DETAILED ACTION
This is in response to the application filed on July 18th 2025, in which claims 1-20 are presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 2/2/26 and 7/18/25 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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(s) 1-6, 8-10 and 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over Baldi US 11,005,754 B1 in view of Vankayala et al. US 2022/0394694 A1.
Regarding claim 1, Baldi discloses:
An electronic device comprising: a communication circuit; memory; and at least one processor including processing circuitry (device with processor, memory and network interface – abstract, Figs. 1, 13), wherein the memory stores instructions that, when individually or collectively executed by the at least one processor, cause the electronic device to:
execute an application (data plane program – col. 2 ln. 33-52 and col. 3 ln. 1-2);
receive a plurality of data packets for the application from an external device through the communication circuit (receive packets over network - Fig. 1, col. 2 ln. 60 – col. 3 ln. 22);
determine whether at least one of data throughput information on the external device, state information about a channel transmitting the plurality of data packets, or signal round- trip time information satisfies a specified condition (check condition information for packets and match hook – Figs. 4, 7 and col. 3 ln. 20-40, also see col. 7 ln. 10-25; although Baldi does not explicitly teach “throughout” or “round-trip time”, it contemplates a variety of header metadata – see col. 6 ln. 10-20, this reads on “state information about a channel transmitting the plurality of data packets” under the broadest reasonable interpretation of “state information”);
apply … algorithms to merge and process the plurality of data packets to the plurality of data packets, based on the specified condition being satisfied (when condition is satisfied, execute specific processing that matches hook/key – see col. 3 ln. 23-35 and ln. 63 – col. 4 ln. 3 and Fig. 14 step 1410; regarding the term “merge and process”, this is taught by Baldi as well since it explicitly discloses “merging” instructions and then processing packets – see abstract, col. 2 ln. 33-45 and Fig. 14 step 1420); and
refrain from applying the … algorithms to the plurality of data packets, based on the specified condition not being satisfied (when condition does not match perform a default action – col. 3 ln. 58-62).
Baldi does not explicitly disclose using artificial intelligence but this is taught by Vankayala (group a plurality of data packets based on network parameters using AI – abstract, paragraphs 6, 13, and Fig. 1). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Baldi to use AI as taught by Vankayala for the purpose of dynamically processing packets. Vankayala suggests that using AI improves resource allocation and allows different quality of services to be supported, this dynamic switching enhances user experience (see paragraphs 3-7). Vankayala also teaches the network parameters include throughput and latency, i.e. RTT (see paragraph 53).
Regarding claim 2, Baldi teaches applying a first algorithm and a second algorithm based on conditions of data packets as discussed above. Baldi does not explicitly disclose check a property of the application, applying a first artificial intelligence learning-based algorithm, based on the application having a first property; and applying a second artificial intelligence learning-based algorithm, based on the application having a second property but this is taught by Vankayala as application specific processing for individual quality of service requirements (paragraphs 20-21). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Baldi to use application requirements/properties as taught by Vankayala for the purpose of dynamically processing packets. As discussed above, Vankayala suggests that AI provides optimal bandwidth management and resource allocation allows different quality of services to be supported per application, this dynamic switching enhances user experience (see paragraphs 3-7).
Regarding claim 3, Baldi does not explicitly disclose confirm an application requiring a RTT to be less than or equal to a specified value as the application having the first property. But this is taught by Vankayala as UE applications have quality of service requirements including latency (paragraphs 4, 6, 12) and using AI to process packets based on the network parameters (paragraphs 13, 53). The motivation to combine is the same.
Regarding claim 4, Baldi does not explicitly disclose confirm an application requiring a downlink data rate to be greater than or equal to a specified value as the application having the first property. But this is taught by Vankayala as UE applications have quality of service requirements including downlink bandwidth (paragraphs 3, 6, 35-36, Fig. 6) and using AI to process packets based on the network parameters (paragraphs 13, 53). The motivation to combine is the same.
