DETAILED ACTION
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 claims filed on 07/08/2026.
Claims 1-25 are pending.
Claim Objections
Claim 10 is objected to because of the following informalities: “system of he device” should read “system of the . Appropriate correction is required.
Applicant is advised that should claim 8 be found allowable, claim 10 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Claim Rejections - 35 USC § 103
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.
Claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) further in view of Nachimuthu et al. (US 2018/0027063 A1).
Regarding claim 1, Tian teaches a computer-implemented method performed by a first device (Paragraph 92, Fig. 4 is the embodiment device of the method described in Fig. 2), the method comprising: … causing metrics information associated with the second device to be obtained (Paragraph 35, describes the first step 201 in Fig. 2 pertaining to obtaining the current utilization ratio of properties of physical devices), the metrics information indicating a measurement of a performance of a component of the second device, (Paragraph 35, the utilization ratio of properties of physical machines include components such as CPU load, memory load, and network load); determining a load of a processing unit of the second device based on the metrics information, (Paragraph 36, the paragraph describes step 202 in Fig. 2 which determines the mean load value of the device according the utilization ratio found in step 201); determining, based on the load of the processing unit, whether the second device is capable of executing a portion of a job via the second network (Paragraph 37, describes step 203 found in Fig. 2 which involves the deployment of a task based on the determined load from step 202); data associated with executing the portion of the job based on determining that the second device is capable of executing the portion of the job (Claim 1 determining, according to the current utilization ratios, physical machines that have residual capability satisfying a current task for allocating a virtual machine; predicting a load degree of each of the physical machines on the assumption that the virtual machine is allocated by each of the physical machines) and causing the second device to execute the portion of the job based on providing the data (Paragraph 37, describes step 203 found in Fig. 2 which involves the deployment of a task based on the determined load from step 202). However, Tian fails to teach reducing delays associated with a second device executing jobs by causing metrics information associated with the second device to be obtained, the delays being reduced by the metrics information being obtained by a third device from a controller associated with the second device via a first network; the metrics information being provided by the third device to the first device; providing data associated with executing the portion of the job based on determining that the second device is capable of executing the portion of the job; and causing the second device to execute the portion of the job based on providing the data.
In a similar field of endeavor Hassan teaches reducing delays associated with a second device executing jobs by causing metrics information associated with the second device to be obtained, (Paragraph 22 The intelligent engine 102 may determine how to route traffic received from one or more of the networks 104a-b based on the summarized utilization information 112a-b received from the monitors 108a-b. For example, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks l04a-b over network #4 104d instead of network #3 104c) the delays being reduced by the metrics information being obtained by a third device from a controller associated with the second device via a first network (Paragraph 21, For example, network elements 106a-c are shown to be configured to transmit usage information to monitor 108a, while network elements 106d-f are shown configured to transmit usage information to monitor 108b; Paragraph 22, intelligent engine 102 may determine how to route traffic received from one or more networks; Paragraph 40, As discussed above with respect to FIG. 1, dynamically allocating resources may include routing traffic over a first network (e.g. 104c) instead of a second network (e.g. 104d). For example, load may be routed over a network with a lower or more stable utilization and/or jitter instead of a network having higher utilization and/or jitter); the metrics information being provided by the third device to the first device; (Paragraph 21, The summarized information 112a-b may then be transmitted by the monitors 10Sa-b respectively to the intelligent engine 102) call traffic or call request messages, over the third network 104c or the fourth network 104d). providing data associated with executing the portion of the job based on determining that the second device is capable of executing the portion of the job (Paragraph 39, For example, the load may be allocated to a second computing resource … In some aspects, the computing resource may be a core within a multi-core hardware processor. In these aspects, decisions as to how to route processing tasks (data) to which core of the multi-core hardware processor may be based on the techniques of the present disclosure) and causing the second device to execute the portion of the job based on providing the data (Paragraph 16, If the number and/or frequency meet one or more criterion, a determination may be made that the resource is over utilized, and computing loads, such as network traffic, disk read and/or write requests, processing tasks, or other computing tasks depending on the various embodiments, may then be shifted to other, less utilized resources).Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add reducing delays associated with a second device executing jobs by causing metrics information associated with the second device to be obtained, the delays being reduced by the metrics information being obtained by a third device from a controller associated with the second device via a first network; the metrics information being provided by the third device to the first device; providing data associated with executing the portion of the job based on determining that the second device is capable of executing the portion of the job; and causing the second device to execute the portion of the job based on providing the data described in Hassan with the teachings of Tian because the task routing provided helps to reduce resource overutilization. However, Tian in view of Hassan fails to teach the metrics information being obtained by a third device from a controller associated with the second device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, the first network including an out-of-band network and the second network including a high speed network; executing a portion of a job via the second network; the data being provided to the second device via the second network; execute the portion of the job based on providing the data via the second network.
In a similar field of endeavor Nachimuthu teaches the metrics information being obtained by a third device from a controller associated with the second device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, (Nachimuthu Paragraph 94, In some instances, a management controller may send the metric data directly to the pod management controller in a REST architecture in a JSON data format via an OOB network. In another example, the management controller may send the metric data to the pod management controller via a rack management controller. A rack management controller may receive metric data from any number of sleds and physical resources of sleds to send to the pod management controller. The rack management controller may also send the metric in a REST architecture and JSON data format. Note that in both examples, the metric data may be sent to the pod management controller via an OOB network such that the metric data does not interfere with processing and data transfer on other networks, such as an optical fiber network) the first network including an out-of-band network and the second network including a high speed network; (Nachimuthu Paragraph 53, In embodiments, the pod management controller 1231 may couple with one or more racks 1202 via one or more Ethernet links as part of an out-of-band (OOB) network. In one example, the OOB network may be a separate network from an optical fiber network used to communicate data between the sleds, for example; Paragraph 29, Furthermore, in the illustrative embodiment, the data center 100 utilizes a single network architecture ("fabric") that supports multiple other network architectures including Ethernet and Onmi-Path. The sleds, in the illustrative embodiment, are coupled to switches via optical fibers, which provide higher bandwidth and lower latency than typical twister pair cabling ( e.g., Category 5, Category 5e, Category 6, etc.)) executing a portion of a job via the second network (Nachimuthu Paragraph 84, Note that the metric data may be communicated between the racks 1602 and the pod management controller 1631 via the OOB network; however, the one or more tasks may be communicated to the racks 1602 and particular resources 1605 via a different network, such as an optical fiber network; The pod management controller 1631 utilize the metric data to determine physical resources 1605 for processing one or more tasks of a workload) the data being provided to the second device via the second network (Nachimuthu Paragraph 84, Note that the metric data may be communicated between the racks 1602 and the pod management controller 1631 via the OOB network; however, the one or more tasks may be communicated to the racks 1602 and particular resources 1605 via a different network, such as an optical fiber network) execute the portion of the job based on providing the data via the second network (Nachimuthu Paragraph 84, The pod management controller 1631 may cause the one or more tasks to be processed by the determined physical resources 1605. Note that the metric data may be communicated between the racks 1602 and the pod management controller 1631 via the OOB network; however, the one or more tasks may be communicated to the racks 1602 and particular resources 1605 via a different network, such as an optical fiber network). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the metrics information being obtained by a third device from a controller associated with the second device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, the first network including an out-of-band network and the second network including a high speed network; executing a portion of a job via the second network; the data being provided to the second device via the second network; execute the portion of the job based on providing the data via the second network described in Nachimuthu with the teachings of Tian in view of Hassan because the out of band network prevents interference and bandwidth usage with other data (Nachimuthu Paragraph 67).
Claims 2-3, 21, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) further in view of Kim (US 2014/0373025).
