CTNF 19/007,364 CTNF 91461 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Double Patenting 08-33 AIA The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg , 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman , 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi , 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum , 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel , 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington , 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA/25, or PTO/AIA/26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. 08-34 AIA Claim s 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim s 1-20 of U.S. Patent No. 12,212,479 B2 . Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-20 of U.S. Patent No. 12,212,479 B2 teaches on each and every limitation of claims 1-20 of the Instant Application . Instant Application US 12,212,479 B2 1. A device comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, the operations comprising: determining a protocol-induced latency based on end-to-end communication path performance information corresponding to testing of end-to-end communication paths between a plurality of user equipment and endpoints via a network, wherein the protocol-induced latency is determined to comprise a first minimum end- to-end communication path latency indicated in the end-to-end communication path performance information; determining a network-distance-based latency, wherein the network-distance-based latency is determined to comprise a second minimum end-to-end communication path latency of a selected group of end-to-end communication paths indicated in a portion of the end-to-end communication path performance information minus the protocol-induced latency, wherein the end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the portion of the end-to-end communication path performance information is specific to a defined market of the plurality of markets of the network; and enabling determining a network response operation based on the network-distance-based latency. 1. A device, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, the operations comprising: receiving end-to-end communication path performance information corresponding to testing of end-to-end communication paths between various pairs of user equipment and endpoints via a network, wherein each pair comprises a respective user equipment and a respective endpoint ; determining a protocol-induced latency based on the end-to-end communication path performance information, corresponding to testing of end-to-end communication paths between various pairs of user equipment and endpoints via a network, wherein the protocol-induced latency is determined to comprise a first minimum end- to-end communication path latency indicated in the end-to-end communication path performance information; determining a network-distance-based latency, wherein the network-distance-based latency is determined to comprise a second minimum end-to-end communication path latency of a selected group of end-to-end communication paths indicated in a portion of the end-to-end communication path performance information minus the protocol-induced latency, wherein the end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the portion of the end-to-end communication path performance information is specific to a defined market of the plurality of markets of the network; and enabling determining a network response operation based on the network-distance-based latency. 2. The device of claim 1, wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. 2. The device of claim 1, wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. 3. The device of claim 1, wherein the end-to-end communication path performance information is received from third-party equipment corresponding to a third-party entity, wherein the third-party equipment does not correspond to a network operator entity, and wherein the third-party equipment is not a user equipment. 3. The device of claim 1, wherein the end-to-end communication path performance information is received from third-party equipment corresponding to a third-party entity, wherein the third-party equipment does not correspond to a network operator entity, and wherein the third-party equipment is not a user equipment. 4. The device of claim 1, wherein the end-to-end communication path performance information comprises a first portion and a second portion, and wherein the first portion is received from third-party equipment corresponding to a third-party entity, and wherein the second portion is received from at least one user equipment. 4. The device of claim 1, wherein the end-to-end communication path performance information comprises a first portion and a second portion, and wherein the first portion is received from third-party equipment corresponding to a third-party entity, and wherein the second portion is received from at least one user equipment. 5. The device of claim 1, wherein the end-to-end communication path performance information is received, directly from at least one user equipment, by network equipment corresponding to a network operator entity. 5. The device of claim 1, wherein the end-to-end communication path performance information is received, directly from at least one user equipment, by network equipment corresponding to a network operator entity. 6. The device of claim 1, wherein the selected group of end-to-end communication paths are selected based on a level of similarity between end-to-end communication paths indicated in the end-to-end communication path performance information. 6. The device of claim 1, wherein the selected group of end-to-end communication paths are selected based on a level of similarity between end-to-end communication paths indicated in the end-to-end communication path performance information. 7. The device of claim 1, wherein an accuracy of the network-distance-based latency increases as a count of end-to-end communication path tests indicated in the end-to-end communication path performance information increases. 7. The device of claim 1, wherein an accuracy of the network-distance-based latency increases as a count of end-to-end communication path tests indicated in the end-to-end communication path performance information increases. 8. The device of claim 1, wherein, based on the network-distance-based latency, the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. 8. The device of claim 1, wherein, based on the network-distance-based latency, the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. 9. The device of claim 1, wherein a network distance information is determined from the network-distance-based latency based on a speed of signal propagation in a corresponding communication path medium. 9. The device of claim 1, wherein a network distance information is determined from the network-distance-based latency based on a speed of signal propagation in a corresponding communication path medium. 10. The device of claim 9, wherein, based on the network distance information determined from the network-distance-based latency, the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. 10. The device of claim 9, wherein, based on the network distance information determined from the network-distance-based latency, the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. 11. A method comprising: determining, by a system comprising a processor, a protocol-induced latency based on crowdsourced end-to-end communication path performance information corresponding to testing of end-to-end communication paths between a plurality of user equipment and endpoints via a network, wherein the protocol-induced latency is determined to comprise a first minimum end-to-end communication path latency indicated in the crowdsourced end-to-end communication path performance information; determining, by the system, a network-distance-based latency, wherein the network-distance-based latency is determined to comprise a second minimum end-to-end communication path latency of a selected group of end-to-end communication paths indicated in a selectable portion of the crowdsourced end-to-end communication path performance information minus the protocol-induced latency, wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is selected based on a defined market of the plurality of markets; and facilitating, by the system, implementing a network response operation based on the network-distance-based latency. 