Regarding claim 5, Baldi discloses check a flag at least partially included in the plurality of data packets and having a specified value related to merging of the data packets, during a specified period (check condition information for packets and match hook – Figs. 4, 7 and col. 3 ln. 20-40, also see col. 7 ln. 10-25; the condition or hook is equivalent to a “flag”; this hook/flag “relates to merging” of the packets because the processing of the packets has been merged – abstract, Fig. 14, col. 2 ln. 25-45; processing instructions can be timestamp dependent, thus they are for “a specified period” – see col. 5 ln. 49-65 and Fig. 3, col. 6 ln. 40-44);
apply, to the data packets, the first algorithm to merge and process at least some of the data packets before receiving a data packet corresponding to the flag having the specified value among the data packets (when condition is satisfied, execute specific processing that matches hook/key – see col. 3 ln. 23-35 and ln. 63 – col. 4 ln. 3 and Fig. 14 step 1410; regarding the term “merge and process”, this is taught by Baldi as well since it explicitly discloses “merging” instructions and then processing packets – see abstract, col. 2 ln. 33-45 and Fig. 14 step 1420; upon receiving a “flag” or new hook, conditions change and thus processing can change); and
apply, to the data packets, the second algorithm to merge and process the received data packets until the specified period ends (use condition to perform packet specific processing as discussed above, this includes multiple algorithms, use timestamp information – col. 5 ln. 49-65, col. 3 ln. 23-44 and Fig. 14).
Baldi does not explicitly performing the actions based on the application having a first property or based on the application having the second property but this is taught by Vankayala as application specific processing for individual quality of service requirements (paragraphs 20-21). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Baldi to use application requirements/properties as taught by Vankayala for the purpose of dynamically processing packets. Vankayala suggests that optimal bandwidth management and resource allocation allows different quality of services to be supported per application, this dynamic switching enhances user experience (see paragraphs 3-7).
Regarding claim 6, Baldi discloses refrain from considering the flag having the specified value and perform an operation of applying the second algorithm to the data packets, (when condition does not match perform a default action – col. 3 ln. 58-62). Baldi does not explicitly disclose considering the application property but this is taught by Vankayala as explained above. The motivation to combine is the same.
Regarding claim 8, Baldi discloses applying the algorithm to the data packets based on the data packets being TCP packets; and refrain from applying the algorithm to the data packets, based on the data packet not being TCP (apply processing action based on protocol type, e.g. UDP, TCP, etc. – see col. 7 ln. 20-50 and Fig. 4). Baldi does not explicitly disclose artificial intelligence but this is taught by Vankayala as discussed above. The motivation to combine is the same.
Regarding claim 9, Baldi discloses:
An electronic device comprising: a communication circuit; memory; and at least one processor including processing circuitry, wherein the memory stores instructions that, when individually or collectively executed by the at least one processor (device with processor, memory and network interface – abstract, Figs. 1, 13), cause the electronic device to:
execute an application (data plane program – col. 2 ln. 33-52 and col. 3 ln. 1-2);
receive a plurality of data packets for the application from an external device through the communication circuit (receive packets over network - Fig. 1, col. 2 ln. 60 – col. 3 ln. 22);
check a flag set in the plurality of data packets and having specified value related to merging of the data packets, during a specified period (check condition information for packets and match hook – Figs. 4, 7 and col. 3 ln. 20-40, also see col. 7 ln. 10-25; the condition or hook is equivalent to a “flag”; this hook/flag “relates to merging” of the packets because the processing of the packets has been merged – abstract, Fig. 14, col. 2 ln. 25-45; processing instructions can be timestamp dependent, thus they are for “a specified period” – see col. 5 ln. 49-65 and Fig. 3, col. 6 ln. 40-44);
apply, to the data packets, a first algorithm to merge and process at least some of the data packets before receiving a data packet corresponding to the flag having the specified value among the data packets (when condition is satisfied, execute specific processing that matches hook/key – see col. 3 ln. 23-35 and ln. 63 – col. 4 ln. 3 and Fig. 14 step 1410; regarding the term “merge and process”, this is taught by Baldi as well since it explicitly discloses “merging” instructions and then processing packets – see abstract, col. 2 ln. 33-45 and Fig. 14 step 1420; upon receiving a “flag” or new hook, conditions change and thus processing can change); and
apply, to the data packets, a second algorithm to merge and process the received data packets until the specified period ends (use condition to perform packet specific processing as discussed above, this includes multiple algorithms, use timestamp information – col. 5 ln. 49-65, col. 3 ln. 23-44 and Fig. 14).
Baldi does not explicitly disclose check a property of the application, based on the application having a first property or based on the application not having the first property but this is taught by Vankayala as application specific processing for individual quality of service requirements (paragraphs 20-21). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Baldi to use application requirements/properties as taught by Vankayala for the purpose of dynamically processing packets. Vankayala suggests that optimal bandwidth management and resource allocation allows different quality of services to be supported per application, this dynamic switching enhances user experience (see paragraphs 3-7). Furthermore, the subject matter of this claim corresponds to the rejection of claim 2 without the artificial intelligence features.