Regarding claim 2, Tian in view of Hassan in view of Nachimuthu teaches the computer-implemented method of claim 1 (see above). However, Tian in view of Hassan in view of Nachimuthu fails to teach wherein determining the load comprises: obtaining, from a data structure and using the metrics information, information indicating the load of the second device associated with the measurement, wherein the data structure stores load information, indicating different loads of the processing unit, in association with metrics information indicating different measurements of a performance of the component, wherein the different measurements correspond to the different loads, and wherein the load information, indicating each load of the different loads, is stored in association with the metrics information indicating a corresponding measurement of the different measurements.
In a similar field of endeavor Kim teaches wherein determining the load comprises: obtaining, from a data structure and using the metrics information, information indicating the load of the second device associated with the measurement (Paragraph 90, processing part may obtain performance information and may store the performance information in a database and use the stored information in order to allocate processes requested later), wherein the data structure stores load information, indicating different loads of the processing unit, in association with metrics information indicating different measurements of a performance of the component (Paragraph 93, processing part may obtain performance of core included in each core group), wherein the different measurements correspond to the different loads, and wherein the load information, indicating each load of the different loads, is stored in association with the metrics information indicating a corresponding measurement of the different measurements (Paragraph 95, different information is obtained and stored relating to the load of the cores when running a process and is stored in a data structure such as table 2 which shows the different measurements associated with the different processes).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to apply the technique wherein determining the load comprises: obtaining, from a data structure and using the metrics information, information indicating the load of the second device associated with the measurement, wherein the data structure stores load information, indicating different loads of the processing unit, in association with metrics information indicating different measurements of a performance of the component, wherein the different measurements correspond to the different loads, and wherein the load information, indicating each load of the different loads, is stored in association with the metrics information indicating a corresponding measurement of the different measurements as described in Kim with the device of Tian in view of Hassan in view of Nachimuthu because the inclusion of a database storing the obtained metrics and load information will improve the access speed of these resources for the device to allocate jobs.
Regarding claim 3, Tian in view of Hassan in view of Nachimuthu in view of Kim teaches the computer-implemented method as described in claim 2 (see above). In addition, Tian teaches wherein the different loads are associated with the second device executing one or more applications, and wherein the different measurements are obtained during execution of the one or more applications by the second device (Paragraph 57-62, current task is a non-single virtual machine task such that the properties of each physical machine in the cluster must be obtained to determine the cluster which can deploy the task).
Regarding claim 21, Tian teaches a computer-implemented method performed by a first device (Fig. 2, A set of methods which can be implemented as program instructions which obtain current utilization information of each physical machine and determines the load of the machine based on the information gathered), the method comprising: … by causing metrics information associated with the second device to be obtained, the metrics information indicating different measurements of a performance of a component of the second device during an execution of an application by the second device, (Paragraph 35, Tian describes step 201 found in Fig. 2 which involves obtaining the current utilization ratios of properties found on each physical machine), and the different measurements being associated with different loads of the second device during the execution of the application by the second device; (Paragraph 35, obtain current utilization ratios of properties of each physical machine in a scheduling domain, and determine, according to the current utilization ratios, physical machines that have residual capability satisfying a current allocation task); obtaining particular metrics information indicating a particular measurement of the performance of the component (Paragraph 35, obtain the current utilization ratio of each physical machine, where the properties include a CPU load, memory load, and network load); providing data associated with executing a job based on a particular load, of the second device, associated with the particular measurement (paragraph 37, select a machine with minimal load variance to allocate task). However, Tian fails to teach reducing delays associated with a second device executing jobs by causing metrics information associated with the second device to be obtained, the delays being reduced by the metrics information being obtained by a third device from a controller associated with the second device via a first network; and causing the second device to execute the job based on the data.
In a similar field of endeavor Hassan teach reducing delays associated with a second device executing jobs by causing metrics information associated with the second device to be obtained, (Paragraph 22 The intelligent engine 102 may determine how to route traffic received from one or more of the networks 104a-b based on the summarized utilization information 112a-b received from the monitors 108a-b. For example, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks l04a-b over network #4 104d instead of network #3 104c) the delays being reduced by the metrics information being obtained by a third device from a controller associated with the second device via a first network (Paragraph 21, For example, network elements 106a-c are shown to be configured to transmit usage information to monitor 108a, while network elements 106d-f are shown configured to transmit usage information to monitor 108b; Paragraph 22, intelligent engine 102 may determine how to route traffic received from one or more networks; Paragraph 40, As discussed above with respect to FIG. 1, dynamically allocating resources may include routing traffic over a first network (e.g. 104c) instead of a second network (e.g. 104d). For example, load may be routed over a network with a lower or more stable utilization and/or jitter instead of a network having higher utilization and/or jitter); and causing the second device to execute the job based on the data (Paragraph 94, Each of the plurality of network devices may be a server, such as server 28A of FIG. 1, that is responsive to probing, the server executing the application for a respective data flow; Paragraph 85, In the example of network device 80, data plane 85 includes forwarding units 112 that provide high-speed forwarding of network traffic received by interface cards 114A-114N ("IFCs 44") via inbound links 116A-116N to outbound links 118A-118N). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the metrics information being obtained via a first network; determining, based on the load of the processing unit, whether the second device is capable of executing a portion of a job via a second network described in Hassan with the teachings of Tian because the task routing provided helps to reduce resource overutilization. However, Tian in view of Hasan fails to teach the metrics information being obtained by a third device from a controller associated with the second device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, the first network including an out-of-band network and the second network including a high speed network; the data being provided to the second device via the second network.
In a similar field of endeavor Nachimuthu teaches the metrics information being obtained by a third device from a controller associated with the second device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, (Nachimuthu Paragraph 94, In some instances, a management controller may send the metric data directly to the pod management controller in a REST architecture in a JSON data format via an OOB network. In another example, the management controller may send the metric data to the pod management controller via a rack management controller. A rack management controller may receive metric data from any number of sleds and physical resources of sleds to send to the pod management controller. The rack management controller may also send the metric in a REST architecture and JSON data format. Note that in both examples, the metric data may be sent to the pod management controller via an OOB network such that the metric data does not interfere with processing and data transfer on other networks, such as an optical fiber network) the first network including an out-of-band network and the second network including a high speed network; (Nachimuthu Paragraph 53, In embodiments, the pod management controller 1231 may couple with one or more racks 1202 via one or more Ethernet links as part of an out-of-band (OOB) network. In one example, the OOB network may be a separate network from an optical fiber network used to communicate data between the sleds, for example; Paragraph 29, Furthermore, in the illustrative embodiment, the data center 100 utilizes a single network architecture ("fabric") that supports multiple other network architectures including Ethernet and Onmi-Path. The sleds, in the illustrative embodiment, are coupled to switches via optical fibers, which provide higher bandwidth and lower latency than typical twister pair cabling ( e.g., Category 5, Category 5e, Category 6, etc.)) the data being provided to the second device via the second network; (Nachimuthu Paragraph 84, The pod management controller 1631 may cause the one or more tasks to be processed by the determined physical resources 1605. Note that the metric data may be communicated between the racks 1602 and the pod management controller 1631 via the OOB network; however, the one or more tasks may be communicated to the racks 1602 and particular resources 1605 via a different network, such as an optical fiber network). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the metrics information being obtained by a third device from a controller associated with the second device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, the first network including an out-of-band network and the second network including a high speed network; the data being provided to the second device via the second network; described in Nachimuthu with the teachings of Tian in view of Hassan because the out of band network prevents interference and bandwidth usage with other data (Nachimuthu Paragraph 67). However, Tian in view of Hasan in view of Nachimuthu fails to teach storing, in a data structure, the metrics information in association with load information indicating the different loads of the second device, the metrics information of a measurement, of the different measurements, being stored in association with a corresponding load of the different loads; the particular load being determined using the particular metrics information and the data structure.