11. A method, comprising: accessing, by a system comprising a processor, crowdsourced end-to-end communication path performance information corresponding to testing of end-to-end communication paths between various pairs of user equipment and endpoints via a network, wherein each pair comprises a respective user equipment and a respective endpoint ; determining, by the system, a protocol-induced latency based on the crowdsourced end-to-end communication path performance information, corresponding to testing of end-to-end communication paths between various pairs of user equipment and endpoints via a network, wherein the protocol-induced latency is determined to comprise a first minimum end-to-end communication path latency indicated in the crowdsourced end-to-end communication path performance information; determining, by the system, a network-distance-based latency, wherein the network-distance-based latency is determined to comprise a second minimum end-to-end communication path latency of a selected group of end-to-end communication paths indicated in a selectable portion of the crowdsourced end-to-end communication path performance information minus the protocol-induced latency, wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is selected based on a defined market of the plurality of markets; and facilitating, by the system, implementing a network response operation based on the network-distance-based latency. 12. The method of claim 11, wherein a portion of the crowdsourced end-to-end communication path performance information is purchased from an entity other than a network entity corresponding to the network. 12. The method of claim 11, wherein a portion of the crowdsourced end-to-end communication path performance information is purchased from an entity other than a network entity corresponding to the network. 13. The method of claim 11, wherein a portion of the crowdsourced end-to-end communication path performance information is generated by an application operating on a first user equipment of the plurality of user equipment, and wherein the application was developed on behalf of a network entity corresponding to the network. 13. The method of claim 11, wherein a portion of the crowdsourced end-to-end communication path performance information is generated by an application operating on a first user equipment of the user equipment, and wherein the application was developed on behalf of a network entity corresponding to the network. 14. A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, the operations comprising: defining a protocol-induced latency as a first minimum end-to-end communication path latency indicated in crowdsourced end-to-end communication path performance information corresponding to testing of end-to-end communication paths between a plurality of user equipment and endpoints of a network; defining a network-distance-based latency, for an end-to-end communication path of the end-to-end communication paths indicated in the crowdsourced end-to-end communication path performance information, as a second minimum end-to-end communication path latency of a selected group of end-to-end communication paths indicated in the crowdsourced end-to-end communication path performance information minus the protocol-induced latency, wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is specific to a defined market of the plurality of markets of the network; and enabling implementation of a network response operation based on the network-distance-based latency. 14. A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, the operations comprising: receiving crowdsourced end-to-end communication path performance information corresponding to testing of end-to-end communication paths between various pairs of user equipment and endpoints of a network, wherein each pair comprises a respective user equipment and a respective endpoint ; defining a protocol-induced latency as a first minimum end-to-end communication path latency indicated in the crowdsourced end-to-end communication path performance information; corresponding to testing of end-to-end communication paths between various pairs of user equipment and endpoints via a network, defining a network-distance-based latency, for an end-to-end communication path of the end-to-end communication paths indicated in the crowdsourced end-to-end communication path performance information, as a second minimum end-to-end communication path latency of a selected group of end-to-end communication paths indicated in the crowdsourced end-to-end communication path performance information minus the protocol-induced latency, wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is specific to a defined market of the plurality of markets of the network; and enabling implementation of a network response operation based on the network-distance-based latency. 15. The non-transitory machine-readable medium of claim 14, wherein a portion of the crowdsourced end-to-end communication path performance information is purchased from a second entity other than a network entity corresponding to the network. 15. The non-transitory machine-readable medium of claim 14, wherein a portion of the crowdsourced end-to-end communication path performance information is purchased from a second entity other than a network entity corresponding to the network. 16. The non-transitory machine-readable medium of claim 14, wherein an accuracy of the network-distance-based latency increases as a count of end-to-end communication path tests indicated in the crowdsourced end-to-end communication path performance information increases. 16. The non-transitory machine-readable medium of claim 14, wherein an accuracy of the network-distance-based latency increases as a count of end-to-end communication path tests indicated in the crowdsourced end-to-end communication path performance information increases. 17. The non-transitory machine-readable medium of claim 15, wherein the second entity is not a user equipment. 17. The non-transitory machine-readable medium of claim 15, wherein the second entity is not a user equipment. 18. The non-transitory machine-readable medium of claim 14, wherein, based on the network-distance-based latency, the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. 18. The non-transitory machine-readable medium of claim 14, wherein, based on the network-distance-based latency, the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. 19. The non-transitory machine-readable medium of claim 14, wherein a portion of the crowdsourced end-to-end communication path performance information is generated by an application operating on a first user equipment of the plurality of user equipment, and wherein the application was developed on behalf of a network entity corresponding to the network. 19. The non-transitory machine-readable medium of claim 14, wherein a portion of the crowdsourced end-to-end communication path performance information is generated by an application operating on a first user equipment of the user equipment, and wherein the application was developed on behalf of a network entity corresponding to the network. 20. The non-transitory machine-readable medium of claim 14, wherein the crowdsourced end-to-end communication path performance information is received, directly from at least one user equipment, by network equipment corresponding to a network operator entity. 