Regarding claim 10, Baldi discloses refrain from considering the flag having the specified value and perform an operation of applying the second algorithm to the data packets, (when condition does not match perform a default action – col. 3 ln. 58-62). Baldi does not explicitly disclose considering the application property but this is taught by Vankayala as explained above. The motivation to combine is the same.
Regarding claim 12, Baldi discloses check … the application based on information related to a channel state with the external device satisfying a specified condition (checking conditions includes “state” information such as protocols used – see col. 3, ln. 20-60, col. 7 ln. 20-42 and Figs. 2-4). Baldi does not explicitly disclose the property of the application but this is taught by Vankayala as explained above.
Regarding claim 13, it appears to correspond to previously presented claim 4, thus it is rejected for the same reasons.
Regarding claim 14, Baldi does not disclose each of the first or second algorithm comprises an artificial intelligence model trained based on at least one of data throughout information about the external device, state information about a channel transmitting the plurality of data packets, or signal round-trip time information. But this is taught by Vankayala as training the AI model based on network parameters including at least throughout and latency (AI model is trained using plurality of network parameters – paragraphs 13, 82, 84; parameters include throughput and latency – paragraph 6). The motivation to combine is the same as that given above in the rejection of claim 1, i.e. using AI to dynamically manage network traffic improves user experience.
Regarding claim 15, Baldi does not explicitly disclose the artificial model is generated by the external device but Vankayala discloses training the AI model as discussed above (see paragraphs 13, 84) and Baldi suggests different devices may perform different functions (Fig. 1). Thus, the combination would result in training/generating the AI by an external device.
Regarding claim 16, the combination of Baldi and Vankayala teaches that applications have different requirements (RTT) and applying processing/algorithms based on the application specific requirements as discussed above. The combination does not explicitly disclose “a list” of applications but this is essentially what Vankayala discloses by using the AI model, when the model determines the service is of a specific type of service (i.e. the application is on a list), then certain processing is invoked (see Figs. 5-6). Likewise, Baldi teaches a table of rules with conditions and invoking key processing when a hook matches, this is similar to the application being on a list, since a table is also a list (see Figs. 3-4 and col. 3 ln. 45-56). Therefore, the combination discloses the recited feature of store a list of applications and applying a second/specific processing/algorithm when the application is included in the list.
Regarding claim 17, as discussed above, the combination of Baldi and Vankayala does not explicitly disclose a list but they disclose the functional equivalent regarding having a set of rules/conditions and then performing a specific action when those rules/conditions are triggered. Furthermore, Baldi teaches causing the device to apply a first algorithm when the application is not included in the list (perform default action when the packet does not match an entry – col. 3 ln. 58-62).
Regarding claim 18, it appears to correspond to previously presented claim 3, thus it is rejected for the same reasons.
Regarding claim 19, it appears to correspond to previously presented claim 4, thus it is rejected for the same reasons.
Regarding claim 20, Baldi discloses the at least one processor includes an application processor and a communication processor (one or more processors – Fig. 13 item 1320 and col. 12 ln. 64 – col. 13 ln. 24). Vankayala also discloses multiple processors including an application processor (paragraph 64).
Claim(s) 7 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Baldi and Vankayala in view of Kubo et al. US 2020/0146548 A1.
Regarding claim 7, the combination of Baldi and Vankayala discloses applying the artificial intelligence algorithm to the data packets as explained above. The combination does not explicitly disclose applying the algorithm based on the application being executed in a foreground; and refrain from applying the algorithm, based on the application being executed in a background. But this is taught by Kubo as adjusting packet processing operations depending on whether the application is active or operating in the background (abstract). Specifically, Kubo teaches changing duty operations relating to packet transmission/reception based on whether the application is operating in a background or operating in a foreground (paragraphs 8, 39). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Baldi and Vankayala in view of Kubo. Kubo teaches that this well-known technique of adjusting operation based on application status being active or standby (i.e. foreground or background) results in reduced power consumption (paragraph 9).
Regarding claim 11, it corresponds to claim 7 and thus is rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tigli US 2020/0169509 A1 discloses using machine learning to classify data flows (abstract, Fig. 1) including grouping packets, training machine learning models and improving traffic engineering (paragraph 55).
Li et al. US 2025/0016108 A1 discloses marking packets and determining QoS for an application (abstract), also using ML (paragraph 105) and considering the throughout and latency requirements of an application (paragraph 54).
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/JASON D RECEK/Primary Examiner, Art Unit 2458