In a similar field of endeavor Kim teaches teach storing, in a data structure, the metrics information in association with load information indicating the different loads of the second device (Paragraph 90, processing part may obtain performance information and may store the performance information in a database and use the stored information in order to allocate processes requested later), the metrics information of a measurement, of the different measurements, being stored in association with a corresponding load of the different loads (Paragraph 93, processing part may obtain performance of core included in each core group) the particular load being determined using the particular metrics information and the data structure (Paragraph 94, processing core may determine a core having a performance satisfying execution criteria for a core). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add storing, in a data structure, the metrics information in association with load information indicating the different loads of the second device, the metrics information of a measurement, of the different measurements, being stored in association with a corresponding load of the different loads; the particular load being determined using the particular metrics information and the data structure as described in Kim with Tian in view of Hassan in view of Nachimuthu because the use of a database to store information allows for quick access to frequently used data to help increase the speed at which the device can function.
Regarding claim 24, Tian teaches a computer program product for determining a device load, (Fig. 2, A set of methods which can be implemented as program instructions which obtain current utilization information of each physical machine and determines the load of the machine based on the information gathered) the computer program product comprising: one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, (Paragraph 159, Tian states that the steps of the methods may be implemented by program instructions that can be stored in computer readable storage medium), the program instructions comprising: program instructions to … causing metrics information associated with the device to be obtained, the metrics information indicating different measurements of a performance of a component of the second device during an execution of an application by the device, (Paragraph 35, Tian describes step 201 found in Fig. 2 which involves obtaining the current utilization ratios of properties found on each physical machine), and the different measurements corresponding to different loads of the device during the execution of the application by the device; (Paragraph 35, obtain current utilization ratios of properties of each physical machine in a scheduling domain, and determine, according to the current utilization ratios, physical machines that have residual capability satisfying a current allocation task); program instructions to obtain particular metrics information indicating a particular measurement of the performance of the component; (Paragraph 35, obtain the current utilization ratio of each physical machine, where the properties include a CPU load, memory load, and network load); program instructions to provide data associated with executing a job based on a particular load, of the device, associated with the particular measurement (paragraph 37, select a machine with minimal load variance to allocate task). However, Tian fails to teach reduce delays associated with a device executing jobs by causing metrics information associated with the device to be obtained, the delays being reduced by the metrics information being obtained by an additional device from a controller associated with the device via a first network; and cause the device to execute the job based on providing the data.
In a similar field of endeavor Hassan teach reduce delays associated with a device executing jobs by causing metrics information associated with the device to be obtained, (Paragraph 22 The intelligent engine 102 may determine how to route traffic received from one or more of the networks 104a-b based on the summarized utilization information 112a-b received from the monitors 108a-b. For example, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks l04a-b over network #4 104d instead of network #3 104c) the delays being reduced by the metrics information being obtained by an additional device from a controller associated with the device via a first network (Paragraph 21, For example, network elements 106a-c are shown to be configured to transmit usage information to monitor 108a, while network elements 106d-f are shown configured to transmit usage information to monitor 108b; Paragraph 22, intelligent engine 102 may determine how to route traffic received from one or more networks; Paragraph 40, As discussed above with respect to FIG. 1, dynamically allocating resources may include routing traffic over a first network (e.g. 104c) instead of a second network (e.g. 104d). For example, load may be routed over a network with a lower or more stable utilization and/or jitter instead of a network having higher utilization and/or jitter); and cause the device to execute the job based on providing the data (Paragraph 94, Each of the plurality of network devices may be a server, such as server 28A of FIG. 1, that is responsive to probing, the server executing the application for a respective data flow; Paragraph 85, In the example of network device 80, data plane 85 includes forwarding units 112 that provide high-speed forwarding of network traffic received by interface cards 114A-114N ("IFCs 44") via inbound links 116A-116N to outbound links 118A-118N). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add reduce delays associated with a device executing jobs by causing metrics information associated with the device to be obtained, the delays being reduced by the metrics information being obtained by an additional device from a controller associated with the device via a first network; and cause the device to execute the job based on providing the data described in Hassan with the teachings of Tian because the task routing provided helps to reduce resource overutilization. However, Tian in view of Hasan fails to teach the metrics information being obtained by an additional device from a controller associated with the device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, the first network including an out-of-band network and the second network including a high speed network; the data being provided to the device via the second network.
In a similar field of endeavor Nachimuthu teaches the metrics information being obtained by an additional device from a controller associated with the device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, (Nachimuthu Paragraph 94, In some instances, a management controller may send the metric data directly to the pod management controller in a REST architecture in a JSON data format via an OOB network. In another example, the management controller may send the metric data to the pod management controller via a rack management controller. A rack management controller may receive metric data from any number of sleds and physical resources of sleds to send to the pod management controller. The rack management controller may also send the metric in a REST architecture and JSON data format. Note that in both examples, the metric data may be sent to the pod management controller via an OOB network such that the metric data does not interfere with processing and data transfer on other networks, such as an optical fiber network) the first network including an out-of-band network and the second network including a high speed network; (Nachimuthu Paragraph 53, In embodiments, the pod management controller 1231 may couple with one or more racks 1202 via one or more Ethernet links as part of an out-of-band (OOB) network. In one example, the OOB network may be a separate network from an optical fiber network used to communicate data between the sleds, for example; Paragraph 29, Furthermore, in the illustrative embodiment, the data center 100 utilizes a single network architecture ("fabric") that supports multiple other network architectures including Ethernet and Onmi-Path. The sleds, in the illustrative embodiment, are coupled to switches via optical fibers, which provide higher bandwidth and lower latency than typical twister pair cabling ( e.g., Category 5, Category 5e, Category 6, etc.)) the data being provided to the device via the second network; (Nachimuthu Paragraph 84, The pod management controller 1631 may cause the one or more tasks to be processed by the determined physical resources 1605. Note that the metric data may be communicated between the racks 1602 and the pod management controller 1631 via the OOB network; however, the one or more tasks may be communicated to the racks 1602 and particular resources 1605 via a different network, such as an optical fiber network). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the metrics information being obtained by an additional device from a controller associated with the device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, the first network including an out-of-band network and the second network including a high speed network; the data being provided to the device via the second network described in Nachimuthu with the teachings of Tian in view of Hassan because the out of band network prevents interference and bandwidth usage with other data (Nachimuthu Paragraph 67). However, Tian in view of Hasan in view of Nachimuthu fails to teach storing, in a data structure, the metrics information in association with load information indicating the different loads of the second device, the metrics information of a measurement, of the different measurements, being stored in association with a corresponding load of the different loads; the particular load being determined using the particular metrics information and the data structure.
In a similar field of endeavor Kim teaches program instructions to store, in a data structure, the metrics information in association with load information indicating the different loads of the device (Paragraph 90, processing part may obtain performance information and may store the performance information in a database and use the stored information in order to allocate processes requested later), the metrics information of a measurement, of the different measurements, being stored in association with a corresponding load of the different loads (Paragraph 95, different information is obtained and stored relating to the load of the cores when running a process and is stored in a data structure such as table 2 which shows the different measurements associated with the different processes). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the program instructions to store, in a data structure, the metrics information in association with load information indicating the different loads of the device, the metrics information of a measurement, of the different measurements, being stored in association with a corresponding load of the different loads as described in Kim with Tian in view of Hassan in view of Nachimuthu because the inclusion of database can improve the accessibility of the metrics information for a quicker execution of instructions making use of that information.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in further view Schmidt et al. (US 2020/0233724).
Regarding claim 4, Tian in view of Hassan in view of Nachimuthu teaches the computer-implemented method of claim 1 (see above) and wherein the load of the processing unit includes an amount of usage of the processing unit (Tian, Paragraph 35, teaches the utilization ratio of properties of physical machines includes the CPU load). However, Tian in view of Hassan in view of Nachimuthu fails to teach wherein determining the load comprises: using a machine learning model to predict the load based on the metrics information indicating the measurement.
In a similar field of endeavor Schmidt teaches wherein determining the load comprises: using a machine learning model to predict the load based on the metrics information indicating the measurement (Paragraph 23, machine algorithm trained to provide as output a prediction of the performance of the workload). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the machine learning model to predict the load based on metrics information indicating the measurement as disclosed in Schmidt with Tian in view of Hassan in view of Nachimuthu because the use of a machine learning model can improve the efficiency of determining the workload by making use of the metric information.