20. The non-transitory machine-readable medium of claim 14, wherein the crowdsourced end-to-end communication path performance information is received, directly from at least one user equipment, by network equipment corresponding to a network operator entity . Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 07-21-aia AIA Claim s 1-2, 5-6, 8-11, 13-14, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent 9,602,377 B2 (Agarwal) in view of US PGPub 2020/0403876 Al (Liu) . Regarding Claim 1: Agarwal teaches A device (FIG. 4, operation of the latency service 118 to calculate latency estimations based on input latency factors. The latency service 118 represents any computing device programmed to perform the operations illustrated in FIG. 4. The latency service 118 may represent a web service, network operations center, cloud computing service, server computing device) , comprising: a processor (Fig 5, processor of the Latency Service 118) ; and a memory (Fig 5, memory area 502 of the Latency Service 118) that stores executable instructions that, when executed by the processor, facilitate performance of operations, (Fig 5, The latency service 118 includes one or more computer-readable media such as a memory area 502. The interface component 506, when executed by at least one processor of the latency service 118, causes the processor to receive a request for a latency estimation for sending data from a first computing device to a second computing device) the operations comprising: determining a protocol-induced latency based on end-to-end communication path performance information (ie. observed latency measurement, inherent latency) corresponding to testing of end-to-end communication paths between a plurality of user equipment and endpoints via a network, wherein the protocol-induced latency is determined to comprise a first minimum end-to-end communication path latency (ie. inherent latency) indicated in the end-to-end communication path performance information; (latency(R (p(i), t(j)): observed latency measurement, minimum latency of successive measurements, Table 1, Col 4. The latency service 118 defines a relationship between the signal strength and the corresponding latency measurements for each cell site. A low signal strength, for example, may correspond to an increased latency. In further embodiments, the latency service 118 determines congestion associated with each cell site by analyzing a quantity of computing devices such as computing devices 102 currently connected to each cell site. A high number of devices connected to a cell site may correspond, for example, to an increased latency, Col 7 ln 8-18.) determining a network-distance-based latency, wherein the network-distance-based latency is determined to comprise a second minimum end-to-end communication path latency (ie. minimum latency of successive measurements) of a selected group of end-to-end communication paths indicated in a portion of the end-to-end communication path performance information minus the protocol-induced latency, (ie. latency factors, inherent latency) ( Selected group of communication paths: FIG. 3, a first latency occurs between the mobile computing device 306 and the cell site 304. A second latency occurs between the cell site 304 and an access point 302. A third latency occurs between the access point 302 identified by the access point 302 and the destination computing device 104, Col 6 ln 1-19. latency(R (p(i), t(j)): observed latency measurement, minimum latency of successive measurements, Table 1, Col 4. The measurement filter component 508 (of the latency service 118) accesses relationships derived from the latency factors and latency measurements aggregated from a plurality of computing devices 102. … The calculated latency estimation may include a sum of a first latency value from the first computing device to a cell site identified by the cell site identifier, a second latency value from the cell site to an access point identified by the APN 612, and a third latency value from the access point to the second computing device, Col 9-10 ln 56-67, 1-6. The minimum latency measurement observed in the aggregated latency records 504 involving the cell site, APN 612, and signal strength specified in the request represents the inherent latency between the first computing device and the APN 612. The first latency value is then subtracted from the determined latency between the first computing device and the access point to obtain the second latency value, Col 10 ln 23-41) wherein the end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the portion of the end-to-end communication path performance information is specific to a defined market of the plurality of markets of the network; and enabling determining a network response operation based on the network-distance-based latency. (At 410, the latency service 118 provides the calculated latency estimation to the first computing device. The first 10 computing device may adjust performance of operations of execution of the applications executing on the first computing device based on the calculated latency estimation. For example, some operations may be postponed, or execution of some applications may be suspended, if the latency estimation exceeds a pre-defined threshold, Col 8 ln 8-15) Agarwal teaches wherein the selected group of communication paths is selected based on a defined market (ie. particular cell/topology site, APN 612) of the network Col 10 ln 23-40. However, Agarwal is silent on wherein the end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the portion of the end-to-end communication path performance information is specific to a defined market of the plurality of markets of the network. Liu teaches, in the same field of endeavor, a device in which a processing system enables mobile devices on a communication network to perform latency tests to obtain first latency test data, Abstract. Liu also teaches wherein the end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the portion of the end-to-end communication path performance information is specific to a defined market of the plurality of markets of the network. ([0028] In various embodiments, latency data is crowdsourced from a large number of UEs in a mobile network, and analyzed to map the topology of the network. Based on the network topology map, latency can then be estimated for other UEs sharing the same network topology. [0033] A machine learning clustering method can be used to aggregate IP locations into clusters; a cluster location is calculated by the lowest latency tests associated with the IP addresses in that cluster. In this embodiment, a cluster location is considered to be a network edge location. [0042] The system can then convert the edge server/data center latencies to distances, and thus derive the network topology including data center locations and network edge server locations (step 2618)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal per Liu to include wherein the end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the portion of the end-to-end communication path performance information is specific to a defined market of the plurality of markets of the network. This would be advantageous as discussed above, as it would allow the modified system to provide a more comprehensive understanding of network latencies across different locales/markets by inclusion of data relating to different/additional markets (ie. network topologies, cells) and aid in troubleshooting. Regarding Claim 11: Agarwal teaches A method, comprising: determining, by a system comprising a processor, a protocol-induced latency based on crowdsourced end-to-end communication path performance information (ie. observed latency measurement, inherent latency) corresponding to testing of end-to-end communication paths between a plurality of user equipment and endpoints via a network, wherein the protocol-induced latency is determined to comprise a first minimum end-to-end communication path latency (ie. inherent latency) indicated in the crowdsourced end-to-end communication path performance information; (latency(R (p(i), t(j)): observed latency measurement, minimum latency of successive measurements, Table 1, Col 4. The latency service 118 defines a relationship between the signal strength and the corresponding latency measurements for each cell site. A low signal strength, for example, may correspond to an increased latency. In further embodiments, the latency service 118 determines congestion associated with each cell site by analyzing a quantity of computing devices such as computing devices 102 currently connected to each cell site. A high number of devices connected to a cell site may correspond, for example, to an increased latency, Col 7 ln 8-18) determining, by the system, a network-distance-based latency, wherein the network-distance-based latency is determined to comprise a second minimum end-to-end communication path latency (ie. minimum latency of successive measurements) of a selected group of end-to-end communication paths indicated in a selectable portion of the crowdsourced end-to-end communication path performance information minus the protocol-induced latency (ie. latency factors, inherent latency) , ( Selected group of communication paths: FIG. 3, a first latency occurs between the mobile computing device 306 and the cell site 304. A second latency occurs between the cell site 304 and an access point 302. A third latency occurs between the access point 302 identified by the access point 302 and the destination computing device 104, Col 6 ln 1-19. latency(R (p(i), t(j)): observed latency measurement, minimum latency of successive measurements, Table 1, Col 4. The measurement filter component 508 (of the latency service 118) accesses relationships derived from the latency factors and latency measurements aggregated from a plurality of computing devices 102. The estimator component 510 (of the latency service 118) calculates the latency estimation based on the relationships accessed by the measurement filter and the latency factors of the first computing device received by the interface component 506, Col 9-10 ln 56-67, 1-6. The minimum latency measurement observed in the aggregated latency records 504 involving the cell site, APN 612, and signal strength specified in the request represents the inherent latency between the first computing device and the APN 612. The first latency value is then subtracted from the determined latency between the first computing device and the access point to obtain the second latency value, Col 10 ln 23-41) wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is selected based on a defined market of the plurality of markets; and facilitating, by the system, implementing a network response operation based on the network-distance-based latency. (At 410, the latency service 118 provides the calculated latency estimation to the first computing device. The first 10 computing device may adjust performance of operations of execution of the applications executing on the first computing device based on the calculated latency estimation. Some operations may be postponed, or execution of some applications may be suspended, if the latency estimation exceeds a pre-defined threshold, Col 8 ln 8-15) Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal is silent on wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is selected based on a defined market of the plurality of markets. Liu teaches wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is selected based on a defined market of the plurality of markets. ([0028] In various embodiments, latency data is crowdsourced from a large number of UEs in a mobile network, and analyzed to map the topology of the network. Based on the network topology map, latency can then be estimated for other UEs sharing the same network topology. [0033] A machine learning clustering method can be used to aggregate IP locations into clusters; a cluster location is calculated by the lowest latency tests associated with the IP addresses in that cluster. In this embodiment, a cluster location is considered to be a network edge location. [0042] The system can then convert the edge server/data center latencies to distances, and thus derive the network topology including data center locations and network edge server locations (step 2618)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal per Liu to include wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is selected based on a defined market of the plurality of markets. This would be advantageous as discussed above, as it would allow the combined system to provide further accuracy for determining latency by utilizing crowdsourced (real usage) data along with other received performance network metrics. Further, it would be advantageous to include defining locales/markets of the network for analysis as it would allow the modified system to provide a more comprehensive understanding of network latencies across different locales/markets for aid in troubleshooting. Regarding Claim 14: Agarwal teaches A non-transitory machine-readable medium (Fig 5, memory area 502 of Latency Service 118) , comprising executable instructions that, when executed by a processor (Fig 5, processor of the Latency Service 118) , (Fig 5, The latency service 118 includes one or more computer-readable media such as a memory area 502. The interface component 506, when executed by at least one processor of the latency service 118, causes the processor to receive a request for a latency estimation for sending data from a first computing device to a second computing device) facilitate performance of operations, the operations comprising: defining a protocol-induced latency as a first minimum end-to-end communication path latency (ie. observed latency measurement/inherent latency) indicated in crowdsourced end-to-end communication path performance information corresponding to testing of end-to-end communication paths between a plurality of user equipment and endpoints of a network; (latency(R (p(i), t(j)): observed latency measurement, minimum latency of successive measurements, Table 1, Col 4. The signal strength, signal-to-noise ratio, error rate, and or stability of the connection represents the strength of the connection between the computing device 102 and the cell site. The APN 612 identifies a particular network 105 used by the computing device 102 during the latency measurement, Col 3 ln 61-66) defining a network-distance-based latency (ie. calculated latency value) , for an end-to-end communication path of the end-to-end communication paths indicated in the crowdsourced end-to-end communication path performance information (ie. first, second and third latencies) , as a second minimum end-to-end communication path latency (ie. minimum latency of successive measurements) of a selected group of end-to-end communication paths indicated in the crowdsourced end-to-end communication path performance information (ie. minimum latency) , minus the protocol-induced latency (ie. latency factors, inherent latency) , (The measurement filter component 508 of the latency service 118 accesses relationships derived from the latency factors and latency measurements aggregated from a plurality of computing devices 102. The calculated latency estimation may include a sum of a first latency value from the first computing device to a cell site identified by the cell site identifier, a second latency value from the cell site to an access point identified by the APN 612, and a third latency value from the access point to the second computing device, Col 9-10 ln 56-67, 1-6. The minimum latency measurement observed in the aggregated latency records 504 involving the cell site, APN 612, and signal strength specified in the request represents the inherent latency between the first computing device and the APN 612. The first latency value is then subtracted from the determined latency between the