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 .
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 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.
This action is responsive to the RCE filed on 6/23/26.
Claim(s) 1-3, 5-13, 15-22 is/are presented for examination.
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 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 of this title, 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) 1-2, 5, 7-12, 15, 17-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pennarun, U.S. Patent/Pub. No. US 2019/0199772 A1 and in view of Savalle, U.S. Patent/Pub. No. 2020/0379839 A1.
As to claim 1, Pennarun teaches a method comprising:
receiving, at a device, application performance metrics generated by an online application accessible via a network, the application performance metrics, each of the application performance metrics including at least one of concealment time, bit rate, video resolution, frame rate, or buffer delay (Pennarun, figure 4E, 4F, 6B, 6C, 7; page 5, paragraph 57-59; i.e., [0057] the particular simulation scenario, (ii) commands associated with particular simulated impairments (e.g., one-way latency, round trip latency, jitter, packet loss, TCP retransmission, etc.),);
performing, by the device, a trial-and-error testing process to determine a cause of the degraded state of the online application, the trial-and-error process including:
testing the online application while iteratively applying a plurality of simulated scenarios, each of the simulated scenarios representing a degraded network state, the plurality of simulated scenarios being associated with different combinations of performance parameters, each of the performance parameters including at least one of loss, latency, jitter, bandwidth, or background load (Pennarun, figure 4E, 4F, 6B, 6C, 7; page 5, paragraph 57-59; i.e., [0058] the simulation data includes: (i) scenario data identifying the particular simulation scenario that programmed or selected for the simulation, (iii) test app data identifying the application that had been tested for the simulation, (iv) the encoded output data stream (the output of test app module 244), (v) the impaired output data stream (the output of network simulator 246); [0060] each simulation scenario provides a reproducible sequence of dynamically changing impairments, thereby allowing for repeatable tests and reliable results when comparing different versions of the same test application);
obtaining, for individual ones of the plurality of simulated scenarios, one or more simulation metrics that were produced from the testing (Pennarun, figure 4E, 4F, 6B, 6C, 7; page 5, paragraph 57-59; i.e., [0058] the simulation data includes: (i) scenario data identifying the particular simulation scenario that programmed or selected for the simulation, (iii) test app data identifying the application that had been tested for the simulation, (iv) the encoded output data stream (the output of test app module 244), (v) the impaired output data stream (the output of network simulator 246); [0060] each simulation scenario provides a reproducible sequence of dynamically changing impairments, thereby allowing for repeatable tests and reliable results when comparing different versions of the same test application);
comparing, for individual ones of the plurality of simulated scenarios, the one or more simulation metrics for the individual simulated scenario to the application performance metrics generated by the online application (Pennarun, figure 9; page 7, paragraph 72; i.e., [0072] the test application are determined based on the quality metrics ( e.g., percentage of dropped packets, average/high/low latency and/or bandwidth levels, and so forth). In some implementations, a simulated user experience value is determined and associated with the simulation scenario for the test application (e.g., "User Experience Score" in Summary 624, FIG. 6C). In some implementations, the simulated user experience value is determined by deriving one or more simulated
quality of service (QoS) values from the plurality of quality metrics, and comparing the one or more simulated QoS values with and one or more target QoS values. For example, data stream exhibits a threshold percentage of dropped packets, and the
simulated QoS value (e.g., 70% packet drop rate) is compared to a target QoS value (e.g., 5% packet drop rate)); and
determining, based on the comparison and from among the plurality of simulated scenarios, a particular simulated scenario that is associated with one or more simulation metrics that have a threshold amount of similarity to the application performance metrics generated by the online application (Pennarun, figure 4E, 4F, 6B, 6C, 7; page 5, paragraph 57-59; i.e., [0058] the simulation data includes: (i) scenario data identifying the particular simulation scenario that programmed or selected for the simulation, (iii) test app data identifying the application that had been tested for the simulation, (iv) the encoded output data stream (the output of test app module 244), (v) the impaired output data stream (the output of network simulator 246); [0060] each simulation scenario provides a reproducible sequence of dynamically changing impairments, thereby allowing for repeatable tests and reliable results when comparing different versions of the same test application).
But Pennarun failed to teach the claim limitation wherein indicative of a degraded state of the online application; providing, by the device, an indication of the particular simulated scenario as a cause of the degraded state of the online application.
However, Savalle teaches the claim limitation wherein indicative of a degraded state of the online application (Savalle, page 2, paragraph 22-24; i.e., [0022] [0022] comparison of a measured level of use of a resource available in the measuring repository with the acceptable consumption interval of the level of use for each resource of an application available in a memory of the repository of use, to create an "application
performance degradation" category stored in a memory, when the measured level of use is outside the acceptable consumption interval of the resource); providing, by the device, an indication of the particular simulated scenario as a cause of the degraded state of the online application (Savalle, page 5, paragraph 50; page 10, paragraph 109; i.e., [0109] To test the performance of the backup tunnels(s) post-reroute, device 308 could measure the tunnel health (e.g., loss, latency, jitter) and the SLAB at a high frequency ( e.g., every 500 ms), to observe any SLA changes. In another embodiment, the edge device 308 may initiate Deep-Packet Inspection (DPI) for the application(s) on the tunnel).
