is greater than or equal to a certain standard) ; Manula does not explicitly teach that the utilization size is a bandwidth size, that a request to be processed to the distributed memory [is transmitted] and that each of the queues [are] divided according to the priorities . However, bandwidth sizes are a popular type of metric compared to thresholds used with queues as evidenced by Kerrigan above (Paragraphs 63-64 and 66), each of the queues [being] divided according to the priorities is a popular method of prioritization as evidenced by Kerrigan above (Paragraphs 21 and 40), and transmitting a request to be processed to the distributed memory is a popular method of processing requests as evidenced by Kerrigan above (Fig. 1, Paragraphs 26 and 41, “If requests are directed to one of the core-hosted services 108-C, the edge computing devices or edge nodes at the edge computing sites 104 will forward such requests to the management computing site 102. The management computing site 102 will service the requests, and provide responses (if applicable) back to the edge computing sites 104, which will in turn provide the responses back to the requesting client device 116… In step 202, at least a given portion of data stored in at least one of the two or more different processing queues in the first one of the two or more sets of processing queues is processed by the first one of the two or more services in the service chain. Step 202 may comprise selecting the given portion of the data stored in said at least one of the two or more different processing queues in the first one of the two or more sets of processing queues based at least in part on a designated prioritization level specifying relative frequency of selecting the given portion of the data from each of the two or more different processing queues in the first one of the two or more sets of processing queues.” The given portion of data from the selected queue being forwarded to the management computing site to service the request correlates to transmitting a request to the distributed memory). Kerrigan further teaches: and determining whether to transmit a request by a queue having a lower priority than a queue when the queue does not comprise the request to be processed (Fig. 1, Paragraphs 26, 41 and 64, “If requests are directed to one of the core-hosted services 108-C, the edge computing devices or edge nodes at the edge computing sites 104 will forward such requests to the management computing site 102. The management computing site 102 will service the requests, and provide responses (if applicable) back to the edge computing sites 104, which will in turn provide the responses back to the requesting client device 116… In step 202, at least a given portion of data stored in at least one of the two or more different processing queues in the first one of the two or more sets of processing queues is processed by the first one of the two or more services in the service chain. Step 202 may comprise selecting the given portion of the data stored in said at least one of the two or more different processing queues in the first one of the two or more sets of processing queues based at least in part on a designated prioritization level specifying relative frequency of selecting the given portion of the data from each of the two or more different processing queues in the first one of the two or more sets of processing queues… A prioritization level of 100% means that applications, services or other software (e.g., IT assets 412, services 420, aggregator service 464) will always check higher priority queues first for data to process, so that the only time normal or relatively lower priority queues are checked is when the higher priority queues are empty.” The given portion of data from the selected queue being forwarded to the management computing site to service the request correlates to transmitting a request to the distributed memory. A normal or relatively lower priority queue being checked when the higher priority queues are empty correlates to determining whether to transmit a request by a queue having a lower priority than a queue when the queue does not comprise the request to be processed) or a size of a bandwidth corresponding to the queue is less than the certain standard. Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with wherein the determining further comprises: transmitting a request to be processed when there is the request to be processed and a size of a utilization corresponding to each of the queues is greater than or equal to a certain standard by each of the queues as taught by Manula because checking if the available entries indicated by the queue descriptor are depleted allow the HCA to determine that the queue has no remaining entries. This can signal that the current threshold is set too low, and additional incoming packets may not be stored, and could be dropped or returned to the sender until space in the queue is available (Manula: paragraph 85) . 