Claims 5, 8, 10, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) further in view of Pai et al. (US 2017/0353496).
Regarding claim 5, Tian in view of Hassan in view of Nachimuthu teaches the computer-implemented method of claim 1 (see above), wherein obtaining the metrics information comprises: reducing disruptions over the second network by obtaining the metrics information from the third device, (Hassan, Paragraph 21, For example, network elements 106a-c are shown to be configured to transmit usage information to monitor 108a, while network elements 106d-f are shown configured to transmit usage information to monitor 108b; Paragraph 22, The intelligent engine 102 may determine how to route traffic received from one or more of the networks 104a-b based on the summarized utilization information 112a-b received from the monitors 108a-b. For example, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks 104a-b over network #4 104d instead of network #3 104c), wherein the metrics information is obtained, from the third device and from a controller associated with the second device, via the first network (Hassan, Paragraph 21. The network elements are configured to transmit utilization information to monitoring process and the information is then transmitted to the intelligent engine by the monitors), wherein the metrics information is obtained via the first network to reduce disruptions over the second network and reduce delays associated with the second device executing jobs based on reducing the disruptions (Hassan, Paragraph 14, The disclosed embodiments also provide support for subsequent decisions based on the analysis of this utilization information. Such decisions may include assigning at least some computing tasks to other computing resources instead of the subject computing resource, to at least partially reduce the utilization of the subject computing resource over the medium term. This reduction in utilization may restore the subject computing resource to more effective operation; Paragraph 22, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks 104a-b over network #4 104d instead of network #3 104c. In some aspects, the determination may be based on the detection of one or more spikes in utilization on the monitored network. In some aspects, an adaptive threshold may be used to determine whether a network is too heavily utilized to support additional traffic; Paragraph 41, For example, disk write requests or other file based operations may be routed to a stable storage device that is less heavily utilized than another stable storage device, reducing latency of write requests and/or file operations and load balancing the stable storage devices in some aspects). However, Tian in view of Hassan in view of Nachimuthu fails to explicitly teach wherein the first network is a network that is inaccessible to an operating system of the second device.
In a similar field of endeavor Pai teaches wherein the first network is a network that is inaccessible to an operating system of the second device (Paragraph 16, hardware-based isolation technique is used to isolate untrustworthy network resources from the operating system). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the first network is a network that is inaccessible to an operating system of the second device as taught in Pai with Tian in view of Hassan in view of Nachimuthu because this modification will improve the security between the devices over the network as any attacks will not be able to gain important control of the device.
Regarding claim 8, Tian teaches a computer program product for determining a load of a device (Fig. 2, A set of methods which can be implemented as program instructions which obtain current utilization information of each physical machine and determines the load of the machine based on the information gathered), the computer program product comprising of one or more computer readable storage media and program instructions collectively stored on the one or more computer readable storage media (Paragraph 159, Tian states that the steps of the methods may be implemented by program instructions that can be stored in computer readable storage medium), the program instructions comprising: program instructions to… by causing metrics information associated with the device to be obtained from the device, (Paragraph 35, describes the first step 201 in Fig. 2 pertaining to obtaining the current utilization ratio of properties of physical devices), the metrics information indicating a measurement of a performance of a component of the device, (Paragraph 35, the utilization ratio of properties of physical machines include components such as CPU load, memory load, and network load); program instructions to determine a load of a processing unit of the device based on the metrics information; (Paragraph 36, the paragraph describes step 202 in Fig. 2 which determines the mean load value of the device according the utilization ratio found in step 201 including CPU load); program instructions to provide data associated with executing a portion of the job based on determining the load of the processing unit, (Claim 1 determining, according to the current utilization ratios, physical machines that have residual capability satisfying a current task for allocating a virtual machine; predicting a load degree of each of the physical machines on the assumption that the virtual machine is allocated by each of the physical machines) and program instructions to cause the device to execute the portion of the job based on providing the data (Paragraph 37, describes step 203 found in Fig. 2 which involves the deployment of a task based on the determined load from step 202). However, Tian fails to teach reduce delays associated with the device executing jobs by causing metrics information associated with the device to be obtained from the device, the metrics information being obtained by an additional device from a controller associated with the device via a first network; program instruction to provide data associated with executing the portion of a job based on determining the load of the device, and program instructions to cause the device to execute the portion of the job based on providing the data.
In a similar field of endeavor Hassan teaches reduce delays associated with the device executing jobs by causing metrics information associated with the device to be obtained from the device, (Paragraph 22 The intelligent engine 102 may determine how to route traffic received from one or more of the networks 104a-b based on the summarized utilization information 112a-b received from the monitors 108a-b. For example, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks l04a-b over network #4 104d instead of network #3 104c) the metrics information being obtained by an additional device from a controller associated with the device via a first network (Paragraph 21, For example, network elements 106a-c are shown to be configured to transmit usage information to monitor 108a, while network elements 106d-f are shown configured to transmit usage information to monitor 108b); program instruction to provide data associated with executing the portion of a job based on determining the load of the device, (Paragraph 39, For example, the load may be allocated to a second computing resource … In some aspects, the computing resource may be a core within a multi-core hardware processor. In these aspects, decisions as to how to route processing tasks (data) to which core of the multi-core hardware processor may be based on the techniques of the present disclosure) and program instructions to cause the device to execute the portion of the job based on providing the data (Paragraph 16, If the number and/or frequency meet one or more criterion, a determination may be made that the resource is over utilized, and computing loads, such as network traffic, disk read and/or write requests, processing tasks, or other computing tasks depending on the various embodiments, may then be shifted to other, less utilized resources). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add reduce delays associated with the device executing jobs by causing metrics information associated with the device to be obtained from the device, the metrics information being obtained by an additional device from a controller associated with the device via a first network; program instruction to provide data associated with executing the portion of a job based on determining the load of the device, and program instructions to cause the device to execute the portion of the job based on providing the data described in Hassan with the teachings of Tian because the task routing provided helps to reduce resource overutilization. However, Tian in view of Hassan fails to teach the metrics information being obtained by an additional device from a controller associated with the device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, the first network including an out-of-band network and the second network including a high speed network; the data being provided to the device via the second network.
In a similar field of endeavor Nachimuthu teaches the metrics information being obtained by an additional device from a controller associated with the device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, (Nachimuthu Paragraph 94, In some instances, a management controller may send the metric data directly to the pod management controller in a REST architecture in a JSON data format via an OOB network. In another example, the management controller may send the metric data to the pod management controller via a rack management controller. A rack management controller may receive metric data from any number of sleds and physical resources of sleds to send to the pod management controller. The rack management controller may also send the metric in a REST architecture and JSON data format. Note that in both examples, the metric data may be sent to the pod management controller via an OOB network such that the metric data does not interfere with processing and data transfer on other networks, such as an optical fiber network) the first network including an out-of-band network and the second network including a high speed network; (Nachimuthu Paragraph 53, In embodiments, the pod management controller 1231 may couple with one or more racks 1202 via one or more Ethernet links as part of an out-of-band (OOB) network. In one example, the OOB network may be a separate network from an optical fiber network used to communicate data between the sleds, for example; Paragraph 29, Furthermore, in the illustrative embodiment, the data center 100 utilizes a single network architecture ("fabric") that supports multiple other network architectures including Ethernet and Onmi-Path. The sleds, in the illustrative embodiment, are coupled to switches via optical fibers, which provide higher bandwidth and lower latency than typical twister pair cabling ( e.g., Category 5, Category 5e, Category 6, etc.)) the data being provided to the device via the second network (Nachimuthu Paragraph 84, The pod management controller 1631 may cause the one or more tasks to be processed by the determined physical resources 1605. Note that the metric data may be communicated between the racks 1602 and the pod management controller 1631 via the OOB network; however, the one or more tasks may be communicated to the racks 1602 and particular resources 1605 via a different network, such as an optical fiber network). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the metrics information being obtained by an additional device from a controller associated with the device via a first network instead of obtaining the metrics information being obtained via a second network different than the first network, the first network including an out-of-band network and the second network including a high speed network; the data being provided to the device via the second network described in Nachimuthu with the teachings of Tian in view of Hassan because the out of band network prevents interference and bandwidth usage with other data (Nachimuthu Paragraph 67). However, Tian in view of Hassan in view of Nachimuthu fails to teach the first network being inaccessible to an operating system of the device.