first computing device and the access point to obtain the second latency value, Col 10 ln 23-41) wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to- end communication paths is specific to a defined market of the plurality of markets of the network; and enabling implementation of a network response operation based on the network-distance-based latency. (At 410, the latency service 118 provides the calculated latency estimation to the first computing device. The first 10 computing device may adjust performance of operations of execution of the applications executing on the first computing device based on the calculated latency estimation. For example, some operations may be postponed, or execution of some applications may be suspended, if the latency estimation exceeds a pre-defined threshold, Col 8 ln 8-15) Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal is silent on wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is specific to a defined market of the plurality of markets of the network. Liu teaches wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is specific to a defined market of the plurality of markets of the network. ([0028] In various embodiments, latency data is crowdsourced from a large number of UEs in a mobile network, and analyzed to map the topology of the network. Based on the network topology map, latency can then be estimated for other UEs sharing the same network topology. [0033] A machine learning clustering method can be used to aggregate IP locations into clusters; a cluster location is calculated by the lowest latency tests associated with the IP addresses in that cluster. In this embodiment, a cluster location is considered to be a network edge location. [0042] The system can then convert the edge server/data center latencies to distances, and thus derive the network topology including data center locations and network edge server locations (step 2618)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal per Liu to include wherein the crowdsourced end-to-end communication path performance information is associated with a plurality of markets of the network, and wherein the selected group of end-to-end communication paths is specific to a defined market of the plurality of markets of the network. This would be advantageous as discussed above, as it would allow the combined system to provide further accuracy for determining latency by utilizing crowdsourced (real usage) data along with other received performance network metrics. Further, it would be advantageous to include defining locales/markets of the network for analysis as it would allow the modified system to provide a more comprehensive understanding of network latencies across different locales/markets for aid in troubleshooting. Regarding Claim 2: Agarwal (as modified by Liu) teaches on the invention of Claim 1 as described. Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal is silent on wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. Liu teaches wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. ([0028] In various embodiments, latency data is crowdsourced from a large number of UEs in a mobile network, and analyzed to map the topology of the network. Based on the network topology map, latency can then be estimated for other UEs sharing the same network topology. [0033] A machine learning clustering method can be used to aggregate IP locations into clusters; a cluster location is calculated by the lowest latency tests associated with the IP addresses in that cluster. In this embodiment, a cluster location is considered to be a network edge location. [0042] The system can then convert the edge server/data center latencies to distances, and thus derive the network topology including data center locations and network edge server locations (step 2618)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal per Liu to include wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. This would be advantageous as discussed above, as it would allow the modified system to provide further accuracy for determining latency by utilizing crowdsourced (real usage) data along with other received performance network metrics. Regarding Claim 5: Agarwal (as modified by Liu) teaches on the inventions of Claim 1 as described. Agarwal teaches wherein the end-to-end communication path performance information (ie. latency records, latency measurements) is received, directly from at least one user equipment, by network equipment corresponding to a network operator entity. (FIG. 2, The computing device 102 to create latency records 112 and provide the latency records 112 to the latency service 118. At 204, one of the computing devices 102 measures a latency of data transmitted from the computing device 102 to one of the destination computing devices 104. One or more of the applications 110 executed by the computing device 102 each performs latency measurements. In another example, an operating system associated with the computing device 102 performs the latency measurement. The computing device 102 may measure the latency while connected to other computing devices by, for example, performing operations to periodically send and receive test packets during the connection, Col 4-5 ln 62-67, 1-9. The estimator component 510 (of the latency service 118) calculates the latency estimation based on the relationships accessed by the measurement filter and the latency factors of the first computing device received by the interface component 506, Col 9-10 ln 56-67, 1-6.) Regarding Claim 6: Agarwal (as modified by Liu) teaches on the invention of Claim 1 as described. Agarwal teaches wherein the selected group of communication paths are selected based on a level of similarity between communication paths (ie. share same access point) indicated in the end-to-end communication path performance information. (A second latency occurs between the cell site 304 and an access point 302. The second latency may be dependent at least on a mobile operator network 602 associated with the access point 302, and congestion of the mobile operator network 602. The second latency is common to mobile computing devices 306 connected to the cell site 304 and using the same access point 302. A third latency occurs between the access point 302 identified by the access point 302 and the destination computing device 104, Col 6 ln 10-19) Regarding Claim 8: Agarwal (as modified by Liu) teaches on the invention of Claim 1 as described. Agarwal teaches wherein, based on the network-distance-based latency (ie. cell site latency) , the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. (Fig 4, At 410, the latency service 118 provides the calculated latency estimation to the first computing device which may adjust performance of operations of execution of the applications executing on the first computing device based on the calculated latency estimation. Some operations may be postponed, or execution of some applications may be suspended, if the latency estimation exceeds a pre-defined threshold, Col 8 ln 8-15. The latency estimation determines that the different cell site will increase or decrease the latency estimation, and provides that expected adjustment to the first computing device. which is then able to intelligently adjust execution of applications based on the current latency estimation and the expected adjustment. For example, the first computing device may decide to stay connected to the cell site until the latency is expected to decrease, or may decide to switch to another cell site immediately, Col 8 ln 41-50) Regarding Claim 9: Agarwal (as modified by Liu) teaches on the invention of Claim 1 as described. Agarwal teaches wherein a network distance information (ie. cell site congestion) is determined from the network-distance-based latency (ie. cell site latency, calculated latency) based on a speed of signal propagation in a corresponding communication path medium. (The latency service 118 defines a