07-21-aia AIA Claim (s) 3, 9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Kerrigan in view of Manula, Mula, Petty and Kodama et al. (U.S. Patent No. US 20220070074 A1), hereinafter “Kodama.” With regards to Claim 3, Kerrigan in view of Manula, Mula and Petty teach the method of Claim 2 above. Kerrigan in view of Manula, Mula and Petty does not explicitly teach: wherein the traffic load increases a count value even when a queue of a lower priority exceeds the preset comparison standard when a queue of a higher priority is counted, and is calculated through a percentage obtained by dividing the count value of each of the queues divided according to the priorities by a total count value. However, Kodama teaches: wherein the traffic load increases a count value even when a queue exceeds the preset comparison standard when a second queue is counted (Paragraphs 78 and 83, “The condition determination unit 114 determines whether or not an abnormality occurs in each receiving thread 12 on the basis of the correspondence relationship between the operation state of each receiving thread 12 and the number of packet losses of the queue 14 corresponding to each receiving thread 12 (the number of packet losses corresponding to the number of losses information 139) for each receiving thread 12… Then, in a case where the abnormality detection timing comes (YES in S101), the information processing device 1 calculates the occurrence degree of the packet loss in each of the multiple queues 14 on the basis of the time when each of the multiple receiving threads 12 is in the waiting state or the arrival frequency of the packet of each of the multiple queues 14 that stores the packets received by each of the multiple receiving threads 12 (S102).” The condition determination unit determining that an abnormality occurs based on the number of packet losses and operation state of each queue correlates to a queue exceeding the preset comparison standard. The occurrence degree in each of the multiple queues being calculated after the abnormality is detected correlates to increasing a count value even when a queue exceeds the preset comparison standard when a second queue is counted) , and is calculated through a percentage obtained by dividing the count value of each of the queues by a total count value (Paragraph 77, “For each queue 14, the number of losses distribution unit 113 acquires a rate calculated by dividing the occurrence degree indicated by the occurrence degree information 137 corresponding to each queue 14 by the total value of the occurrence degrees indicated by the occurrence degree information 137 corresponding to all the queues 14.” The occurrence degree for each queue correlates to the count value of each of the queues. The occurrence degree being divided by the total value of the occurrence degrees corresponding to all of the queues correlates to a percentage obtained by dividing the count value of each of the queues by a total count value) . Kodama does not explicitly teach that the queue is a queue of a lower priority, that the second queue is a queue of a higher priority, and that each of the queues [are] divided according to the priorities. However, having a queue of a lower priority , a queue of a higher priority, and each of the queues [being] divided according to the priorities are a popular method of prioritization as evidenced by Kerrigan above (Paragraphs 21 and 40). Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with wherein the traffic load increases a count value even when a queue exceeds the preset comparison standard when a second queue is counted and is calculated through a percentage obtained by dividing the count value of each of the queues by a total count value as taught by Kodama because acquiring information for each queue indicating the operating state compared to all other queues can be used to detect whether an abnormality of occurring in each thread or queue. The detection of an abnormality may be used by other units in the system for further analysis (Kodama: paragraphs 77-79 and 85-86). With regards to Claims 9 and 16, the method of Claim 3 performs the same steps as the method and machine of Claims 9 and 16 respectively, and Claims 9 and 16 are therefore rejected using the same rationale set forth above in the rejection of Claim 3 . 