In a similar field of endeavor Pai teaches the first network being inaccessible to an operating system of the device (Paragraph 16, hardware-based isolation technique is used to isolate untrustworthy network resources from the operating system). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the first network being inaccessible to an operating system of the device as taught in Pai with Tian in view of Hassan in view of Nachimuthu because this modification will improve the security between the devices over the network as any attacks will not be able to gain important control of the device.
Regarding claim 10, Tian in view of Hassan in view of Nachimuthu in view of Pai teaches the computer program product of claim 8 (see above), wherein the first network is inaccessible to an operating system of he device. (Pai paragraph 16, hardware-based isolation technique is used to isolate untrustworthy network resources from the operating system).
Regarding claim 15, Tian teaches a system comprising (Paragraph 92, Fig. 4 is the embodiment of the method described in Fig. 2): a first device configured to … obtaining metrics information associated with the second device, (Paragraph 93, Fig. 4 selection control module 41 obtains the utilizations ratio of properties of physical machines), the metrics information indicating a measurement of a performance of the second device (Paragraph 93, properties include CPU load, memory load, and network load); a third device (Paragraph 94 and 95, calculation processing module 42 and deployment unit 43) configured to: obtain the metrics information from the first device; determine a load of the second device based on the metrics information (Paragraph 94, module configured to determine the load value according to the current utilizations ratios); and cause the second device to execute a portion of a job based on the load of the second device (Paragraph 95, module configured to deploy allocation task to lowest load value). However, Tian fails to teach reduce delays associated with a second device executing jobs by obtaining metrics information associated with the second device, the delays being reduced by the metrics information being obtained from a controller associated with the second device via a first network, the metrics information being obtained via the first network to reduce disruptions over the second network and reduce delays associated with the second device executing jobs based on reducing the disruptions; determining, based on the load of the processing unit, whether the second device is capable of executing a portion of a job via a second network; provide data associated with executing a portion of a job based on determining the load.
In a similar field of endeavor Hassan teaches reduce delays associated with a second device executing jobs by obtaining metrics information associated with the second device, (Paragraph 22 The intelligent engine 102 may determine how to route traffic received from one or more of the networks 104a-b based on the summarized utilization information 112a-b received from the monitors 108a-b. For example, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks l04a-b over network #4 104d instead of network #3 104c) the delays being reduced by the metrics information being obtained from a controller associated with the second device via a first network, (Paragraph 21, For example, network elements 106a-c are shown to be configured to transmit usage information to monitor 108a, while network elements 106d-f are shown configured to transmit usage information to monitor 108b; Paragraph 22, intelligent engine 102 may determine how to route traffic received from one or more networks; Paragraph 40, As discussed above with respect to FIG. 1, dynamically allocating resources may include routing traffic over a first network (e.g. 104c) instead of a second network (e.g. 104d). For example, load may be routed over a network with a lower or more stable utilization and/or jitter instead of a network having higher utilization and/or jitter) the metrics information being obtained via the first network to reduce disruptions over the second network and reduce delays associated with the second device executing jobs based on reducing the disruptions (Paragraph 14, The disclosed embodiments also provide support for subsequent decisions based on the analysis of this utilization information. Such decisions may include assigning at least some computing tasks to other computing resources instead of the subject computing resource, to at least partially reduce the utilization of the subject computing resource over the medium term. This reduction in utilization may restore the subject computing resource to more effective operation; Paragraph 22, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks 104a-b over network #4 104d instead of network #3 104c. In some aspects, the determination may be based on the detection of one or more spikes in utilization on the monitored network. In some aspects, an adaptive threshold may be used to determine whether a network is too heavily utilized to support additional traffic; Paragraph 41, For example, disk write requests or other file based operations may be routed to a stable storage device that is less heavily utilized than another stable storage device, reducing latency of write requests and/or file operations and load balancing the stable storage devices in some aspects); provide data associated with executing a portion of a job based on determining the load, (Paragraph 39, For example, the load may be allocated to a second computing resource … In some aspects, the computing resource may be a core within a multi-core hardware processor. In these aspects, decisions as to how to route processing tasks (data) to which core of the multi-core hardware processor may be based on the techniques of the present disclosure). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add reduce delays associated with a second device executing jobs by obtaining metrics information associated with the second device, the delays being reduced by the metrics information being obtained from a controller associated with the second device via a first network, the metrics information being obtained via the first network to reduce disruptions over the second network and reduce delays associated with the second device executing jobs based on reducing the disruptions; determining, based on the load of the processing unit, whether the second device is capable of executing a portion of a job via a second network; provide data associated with executing a portion of a job based on determining the load described in Hassan with the teachings of Tian because the task routing provided helps to reduce resource overutilization. However, Tian in view of Hassan fails to teach the metrics information being obtained from a controller associated with the second device via a first network, … instead being obtained from a second network, the first network including an out-of-band network and the second network including a high speed network, the data being provided to the second device via the second network.
In a similar field of endeavor Nachimuthu teaches the metrics information being obtained from a controller associated with the second device via a first network, … instead being obtained from a second network, (Nachimuthu Paragraph 94, In some instances, a management controller may send the metric data directly to the pod management controller in a REST architecture in a JSON data format via an OOB network. In another example, the management controller may send the metric data to the pod management controller via a rack management controller. A rack management controller may receive metric data from any number of sleds and physical resources of sleds to send to the pod management controller. The rack management controller may also send the metric in a REST architecture and JSON data format. Note that in both examples, the metric data may be sent to the pod management controller via an OOB network such that the metric data does not interfere with processing and data transfer on other networks, such as an optical fiber network) the first network including an out-of-band network and the second network including a high speed network, (Nachimuthu Paragraph 53, In embodiments, the pod management controller 1231 may couple with one or more racks 1202 via one or more Ethernet links as part of an out-of-band (OOB) network. In one example, the OOB network may be a separate network from an optical fiber network used to communicate data between the sleds, for example; Paragraph 29, Furthermore, in the illustrative embodiment, the data center 100 utilizes a single network architecture ("fabric") that supports multiple other network architectures including Ethernet and Onmi-Path. The sleds, in the illustrative embodiment, are coupled to switches via optical fibers, which provide higher bandwidth and lower latency than typical twister pair cabling ( e.g., Category 5, Category 5e, Category 6, etc.)) the data being provided to the second device via the second network; (Nachimuthu Paragraph 84, The pod management controller 1631 may cause the one or more tasks to be processed by the determined physical resources 1605. Note that the metric data may be communicated between the racks 1602 and the pod management controller 1631 via the OOB network; however, the one or more tasks may be communicated to the racks 1602 and particular resources 1605 via a different network, such as an optical fiber network). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the metrics information being obtained from a controller associated with the second device via a first network, … instead being obtained from a second network, the first network including an out-of-band network and the second network including a high speed network, the data being provided to the second device via the second network described in Nachimuthu with the teachings of Tian in view of Hassan because the out of band network prevents interference and bandwidth usage with other data (Nachimuthu Paragraph 67). However, Tian in view of Hassan in view of Nachimuthu fails to teach a first network, that is inaccessible to an operating system of the second device.
In a similar field of endeavor Pai teaches a first network, that is inaccessible to an operating system of the second device, (Paragraph 16, hardware-based isolation technique is used to isolate untrustworthy network resources from the operating system). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add a first network, that is inaccessible to an operating system of the second device, as taught in Pai with Tian in view of Hassan in view of Nachimuthu because this modification will improve the security between the devices over the network as any attacks will not be able to gain important control of the device.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) further in view of Lee et al. (US 2019/0163540).