It would have been obvious to one of ordinary skill in the art before the effective date of the claimed invention to modify Pennarun to substitute acceptable consumption interval from Savalle for error correction from Pennarun to ensure proper performance and proper respect of the quality of service of applications or servers of an application chain (Savalle, page 1, paragraph 3).
As to claim 2, Pennarun-Savalle teaches the method as recited in claim 1, wherein the performance parameters indicate one or more of: increased loss, increased latency, increased jitter, decreased bandwidth, or background load, imposed on traffic associated with the online application (Pennarun, figure 4E, 4F, 6B, 6C, 7; page 5, paragraph 57-59; i.e., [0057] the particular simulation scenario, (ii) commands associated with particular simulated impairments (e.g., one-way latency, round trip latency, jitter, packet loss, TCP retransmission, etc.),).
As to claim 5, Pennarun-Savalle teaches the method as recited in claim 1, wherein the testing includes instructing one or more agents to apply the plurality of simulated scenarios (Pennarun, figure 4E, 4F, 6B, 6C, 7; page 5, paragraph 57-59; i.e., [0058] the simulation data includes: (i) scenario data identifying the particular simulation scenario that programmed or selected for the simulation, (iii) test app data identifying the application that had been tested for the simulation, (iv) the encoded output data stream (the output of test app module 244), (v) the impaired output data stream (the output of network simulator 246); [0060] each simulation scenario provides a reproducible sequence of dynamically changing impairments, thereby allowing for repeatable tests and reliable results when comparing different versions of the same test application).
As to claim 7, Pennarun-Savalle teaches the method as recited in claim 1, wherein the application performance metrics are associated with a wide area network access technology, and wherein the testing of the online application replicates traffic for the online application sent via that wide area network access technology (Pennarun, figure 4E, 4F, 6B, 6C, 7; page 5, paragraph 57-59; i.e., [0058] the simulation data includes: (i) scenario data identifying the particular simulation scenario that programmed or selected for the simulation, (iii) test app data identifying the application that had been tested for the simulation, (iv) the encoded output data stream (the output of test app module 244), (v) the impaired output data stream (the output of network simulator 246); [0060] each simulation scenario provides a reproducible sequence of dynamically changing impairments, thereby allowing for repeatable tests and reliable results when comparing different versions of the same test application).
As to claim 8, Pennarun-Savalle teaches the method as recited in claim 1, wherein the application performance metrics are associated with an Internet access strategy, and wherein the testing of the online application replicates traffic for the online application sent via using that Internet access strategy (Pennarun, figure 9; page 7, paragraph 72; i.e., [0072] the test application are determined based on the quality metrics ( e.g., percentage of dropped packets, average/high/low latency and/or bandwidth levels, and so forth). In some implementations, a simulated user experience value is determined and associated with the simulation scenario for the test application (e.g., "User Experience Score" in Summary 624, FIG. 6C). In some implementations, the simulated user experience value is determined by deriving one or more simulated quality of service (QoS) values from the plurality of quality metrics, and comparing the one or more simulated QoS values with and one or more target QoS values. For example, data stream exhibits a threshold percentage of dropped packets, and the simulated QoS value (e.g., 70% packet drop rate) is compared to a target QoS value (e.g., 5% packet drop rate)).
As to claim 9, Pennarun-Savalle teaches the method as recited in claim 1, wherein the application performance metrics are associated with poor quality of experience of users of the online application (Pennarun, figure 9; page 7, paragraph 72; i.e., [0072] the test application are determined based on the quality metrics ( e.g., percentage of dropped packets, average/high/low latency and/or bandwidth levels, and so forth). In some implementations, a simulated user experience value is determined and associated with the simulation scenario for the test application (e.g., "User Experience Score" in Summary 624, FIG. 6C). In some implementations, the simulated user experience value is determined by deriving one or more simulated quality of service (QoS) values from the plurality of quality metrics, and comparing the one or more simulated QoS values with and one or more target QoS values. For example, data stream exhibits a threshold percentage of dropped packets, and the simulated QoS value (e.g., 70% packet drop rate) is compared to a target QoS value (e.g., 5% packet drop rate)).
As to claim 10, Pennarun-Savalle teaches the method as recited in claim 1, wherein using clustering on the application performance metrics to identify the degraded state of the online application (Pennarun, figure 9; page 7, paragraph 72; i.e., [0072] the test application are determined based on the quality metrics ( e.g., percentage of dropped packets, average/high/low latency and/or bandwidth levels, and so forth). In some implementations, a simulated user experience value is determined and associated with the simulation scenario for the test application (e.g., "User Experience Score" in Summary 624, FIG. 6C). In some implementations, the simulated user experience value is determined by deriving one or more simulated quality of service (QoS) values from the plurality of quality metrics, and comparing the one or more simulated QoS values with and one or more target QoS values. For example, data stream exhibits a threshold percentage of dropped packets, and the simulated QoS value (e.g., 70% packet drop rate) is compared to a target QoS value (e.g., 5% packet drop rate)).