07-21-aia AIA Claim (s) 5, 12 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Kerrigan in view of Manula, Mula, Petty and Leonard et al. (U.S. Patent No. US 8185912 B1), hereinafter “Leonard.” With regards to Claim 5, Kerrigan in view of Manula, Mula and Petty teach the method of Claim 4 above. Kerrigan in view of Manula, Mula and Petty does not explicitly teach: wherein the selecting comprises: increasing a bandwidth by using the throttle value for a queue to which a corresponding bandwidth is less than the certain standard of all the queues divided according to the priorities, wherein the increased bandwidth is reflected on a next scheduling time. However, Leonard teaches: wherein the selecting comprises: increasing a bandwidth by using the value for a queue to which a corresponding bandwidth is less than the certain standard of all the queues divided according to the priorities, wherein the increased bandwidth is reflected on a next scheduling time (Col. 8, lines 43-47 and lines 55-65, “If the throughput is greater than or less than the cautionary range then the priority setting for the primary queue instance is not lowered. If the throughput remains in the cautionary range, additional determinations are made... If less than a threshold number of application interfaces are operating, the service agent component 240 may increase the number of application interfaces operating in association with the primary queue instance in an effort to increase the primary queue instance's throughput. After adding additional application interfaces, the service agent component 240 re-computes the throughput of the queue instance to determine if the throughput is still within the cautionary range. If the throughput is still within the cautionary range, additional application interfaces may be added.” Adding additional application interfaces to increase the throughput of the queue correlates to increasing the bandwidth for a queue. The total number of additional application interfaces added correlates to increasing a bandwidth by using the value for a queue. The queues having a priority setting correlates to the queues being divided according to the priorities. The service agent re-computing the throughput to check if the throughput is still within the cautionary range correlates to the corresponding bandwidth being less than the certain standard of all the queues divided according to the priorities. The additional application interfaces being added incrementally with the throughput of the queue being re-checked after each interval to reflect changes correlates to the increased bandwidth being reflected on a next scheduling time) . Leonard does not explicitly teach that the value is a throttle value . However, throttle values are a popular metric used to modify the bandwidth of queues as evidenced by Petty above (Col. 6, lines 24-34 and 66-67, Col. 7, lines 1-3, “A trigger threshold indicates a change in queue depth that should be considered as significant to the trigger event processor 65. The value of the trigger threshold is expressed as a percentage of the maximum queue depth attribute of the queue. For example, if a queue's maximum queue depth is one thousand, then a value of one for this attribute would cause the trigger event processor 65 to re-evaluate the processing of the queue whenever its depth passes a multiple of ten messages, which equals 1 percentage of 1000 messages… If the message is determined to be a performance event low message, the trigger event processor reduces the queue depth high percentage by subtracting the value of the trigger threshold from the current value of the queue depth high percentage attribute.” The trigger threshold attribute value which is expressed as a percentage of the maximum queue depth correlates to a throttle value corresponding to the selected queue. The queue depth high percentage attribute value of the queue correlates to bandwidth of the selected queue. The value of the trigger threshold being subtracted from the current value of the queue depth high percentage correlates to the bandwidth of the selected queue being updated using the throttle value). Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Kerrigan with wherein the traffic load increases a count value even when a queue exceeds the preset comparison standard when a second queue is counted and is calculated through a percentage obtained by dividing the count value of each of the queues by a total count value as taught by Leonard because cautionary ranges can be used to trigger the initial alarm based on historical performance data for queue instances. Cautionary ranges can cover performance areas where the throughput is less than expected under normal operating and more than expected if there is a problem present with the queue. This range can be used to detect serious problems with queue instances (Leonard: Col. 8, lines 17-34). With regards to Claims 12 and 18, the method of Claim 5 performs the same steps as the method and machine of Claims 12 and 18 respectively, and Claims 12 and 18 are therefore rejected using the same rationale set forth above in the rejection of Claim 5. Prior Art Made of Record 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Messick et al. (U.S. Patent No. US 20040042489 A1); teaching a method of managing bandwidth allocation in a storage area network. A policy is prepared that defines access parameters for multiple groups of client devices which are grouped according to priority in accessing network resources. The bandwidth is allocated dynamically based on the priority group with an upper and lower limit on the amount of bandwidth allocated to a group . Conclusion 07-40 AIA Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL . See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to SELINA HU whose telephone number is (571)272-5428. The examiner can normally be reached Monday-Friday 8:30-5:30. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chat Do can be reached at (571) 272-3721. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. The publicPAIR and privatePAIR systems are no longer available. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. SELINA HU Examiner Art Unit 2193 /Chat C Do/Supervisory Patent Examiner, Art Unit 2193 Application/Control Number: 18/224,860 Page 2 Art Unit: 2193 Application/Control Number: 18/224,860 Page 3 Art Unit: 2193 Application/Control Number: 18/224,860 Page 4 Art Unit: 2193 Application/Control Number: 18/224,860 Page 5 Art Unit: 2193 Application/Control Number: 18/224,860 Page 6 Art Unit: 2193 Application/Control Number: 18/224,860 Page 7 Art Unit: 2193 Application/Control Number: 18/224,860 Page 8 Art Unit: 2193 Application/Control Number: 18/224,860 Page 9 Art Unit: 2193 Application/Control Number: 18/224,860 Page 10 Art Unit: 2193 Application/Control Number: 18/224,860 Page 11 Art Unit: 2193 Application/Control Number: 18/224,860 Page 12 Art Unit: 2193 Application/Control Number: 18/224,860 Page 13 Art Unit: 2193 Application/Control Number: 18/224,860 Page 14 Art Unit: 2193 Application/Control Number: 18/224,860 Page 15 Art Unit: 2193 Application/Control Number: 18/224,860 Page 16 Art Unit: 2193 Application/Control Number: 18/224,860 Page 17 Art Unit: 2193 Application/Control Number: 18/224,860 Page 18 Art Unit: 2193 Application/Control Number: 18/224,860 Page 19 Art Unit: 2193 Application/Control Number: 18/224,860 Page 20 Art Unit: 2193 Application/Control Number: 18/224,860 Page 21 Art Unit: 2193 Application/Control Number: 18/224,860 Page 22 Art Unit: 2193 Application/Control Number: 18/224,860 Page 23 Art Unit: 2193 Application/Control Number: 18/224,860 Page 24 Art Unit: 2193 Application/Control Number: 18/224,860 Page 25 Art Unit: 2193 Application/Control Number: 18/224,860 Page 26 Art Unit: 2193 Application/Control Number: 18/224,860 Page 27 Art Unit: 2193 Application/Control Number: 18/224,860 Page 28 Art Unit: 2193 Application/Control Number: 18/224,860 Page 29 Art Unit: 2193 Application/Control Number: 18/224,860 Page 30 Art Unit: 2193 Application/Control Number: 18/224,860 Page 31 Art Unit: 2193 Application/Control Number: 18/224,860 Page 32 Art Unit: 2193 Application/Control Number: 18/224,860 Page 33 Art Unit: 2193 Application/Control Number: 18/224,860 Page 34 Art Unit: 2193 Application/Control Number: 18/224,860 Page 35 Art Unit: 2193 Application/Control Number: 18/224,860 Page 36 Art Unit: 2193 Application/Control Number: 18/224,860 Page 37 Art Unit: 2193 Application/Control Number: 18/224,860 Page 38 Art Unit: 2193 Application/Control Number: 18/224,860 Page 39 Art Unit: 2193 Application/Control Number: 18/224,860 Page 40 Art Unit: 2193 Application/Control Number: 18/224,860 Page 41 Art Unit: 2193 Application/Control Number: 18/224,860 Page 42 Art Unit: 2193 Application/Control Number: 18/224,860 Page 43 Art Unit: 2193 Application/Control Number: 18/224,860 Page 44 Art Unit: 2193 Application/Control Number: 18/224,860 Page 45 Art Unit: 2193 Application/Control Number: 18/224,860 Page 46 Art Unit: 2193 Application/Control Number: 18/224,860 Page 47 Art Unit: 2193 Application/Control Number: 18/224,860 Page 48 Art Unit: 2193 Application/Control Number: 18/224,860 Page 49 Art Unit: 2193 Application/Control Number: 18/224,860 Page 50 Art Unit: 2193 Application/Control Number: 18/224,860 Page 51 Art Unit: 2193 Application/Control Number: 18/224,860 Page 52 Art Unit: 2193 Application/Control Number: 18/224,860 Page 53 Art Unit: 2193
Prosecution Insights