Regarding claim 6, Tian in view of Hassan in view of Nachimuthu teaches the computer-implemented method of claim 1 (see above), wherein the component includes the processing unit (Tian, Paragraph 35, teaches the utilization ratio of properties of physical machines includes components such as CPU load). However, Tian in view of Hassan in view of Nachimuthu fails to teach wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the processing unit, and wherein determining the load of the processing unit based on the metrics information comprises: determining the load of the processing unit based on the measurement of the power consumption of the processing unit.
In a similar field of endeavor Lee teaches wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the processing unit (Paragraph 18, monitor program and hardware component system monitor observe the components of the nodes during runtime and ranks the power efficiency consumption), and wherein determining the load of the processing unit based on the metrics information comprises: determining the load of the processing unit based on the measurement of the power consumption of the processing unit (Paragraph 41, the job scheduler program analyzes the power consumption of a task and determines if the task has reached any threshold conditions to be used to determine where to allocate the task). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the processing unit, and wherein determining the load of the processing unit based on the metrics information comprises: determining the load of the processing unit based on the measurement of the power consumption of the processing unit as taught by Lee with Tian in view of Hassan in view of Nachimuthu because the inclusion of the power consumption in the processing unit of the device will increase the accuracy of the determine load and allow for a more accurate job allocation.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) further view of Hyatt et al. (US 2023/0029380) further in view of Lee et al. (US 2019/0163540).
Regarding claim 7, Tian in view of Hassan in view of Nachimuthu teaches the computer-implemented method of claim 1 (see above). However, Tian in view of Hassan in view of Nachimuthu fails to teach wherein the component includes a dynamic random access memory, wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the dynamic random access memory, and wherein determining the load of the processing unit based on the metrics information comprises: determining the load of the processing unit based on the measurement of the power consumption of the dynamic random access memory.
In a similar field of endeavor Hyatt in view of Lee teaches wherein the component includes a dynamic random access memory (Hyatt Paragraph 54, computing platform has physical computing resources including DRAM, NVMe SSD, PCM and the like), wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the dynamic random access memory (Hyatt Paragraph 124, resource monitoring engine may continuously monitor defined parameters of resources based on the resource monitoring policy. Such parameters include the resource utilization levels, temperature, and power consumption), and wherein determining the load of the processing unit based on the metrics information comprises: determining the load of the processing unit based on the measurement of the power consumption of the dynamic random access memory (Hyatt Paragraph 124, resource monitoring engine may continuously monitor defined parameters of resources based on the resource monitoring policy. Such parameters include the resource utilization levels, temperature, and power consumption. Lee Paragraph 41, the job scheduler program analyzes the power consumption of a task and determines if the task has reached any threshold conditions to be used to determine where to allocate the task).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include wherein the component includes a dynamic random access memory, wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the dynamic random access memory, and wherein determining the load of the processing unit based on the metrics information comprises: determining the load of the processing unit based on the measurement of the power consumption of the dynamic random access memory as described in Hyatt in view of Lee into the teachings of Tian in view of Hassan in view of Nachimuthu because this inclusion creates a more accurate portrayal of the resource utilization when determining the workload by making use of the power consumption of DRAM.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) further in view of Sivasubramanian et al. (US 2015/0378764).
Regarding claim 9, Tian in view of Hassan in view of Nachimuthu in view of Pai teaches the computer program product of claim 8 (see above), wherein the program instructions to determine the load of the device based on the metrics information (Paragraph 36, Tian describes step 202 of Fig. 2 which is determining the load values of the machines based on the obtained utilization ratios found in previous step 201). However, Tian in view of Hassan in view of Nachimuthu in view of Pai fails to teach program instructions to determine a memory pressure of a memory associated with a processing unit of the device based on the measurement of the performance of the component of the device.
In a similar field of endeavor Sivasubramanian teaches program instructions to determine a memory pressure of a memory associated with a processing unit of the device based on the measurement of the performance of the component of the device (Paragraph 78, memory pressure index may be calculated within a range where a minimum value of memory pressure may be assigned based on active utilization metrics). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the program instructions to determine the memory pressure of a memory associated with a processing unit of the device based on the measurement of the performance of the component as described in Sivasubramanian with Tian in view of Hassan in view of Nachimuthu in view of Pai because this addition will improve the accuracy of the determined load and help execute the job based on the load.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) further in view of Kim (US 2014/0373025).
Regarding claim 11, Tian on view of Hassan in view of Nachimuthu in view of Pai teaches the computer program product of claim 8 (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Pai fails to teach wherein the program instructions to determine the load of the device include: program instructions to obtain, from a data structure and using the metrics information, load information indicating the load of the device, wherein the metrics information is stored, in the data structure, in association with the load information, and wherein the load information indicates the load of the device.
In a similar field of endeavor Kim teaches wherein the program instructions to determine the load of the device include: program instructions to obtain, from a data structure and using the metrics information, load information indicating the load of the device (Paragraph 90, processing part may obtain performance information and may store the performance information in a database and use the stored information in order to allocate processes requested later), wherein the metrics information is stored, in the data structure, in association with the load information (Paragraph 94, processing part may obtain performance of each core required for executing a the process), and wherein the load information indicates the load of the (Paragraph 95, different information is obtained and stored relating to the load of the cores when running a process and is stored in a data structure such as table 2 which shows the different measurements associated with the different processes). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the program instructions to determine the load of the device include: program instructions to obtain, from a data structure and using the metrics information, load information indicating the load of the device, wherein the metrics information is stored, in the data structure, in association with the load information, and wherein the load information indicates the load of the device as described in Kim with Tian in view of Hassan in view of Nachimuthu in view of Pai because the inclusion of a database storing the obtained metrics and load information will improve the access speed of these resources for the device to allocate executing jobs.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) in view of Wong et al. (US 2023/0102063) further in view of Lee et al. (US 2019/0163540).
Regarding claim 12, Tian in view of Hassan in view of Nachimuthu in view of Pai teaches the computer program product of claim 8 (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Pai fails to teach wherein the component includes a Peripheral Component Interconnect Express (PCIe) bus, wherein the measurement of the performance of the component includes a measurement of a power consumption of the PCIe bus, and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the measurement of the power consumption of the PCIe bus.
In similar field of endeavor Wong in view of Lee teaches wherein the component includes a Peripheral Component Interconnect Express (PCIe) bus, wherein the measurement of the performance of the component includes a measurement of a power consumption of the PCIe bus (Wong Paragraph 36, inspecting run utilization metrics of processing resources can include bus interfaces such as PCIE interface, and the utilization of these resources can be expressed by power consumption), and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the measurement of the power consumption of the PCIe bus (Lee Paragraph 41, the job scheduler program analyzes the power consumption of a task, such as determined in Wong, and determines if the task has reached any threshold conditions to be used to determine where to allocate the task). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include wherein the component includes a Peripheral Component Interconnect Express (PCIe) bus, wherein the measurement of the performance of the component includes a measurement of a power consumption of the PCIe bus, and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the measurement of the power consumption of the PCIe bus as described in Wong in view of Lee with Tian in view of Hassan in view of Nachimuthu in view of Pai because the extra information provided by the measurement of more components allows for a more accurate value of the load to be determined.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) in view of Nastacio (US 2012/0046800).
Regarding claim 13, Tian in view of Hassan in view of Nachimuthu in view of Pai teaches the computer program product of claim 8 (see above). However, Tian in view of Hassan in view of Nachimuthu fails to teach wherein the component includes a cooling system of the device, wherein the measurement of the performance of the component includes a measurement of a performance of the cooling system, and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the measurement of the performance of the cooling system.