relationship between the signal strength and the corresponding latency measurements for each cell site. A low signal strength, for example, may correspond to an increased latency. In further embodiments, the latency service 118 determines congestion (e.g., utilization) associated with each cell site by analyzing a quantity of computing devices such as computing devices 102 currently connected to each cell site. A high number of devices connected to a cell site may correspond, for example, to an increased latency, Col 7 ln 8-18) Regarding Claim 10: Agarwal (as modified by Liu) teaches on the invention of Claim 9 as described. Agarwal teaches wherein, based on the network distance information (ie. cell site congestion) determined from the network-distance-based latency (ie. cell site latency, calculated latency) , the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. (The latency service 118 defines a relationship between the signal strength and the corresponding latency measurements for each cell site. The latency service 118 determines congestion associated with each cell site, Col 7 ln 8-18. Fig 4, At 410, the latency service 118 provides the calculated latency estimation to the first computing device which may adjust performance of operations of execution of the applications executing on the first computing device based on the calculated latency estimation. Some operations may be postponed, or execution of some applications may be suspended, if the latency estimation exceeds a pre-defined threshold, Col 8 ln 8-15. The latency estimation determines that the different cell site will increase or decrease the latency estimation, and provides that expected adjustment to the first computing device. which is then able to intelligently adjust execution of applications based on the current latency estimation and the expected adjustment. The first computing device may decide to stay connected to the cell site until the latency is expected to decrease, or may decide to switch to another cell site immediately, Col 8 ln 41-50) Regarding Claims 13, 19: Agarwal (as modified by Liu) teaches on the inventions of Claims 11, 14 as described. Agarwal teaches wherein a portion of the end-to-end communication path performance information is generated by an application (ie. application 110, operating system) operating on an endpoint of the endpoints (ie. each computing device 102) , and wherein the application was developed on behalf of a network entity (ie. computing device 102) corresponding to the network. (FIG. 2, The computing device 102 to create latency records 112 and provide the latency records 112 to the latency service 118. At 204, one of the computing devices 102 measures a latency of data transmitted from the computing device 102 to one of the destination computing devices 104. One or more of the applications 110 executed by the computing device 102 each performs latency measurements. In another example, an operating system associated with the computing device 102 performs the latency measurement. The computing device 102 may measure the latency while connected to other computing devices by performing operations to periodically send and receive test packets during the connection, Col 4-5 ln 62-67, 1-9) Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal is silent on wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. Liu teaches wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. ([0028] In various embodiments, latency data is crowdsourced from a large number of UEs in a mobile network, and analyzed to map the topology of the network. Based on the network topology map, latency can then be estimated for other UEs sharing the same network topology. [0033] A machine learning clustering method can be used to aggregate IP locations into clusters; a cluster location is calculated by the lowest latency tests associated with the IP addresses in that cluster. In this embodiment, a cluster location is considered to be a network edge location. [0042] The system can then convert the edge server/data center latencies to distances, and thus derive the network topology including data center locations and network edge server locations (step 2618)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal per Liu to include wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. This would be advantageous as discussed above, as it would allow the modified system to provide further accuracy for determining latency by utilizing crowdsourced (real usage) data along with other received performance network metrics. Regarding Claim 18: Agarwal (as modified by Liu) teaches on the invention of Claim 14 as described. Agarwal teaches wherein, based on the network-distance-based latency (ie. cell site latency) , the network response operation comprises at least one of: a network topology adaptation operation, a traffic steering operation, or a repair operation. (Fig 4, At 410, the latency service 118 provides the calculated latency estimation to the first computing device which may adjust performance of operations of execution of the applications executing on the first computing device based on the calculated latency estimation. Some operations may be postponed, or execution of some applications may be suspended, if the latency estimation exceeds a pre-defined threshold, Col 8 ln 8-15. The latency estimation determines that the different cell site will increase or decrease the latency estimation, and provides that expected adjustment to the first computing device. which is then able to intelligently adjust execution of applications based on the current latency estimation and the expected adjustment. For example, the first computing device may decide to stay connected to the cell site until the latency is expected to decrease, or may decide to switch to another cell site immediately, Col 8 ln 41-50) Regarding Claim 20: Agarwal (as modified by Liu) teaches on the inventions of Claim 1 as described. Agarwal teaches wherein the end-to-end communication path performance information (ie. latency records, latency measurements) is received, directly from at least one user equipment, by network equipment corresponding to a network operator entity. (FIG. 2, The computing device 102 to create latency records 112 and provide the latency records 112 to the latency service 118. At 204, one of the computing devices 102 measures a latency of data transmitted from the computing device 102 to one of the destination computing devices 104. One or more of the applications 110 executed by the computing device 102 each performs latency measurements. In another example, an operating system associated with the computing device 102 performs the latency measurement. The computing device 102 may measure the latency while connected to other computing devices by, for example, performing operations to periodically send and receive test packets during the connection, Col 4-5 ln 62-67, 1-9. The estimator component 510 (of the latency service 118) calculates the latency estimation based on the relationships accessed by the measurement filter and the latency factors of the first computing device received by the interface component 506, Col 9-10 ln 56-67, 1-6.) Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal is silent on wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. Liu teaches wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. ([0028] In various embodiments, latency data is crowdsourced from a large number of UEs in a mobile network, and analyzed to map the topology of the network. Based on the network topology map, latency can then be estimated for other UEs sharing the same network topology. [0033] A machine learning clustering method can be used to aggregate IP locations into clusters; a cluster location is calculated by the lowest latency tests associated with the IP addresses in that cluster. In this embodiment, a cluster location is considered to be a network edge location. [0042] The system can then convert the edge server/data center latencies to distances, and thus derive the network topology including data center locations and network edge server locations (step 2618)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal per Liu to include wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. This would be advantageous as discussed above, as it would allow the modified system to provide further accuracy for determining latency by utilizing crowdsourced (real usage) data along with other received performance network metrics . 