Claim(s) 11-12, 15, 17-19 is/are directed to a device claims and they do not teach or further define over the limitations recited in claim(s) 1-2, 5, 7-9. Therefore, claim(s) 11-12, 15, 17-19 is/are also rejected for similar reasons set forth in claim(s) 1-2, 5, 7-9.
Claim(s) 20-22 is/are directed to a non-transitory claim and they do not teach or further define over the limitations recited in claim(s) 1-3. Therefore, claim(s) 20-22 is/are also rejected for similar reasons set forth in claim(s) 1-3.
Claim(s) 3, 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pennarun, U.S. Patent/Pub. No. US 2019/0199772 A1 and in view of Savalle, U.S. Patent/Pub. No. 2020/0379839 A1, and further in view of Volkaerts, US 7,433,358 B1.
As to claim 3, Pennarun-Savalle teaches the method as recited in claim 1. But Pennarun-Savalle failed to teach the claim limitation wherein the application performance metrics an audio or video concealment time.
However, Volkaerts teaches the limitation wherein the application performance metrics an audio or video concealment time (Siakou, col 4, lines 55-65; i.e., audio concealment).
It would have been obvious to one of ordinary skill in the art before the effective date of the claimed invention to modify Pennarun-Savalle to substitute VoIP from Volkaerts for low bit rate from Pennarun-Savalle to incrementing time to live (TTL) value such that latencies of each hop can be measured until the destination address is reached (Volkaerts, page 1, paragraph 3).
Claim(s) 13 is/are directed to a device claims and they do not teach or further define over the limitations recited in claim(s) 3. Therefore, claim(s) 13 is/are also rejected for similar reasons set forth in claim(s) 3.
Claim(s) 6 & 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pennarun, U.S. Patent/Pub. No. US 2019/0199772 A1 and in view of Savalle, U.S. Patent/Pub. No. 2020/0379839 A1, and further in view of Virag, U.S. Pub. No. 2024/0313996 A1.
As to claim 6, Pennarun-Savalle teaches the method as recited in claim 1. But Pennarun-Savalle failed to teach the claim limitation wherein the application performance metrics are associated with a location type, and wherein the testing of the online application replicates traffic for the online application from that location type.
However, Virag teaches the limitation wherein the application performance metrics are associated with a location type, and wherein the testing of the online application replicates traffic for the online application from that location type (Virag, page 8, paragraph 73; page 9, paragraph 77-78; page 11, paragraph 81; i.e., [0073] to mirror or duplicate entire packet flows (which correspond to the latency-sensitive application; [0077] mirror the first P data packets of each packet flow associated with the latency-sensitive application, data packets of a particular packet flow of the latency-sensitive application).
It would have been obvious to one of ordinary skill in the art before the effective date of the claimed invention to modify Pennarun-Savalle to substitute low latency and non-low latency traffic from Virag for traffic of the tunnel from Pennarun-Savalle to enable efficient provisioning of packet classifiers for bifurcation of traffic into low-latency traffic and non-low-latency traffic (Virag, page 1, paragraph 8).
Claim(s) 16 is/are directed to a system claim and they do not teach or further define over the limitations recited in claim(s) 6. Therefore, claim(s) 16 is/are also rejected for similar reasons set forth in claim(s) 6.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-3, 5-13, 15-22 has/have been considered but are moot in view of the new ground(s) of rejection. Applicant’s arguments include the failure of previously applied art to expressly disclose “comparing, for individual ones of the plurality of simulated scenarios, the one or more simulation metrics for the individual simulated scenario to the application performance metrics generated by the online application” (see Applicant’s response, 6/23/26, page 11). It is evident from the detailed mappings found in the above rejection(s) that Pennarun disclosed this functionality (see Pennarun, figure 9; page 7, paragraph 72). Further, it is clear from the numerous teachings (previously and currently cited) that the provision for “comparing, for individual ones of the plurality of simulated scenarios, the one or more simulation metrics for the individual simulated scenario to the application performance metrics generated by the online application” was widely implemented in the networking art. Thus, Applicant’s arguments drawn toward distinction of the claimed invention and the prior art teachings on this point are not considered persuasive.
Listing of Relevant Arts
Garnepudi, U.S. Patent/Pub. No. US 20150088697 A1 discloses implementing the test result.
Yadav, U.S. Patent/Pub. No. US 20170344467 A1 discloses software testing, metric function.
Contact Information
The present application is being examined under the pre-AIA first to invent provisions.
THUONG NGUYEN whose telephone number is (571)272-3864. The examiner can normally be reached on Monday-Friday 9:00-6:00.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Noel Beharry can be reached on 571-270-5630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/THUONG NGUYEN/ Primary Examiner, Art Unit 2416
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