In similar field of endeavor Nastacio teaches wherein the component includes a cooling system of the device (Paragraph 36, cooling correspondence tool included as an application for computing the weighted mapping of thermal relationship between server and cooling unit), wherein the measurement of the performance of the component includes a measurement of a performance of the cooling system (Paragraph 36, cooling correspondence tool included as an application for computing the weighted mapping of thermal relationship between server and cooling unit), and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the measurement of the performance of the cooling system (Paragraph 36, workload planning application may use cooling correspondence data from cooling corresponded tool to plan out workloads). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add the component includes a cooling system of the device, wherein the measurement of the performance of the component includes a measurement of a performance of the cooling system, and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the measurement of the performance of the cooling system as described in Nastachio with Tian in view of Hassan in view of Nachimuthu in view of Pai because the inclusion of the metric information of the cooling unit adds extra information when determining the load for increased precision of the current utilization.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) in view of Sahasranamam et al. (US 2022/0164229).
Regarding claim 14, Tian in view of Hassan in view of Nachimuthu teaches the computer program product of claim 8 (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Pai falls to teach wherein the component includes a fan of the device, wherein the measurement of the performance of the component includes a measurement of a fan speed of the fan, and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the fan speed.
In a similar field of endeavor, Sahasranamam teaches wherein the component includes a fan of the device, wherein the measurement of the performance of the component includes a measurement of a fan speed of the fan (paragraph 26, resource label monitored for information can include the fan speed), and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the fan speed (paragraph 31, management node may obtain the resource labels and manage a workload based on the resource labels obtained from the worker nodes). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the component includes a fan of the device, wherein the measurement of the performance of the component includes a measurement of a fan speed of the fan, and wherein the program instructions to determine the load of the device based on the metrics information comprises: program instructions to determine a load of a processing unit of the device based on the fan speed as described by Sahasranamam with Tian in view of Hassan in view of Nachimuthu in view of Pai because the inclusion of the fan and fan speed in the metrics information for determining the load will increase the accuracy when determining the current load for reference when executing a job.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) in further view of MacNamara et al. (US 2021/0117307).
Regarding claim 16, Tian in view of Hassan in view of Nachimuthu in view of Nachimuthu in view of Pai teaches the system of claim 15 (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Pai fails to teach wherein the measurement of the performance of the second device includes a power management mode of the second device, and wherein the third device, to determine the load of the second device, is configured to: determine the load of the second device based on the power management mode of the second device.
In a similar field of endeavor MacNamara teaches wherein the measurement of the performance of the second device includes a power management mode of the second device (Paragraph 28, a host CPU typically support multiple power modes that can be configured to provide optimal performance for a workload), and wherein the third device, to determine the load of the second device, is configured to: determine the load of the second device based on the power management mode of the second device (Paragraph 38, power modes provide more control over processors for optimal performance as cores running more critical workloads can be controlled by different nodes. Tian Paragraph 36, the paragraph describes step 202 in Fig. 2 which determines the mean load value of the device according the utilization ratio found in step 201 including the CPU load). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the measurement of the performance of the second device includes a power management mode of the second device, and wherein the third device, to determine the load of the second device, is configured to: determine the load of the second device based on the power management mode of the second device as described by MacNamara with Tian in view of Hassan in view of Nachimuthu in view of Pai because the inclusion of the power mode will allow for increased accuracy of the determined load when executing a job based on the power management mode of the CPU load.
Claims 17 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) in further view of Sunwoo et al. (US 2022/0035679).
Regarding claim 17, Tian in view of Hassan in view of Nachimuthu in view of Pai teaches the system of claim 15 (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Pai fails to teach wherein the measurement of the performance of the second device includes a number of instructions per a period of time, and wherein the third device, to determine the load of the second device, is configured to: determine the load of the second device based on the number of instructions per the period of time.
In a similar field of endeavor Sunwoo teaches wherein the measurement of the performance of the second device includes a number of instructions per a period of time, and wherein the third device, to determine the load of the second device, is configured to: determine the load of the second device based on the number of instructions per the period of time ( Paragraph 42, performance monitoring data may include performance counter values, such as cache miss branch misprediction, or a number of instruction excited in a given time period, which indicate counts of various events associated with processing workloads). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the measurement of the performance of the second device includes a number of instructions per a period of time, and wherein the third device, to determine the load of the second device, is configured to: determine the load of the second device based on the number of instructions per the period of as described by Sunwoo with Tian in view of Hassan in view of Nachimuthu in view of Pai because the modification by adding in the amount of instruction per a period of time will give an increase in accuracy when determining the load which will be used as basis for executing a job.
Regarding claim 19, Tian in view of Hassan in view of Nachimuthu in view of Pai teaches the system of claim 15 (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Pai fails to teach wherein the third device, to determine the load of the second device, is configured to: provide the metrics information as an input to a machine learning model; and determine the load of the second device based on an output of the machine learning model.
In a similar field of endeavor Sunwoo teaches wherein the third device, to determine the load of the second device, is configured to: provide the metrics information as an input to a machine learning model; and determine the load of the second device based on an output of the machine learning model (Paragraph 133 and 134, input data for machine learning can be an array of performance monitoring data gather for a particular workload, and the output data of the machine learning model resource suitability metric indicating a value which is suitable for executing a workload). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the third device, to determine the load of the second device, is configured to: provide the metrics information as an input to a machine learning model; and determine the load of the second device based on an output of the machine learning models described in Sunwoo with Tian in view of Hassan in view of Nachimuthu in view of Pai because the modification can increase the likelihood of suitable resource allocation for a workload.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) in view of Sunwoo et al. (US 2022/0035679) in further view of Sivasubramanian et al. (US 2015/0378764).
Regarding claim 18, Tian in view of Hassan in view of Nachimuthu in view of Pai in view of Sunwoo teaches the system of claim 17 (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Pai in view of Sunwoo fails to teach wherein the third device, to determine the load of the second device, is configured to: determine a memory pressure of a memory associated with a processing unit of the second device based on the number of instructions per the period of time.
In a similar field of endeavor Sivasubramanian teaches wherein the third device, to determine the load of the second device, is configured to: determine a memory pressure of a memory associated with a processing unit of the second device based on the number of instructions per the period of time (Paragraph 39, memory pressure index calculator configured to quantify the number and rate of ballooning/swapping operations. Then the memory pressure calculator index may be configured to determine the overall memory pressure). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the third device, to determine the load of the second device, is configured to: determine a memory pressure of a memory associated with a processing unit of the second device based on the number of instructions per the period of time as described in Sivasubramanian with Tian in view of Hassan in view of Nachimuthu in view of Pai in view of Sunwoo because the addition of the memory pressure of a memory based on the number of instruction per period of time will increase the accuracy of the determined load which will allow for more accurate execution of a job based on that load.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Pai et al. (US 2017/0353496) in further view of Lee at al. (US 2019/0163540).
Regarding claim 20, Tian in view of Hassan in view of Nachimuthu in view of Pai teaches the system of claim 15 (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Pai fails to teach wherein the measurement of the performance of the second device includes a measurement of a power consumption of a processing unit of the second device, and wherein the third device, to determine the load of the second device, is configured to: determine the load of the processing unit based on the measurement of the power consumption of the processing unit.
In a similar field of endeavor Lee teaches wherein the measurement of the performance of the second device includes a measurement of a power consumption of a processing unit of the second device, and wherein the third device (Paragraph 18, monitor program ranks the power efficiency consumption of the nodes that make up the data center), to determine the load of the second device, is configured to: determine the load of the processing unit based on the measurement of the power consumption of the processing unit (Paragraph 41, the job scheduler program analyzes the power consumption of a task and determines if the task has reached any threshold conditions to be used to determine where to allocate the task). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add teach wherein the measurement of the performance of the second device includes a measurement of a power consumption of a processing unit of the second device, and wherein the third device, to determine the load of the second device, is configured to: determine the load of the processing unit based on the measurement of the power consumption of the processing unit as described in Lee with Tian in view of Hassan in view of Nachimuthu in view of Pai because the use of the power consumption in determining the load will give a more precise portrayal of the current load when using the load as a basis for executing a job.
Claims 22 and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Kim (US 2014/0373025) further in view of Pai et al. (US 2017/0353496).
Regarding claim 22, Tian in view of Hassan in view of Nachimuthu in view of Kim teaches the computer-implemented method of claim 21 (see above), wherein obtaining the metrics information comprises: obtaining the metrics information from a third device, (Tian, Paragraph 35, obtain the current utilization ratio of each physical machine, where the properties include a CPU load, memory load, and network load). wherein the metrics information is obtained, from the third device and from the second device, (Hassan, Paragraph 21, For example, network elements 106a-c are shown to be configured to transmit usage information to monitor 108a, while network elements 106d-f are shown configured to transmit usage information to monitor 108b;) via the first network, (Nachimuthu Paragraph 84, Note that the metric data may be communicated between the racks 1602 and the pod management controller 1631 via the OOB network; however, the one or more tasks may be communicated to the racks 1602 and particular resources 1605 via a different network, such as an optical fiber network) and wherein the metrics information is obtained via the first network to reduce disruptions over the second network and reduce delays associated with the second device executing jobs (Hassan, Paragraph 14, The disclosed embodiments also provide support for subsequent decisions based on the analysis of this utilization information. Such decisions may include assigning at least some computing tasks to other computing resources instead of the subject computing resource, to at least partially reduce the utilization of the subject computing resource over the medium term. This reduction in utilization may restore the subject computing resource to more effective operation; Paragraph 22, if the intelligent engine determines that network #3 104c is more heavily utilized than network #4 104d, then the intelligent engine may route calls received from one or more of the networks 104a-b over network #4 104d instead of network #3 104c. In some aspects, the determination may be based on the detection of one or more spikes in utilization on the monitored network. In some aspects, an adaptive threshold may be used to determine whether a network is too heavily utilized to support additional traffic; Paragraph 41, For example, disk write requests or other file based operations may be routed to a stable storage device that is less heavily utilized than another stable storage device, reducing latency of write requests and/or file operations and load balancing the stable storage devices in some aspects).
However, Tian in view of Hassan in view of Nachimuthu in view of Kim fails to teach wherein the first network is inaccessible to an operating system of the second device.
In a similar field of endeavor Pai teaches wherein the first network is inaccessible to an operating system of the second device, (Paragraph 16, hardware-based isolation technique is used to isolate untrustworthy network resources from the operating system representing a network between devices with an inaccessible operating system to a device). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the first network is inaccessible to an operating system of the second device as described by Pai with Tian in view of Hassan in view of Nachimuthu in view of Kim because the use of a network that is inaccessible to an operating system of a device will increase the security of the device from malicious attacks that may be conducted on the network.
Regarding claim 25, Tian in view of Hassan in view of Nachimuthu in view of Kim teaches the computer program product of claim 24 (see above). However, Tian in view Hassan in view of Nachimuthu of Kim fails to teach wherein the first network is inaccessible to an operating system of the first device.
In a similar field of endeavor Pai teaches wherein the first network is inaccessible to an operating system of the first device (Paragraph 16, hardware-based isolation technique is used to isolate untrustworthy network resources from the operating system representing a network in which the operating system is inaccessible). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add a network that is inaccessible to an operating system of the first device as described in Pai with Tian in view of Hassan in view of Nachimuthu in view of Kim because the use of a network that is inaccessible to an operating system of a device will increase the security of the device from malicious attacks that may be conducted on the network.
Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (US 2012/0204176) in view of Hassan et al. (US 2019/0327185) in view of Nachimuthu et al. (US 2018/0027063 A1) in view of Kim (US 2014/0373025) further in view of Lee at al. (US 2019/0163540).
Regarding claim 23, Tian in view of Hassan in view of Nachimuthu in view of Kim teaches the computer-implemented method of claim 21, wherein the component includes a processing unit (see above). However, Tian in view of Hassan in view of Nachimuthu in view of Kim fails to teach wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the processing unit, wherein the particular load includes a load of the processing unit, and wherein the method further comprises: determining the load of the processing unit based on the measurement of the power consumption of the processing unit.
In a similar field of endeavor Lee teaches wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the processing unit (Paragraph 18, monitor program ranks the power efficiency consumption of the nodes that make up the data center), wherein the particular load includes a load of the processing unit, and wherein the method further comprises: determining the load of the processing unit based on the measurement of the power consumption of the processing unit (Paragraph 24, Job scheduler uses the power efficiency consumption to determine the dynamic power consumption of each node for the database). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add wherein the measurement of the performance of the component of the second device includes a measurement of a power consumption of the processing unit, wherein the particular load includes a load of the processing unit, and wherein the method further comprises: determining the load of the processing unit based on the measurement of the power consumption of the processing unit as described by Lee with Tian in view of Hassan in view of Nachimuthu in view of Kim because the inclusion of the power consumption in the metrics information allows for increased accuracy when determining the load which is used as a basis for executing a job.
Response to Arguments
Applicant's arguments filed 07/08/2026 have been fully considered but they are not persuasive. Applicant argues in substance:
I. With respect to claim 1, claim 1 stands rejected over Tian et al. in view of Hassan et al.
further in view of Wang. Tian discloses VM allocation using utilization information for physical machines, but Tian does not teach obtaining metrics information by a third device from a controller associated with the second device via the recited first network. Hassan discloses monitors and an intelligent engine for traffic and storage routing, but Hassan likewise does not teach obtaining the claimed metrics information from a controller associated with the second device. Wang discloses out-of-band probing of network paths in an SD-WAN environment, but Wang's synthetic probe packets are not controller-sourced metrics obtained from a monitored device. Accordingly, the combination of Tian, Hassan, and Wang does not teach or suggest amended claim 1.
Claim 8 recites features similar to claim 1. Therefore, the combination of Tian, Hassan, and Wang does not teach or suggest amended claim 8.
With respect to claim 15, claim 15 stands rejected over Tian et al. in view of Hassan et al. in view of Wang in view of Herbert et al. The combination of Tian, Hassan, and Wang does not teach obtaining the recited metrics information from a controller associated with the second device. Herbert likewise does not cure this deficiency. At most, Herbert discloses an internal SoC fabric or bus arrangement for trusted metering and isolated sensors, rather than the presently claimed architecture in which metrics information associated with the second device is obtained from a controller associated with the second device via the recited first network. Accordingly, the combination of Tian, Hassan, Wang, and Herbert does not teach or suggest amended claim 15.
With respect to claim 21, claim 21 stands rejected over Tian et al. in view of Hassan et al. in view of Wang further in view of Kim. Kim may disclose storing measurements and load information in association with one another, but Kim does not teach that the recited metrics information is obtained by a third device from a controller associated with the second device via the recited first network. Nor do Tian, Hassan, or Wang teach this feature. Accordingly, the combination of Tian, Hassan, Wang, and Kim does not teach or suggest amended claim 21.
With respect to claim 24, claim 24 stands rejected over Tian et al. in view of Hassan et al. in view of Wang further in view of Kim. Claim 24 recites features similar to the features of claim 21 above. For at least the reasons presented above with respect to claim 21, the combination of Tian, Hassan, Wang, and Kim does not teach or suggest amended claim 24.
The additional references cited for the additional features recited in claims dependent on claims 1, 8, 15, 21, and 24 do not cure the deficiencies of Tian, Hassan, Wang, Herbert, and Kim.
For at least these reasons, Applicant respectfully requests withdrawal of the rejections of claims 1-25 under 35 U.S.C. 103.
a) Applicant’s arguments with respect to claim(s) 1-25 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Examiner directs Applicant to the detailed mappings in the rejections above.
Conclusion
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.
Examiner respectfully requests, in response to this Office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line number(s) in the specification and/or drawing figure(s). This will assist Examiner in prosecuting the application.
When responding to this Office Action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections. See 37 CFR 1.111(c).
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/A.F.R./Examiner, Art Unit 2197
/BRADLEY A TEETS/Supervisory Patent Examiner, Art Unit 2197