07-21-aia AIA Claim s 3-4 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent 9,602,377 B2 (Agarwal) in view of US PGPub 2020/0403876 Al (Liu) more in view of US Patent 11,516,100 B1 (Zheng) . Regarding Claim 3: Agarwal (as modified by Liu) teaches on the invention of Claim 1 as described. Agarwal teaches on end-to-end communication path performance information. (The minimum latency measurement observed in the aggregated latency records 504 involving the cell site, APN 612, and signal strength specified in the request represents the inherent latency between the first computing device and the APN 612. The first latency value is then subtracted from the determined latency between the first computing device and the access point to obtain the second latency value, Col 10 ln 23-42) Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal (as modified by Liu) is silent on wherein the end-to-end communication path performance information is received from third-party equipment corresponding to a third-party entity, wherein the third-party equipment does not correspond to a network operator entity, and wherein the third-party equipment is not a user equipment . Zheng teaches, in the same field of endeavor, a method for integrating telecommunication network provider performance analytics with vendor testing automation such that specific data from vendor user equipment (UE) testing can be filtered out, Abstract. Zheng also teaches wherein the end-to-end communication path performance information is received from third-party equipment corresponding to a third-party entity, wherein the third-party equipment does not correspond to a network operator entity, (The analyzer component 116 of the network device 112 may measure quality key-performance-indicators (KPIs) to understand pre-launch technology and service experience to make go-no-go decisions. KPIs may include, but are not limited to, call drops, network access failures, data throughput, latency, voice quality, etc. The measured data ( e.g., KPIs) may be collected from test UEs, such as the UE 102, provided to users by a network provider associated with the network device 112, as well as vendor UEs, Col 4 ln 51-59) and wherein the third-party equipment is not a user equipment (ie. vendor with vendor device w analyzer component) . (The vendors may be associated with a vendor device 120 having an analyzer component 122 that may be running tests on their own UEs, such as UE 118, and/or be developing variations on software that report a same version number to the network device 112 as those UEs, such as UE 102, provided to users by the network provider. The vendor tests are often stress tests (e.g., intensive drive tests) that measure upper-bound limits of the UE 118 capabilities, Col 4-5 ln 61-67, 1-2) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal (as modified by Liu) by modifying Agarwal per Zheng to include wherein the end-to-end communication path performance information is received from third-party equipment corresponding to a third-party entity, wherein the third-party equipment does not correspond to a network operator entity, and wherein the third-party equipment is not a user equipment. This would be advantageous as discussed above, as it would allow the combined system to provide further accuracy in the latency determination, by utilizing third-party information, ie. stress tests that measure upper-bound limits of the UE 118 capabilities, see Zheng, Col 4-5 ln 61-67, 1-2. Regarding Claim 4: Agarwal (as modified by Liu) teaches on the invention of Claim 1 as described. Agarwal teaches on a portion of the end-to-end communication path performance information. (The minimum latency measurement observed in the aggregated latency records 504 involving the cell site, APN 612, and signal strength specified in the request represents the inherent latency between the first computing device and the APN 612. The first latency value is then subtracted from the determined latency between the first computing device and the access point to obtain the second latency value, Col 10 ln 23-42) Agarwal teaches on receiving end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal (as modified by Liu) is silent on wherein the end-to-end communication path performance information comprises a first portion and a second portion, and wherein the first portion is received from third-party equipment corresponding to a third-party entity, and wherein the second portion is received from at least one user equipment. Zheng teaches wherein the end-to-end communication path performance information comprises a first portion and a second portion, and wherein the first portion is received from third-party equipment corresponding to a third-party entity (ie. vendor measured data) , and wherein the second portion is received from at least one user equipment (ie. UE measured data from the network provider) . (The analyzer component 116 of the network device 112 may measure quality key-performance-indicators (KPIs) to understand pre-launch technology and service experience to make go-no-go decisions. KPIs may include, 55 but are not limited to, call drops, network access failures, data throughput, latency, voice quality, etc. The measured data ( e.g., KPIs) may be collected from test UEs, such as the UE 102, provided to users by a network provider associated with the network device 112, as well as vendor UEs, Col 4 ln 51-59) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal (as modified by Liu) by modifying Agarwal per Zheng to include wherein the end-to-end communication path performance information comprises a first portion and a second portion, and wherein the first portion is received from third-party equipment corresponding to a third-party entity, and wherein the second portion is received from at least one user equipment. This would be advantageous as discussed above, as it would allow the combined system to provide further accuracy in the latency determination, by utilizing third-party information (ie. stress tests of the UEs) along with the end-to-end performance data of the UEs to provide a complete and accurate picture of the network latency . 07-21-aia AIA Claim s 7, 16 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent 9,602,377 B2 (Agarwal) in view of US PGPub 2020/0403876 Al (Liu) more in view of US PGPub 20210203606 A1 (Burroughs) . Regarding Claim 7: Agarwal (as modified by Liu) teaches on the invention of Claim 1 as described. Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal (as modified by Liu) is silent on wherein an accuracy of the network-distance-based latency increases as a count of communication path tests indicated in the end-to-end communication path performance information increases. Burroughs teaches, in the same field of endeavor, a process for managing network congestion uses crowdsourced real-time information about current conditions in a network, Abstract. Burroughs also teaches wherein an accuracy of the network-distance-based latency increases as a count of communication path tests indicated in the end-to-end communication path performance information increases. ([0056] In an embodiment, the target throughput is estimated for an initial congestion window by using sampled data from the network, combining crowd sourced data for a specific cell (ECI), and learning what the actual fair share throughput is for each user. The accuracy of this estimate is driven by the number of available data samples, which data samples comes from active user sessions. The more users, the more sessions, and the more accurate the estimate) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal (as modified by Liu) by modifying Agarwal per Burroughs to include wherein an accuracy of the network-distance-based latency increases as a count of communication path tests indicated in the end-to-end communication path performance information increases. This would be advantageous as discussed above, as it would allow the combined system to provide higher accuracy results in determining latency by running multiple tests over the network which allows for gathering a wide variety of metrics to use in the latency calculation. Regarding Claim 16: Agarwal (as modified by Liu) teaches on the invention of Claim 18 as described. Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal is silent on wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. Liu teaches wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. ([0028] In various embodiments, latency data is crowdsourced from a large number of UEs in a mobile network, and analyzed to map the topology of the network. Based on the network topology map, latency can then be estimated for other UEs sharing the same network topology. [0033] A machine learning clustering method can be used to aggregate IP locations into clusters; a cluster location is calculated by the lowest latency tests associated with the IP addresses in that cluster. In this embodiment, a cluster location is considered to be a network edge location. [0042] The system can then convert the edge server/data center latencies to distances, and thus derive the network topology including data center locations and network edge server locations (step 2618)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal per Liu to include wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. This would be advantageous as discussed above, as it would allow the modified system to provide further accuracy for determining latency by utilizing crowdsourced (real usage) data along with other received performance network metrics. Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal (as modified by Liu) is silent on wherein an accuracy of the network-distance-based latency increases as a count of communication path tests indicated in the end-to-end communication path performance information increases. Burroughs teaches wherein an accuracy of the network-distance-based latency increases as a count of communication path tests indicated in the end-to-end communication path performance information increases. ([0056] In an embodiment, the target throughput is estimated for an initial congestion window by using sampled data from the network, combining crowd sourced data for a specific cell (ECI), and learning what the actual fair share throughput is for each user. The accuracy of this estimate is driven by the number of available data samples, which data samples comes from active user sessions. The more users, the more sessions, and the more accurate the estimate) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal (as modified by Liu) by modifying Agarwal per Burroughs to include wherein an accuracy of the network-distance-based latency increases as a count of communication path tests indicated in the end-to-end communication path performance information increases. This would be advantageous as discussed above, as it would allow the combined system to provide higher accuracy results in determining latency by running multiple tests over the network which allows for gathering a wide variety of metrics to use in the latency calculation . 07-21-aia AIA Claim s 12, 15 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent 9,602,377 B2 (Agarwal) in view of US PGPub 2020/0403876 Al (Liu) further in view of US PGPub 2007/0027974 A1 (Lee) . Regarding Claims 12, 15: Agarwal (as modified by Liu) teaches on the inventions of Claims 13, 18 as described. Agarwal teaches wherein a portion of the end-to-end communication path performance information is received from an entity other than a network entity corresponding to the network. (In some embodiments, a set of third latency values is maintained by a third-party service. In such embodiments, the estimator component 510 accesses the third-party service to retrieve the third latency value for the particular set of latency factor values from the received request. The third-party service may include, for example, a network coordinate system that builds virtual coordinates of Internet nodes or elements to predict latencies between the nodes, Col 10 ln 40-48) Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal is silent on wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. Liu teaches wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. ([0028] In various embodiments, latency data is crowdsourced from a large number of UEs in a mobile network, and analyzed to map the topology of the network. Based on the network topology map, latency can then be estimated for other UEs sharing the same network topology. [0033] A machine learning clustering method can be used to aggregate IP locations into clusters; a cluster location is calculated by the lowest latency tests associated with the IP addresses in that cluster. In this embodiment, a cluster location is considered to be a network edge location. [0042] The system can then convert the edge server/data center latencies to distances, and thus derive the network topology including data center locations and network edge server locations (step 2618)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal per Liu to include wherein the end-to-end communication path performance information is crowdsourced end-to-end communication path performance information. This would be advantageous as discussed above, as it would allow the modified system to provide further accuracy for determining latency by utilizing crowdsourced (real usage) data along with other received performance network metrics. Agarwal teaches receiving end-to-end communication path performance information from a third party service ( Col 10 ln 40-48 ). However, Agarwal (as modified by Liu) is silent on wherein a portion of the crowdsourced end-to-end communication path performance information is purchased from an entity other than a network entity corresponding to the network. Lee teaches, in the same field of endeavor, A status notification method and facility is provided for use with a service chain processing a request for a service, Abstract. Lee also teaches wherein a portion of the end-to-end communication path performance information is purchased from an entity other than a network entity corresponding to the network. ( [0004] To better approximate the end-user perspective, online service providers can also collect exception data from end-user software, or purchase end-user statistics gathered by third party vendors. [0035] failure alerts and/or logging can be generated for implicit failures (e.g., network failures, non-responsive nodes), explicit failures (e.g., application errors), and performance metrics (e.g., end-to-end and individual node latencies)) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal (as modified by Liu) by modifying Agarwal per Lee to include wherein a portion of the end-to-end communication path performance information is purchased from an entity other than a network entity corresponding to the network. This would be advantageous as discussed above, as it would allow the combined system to provide further accuracy in the latency determination, by purchasing third-party metrics (ie. statistics on UE performance) to utilize in the latency calculations along with network data and end-to-end performance measurements, allowing for a complete network latency assessment . 07-21-aia AIA Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over US Patent 9,602,377 B2 (Agarwal) in view of US PGPub 2020/0403876 Al (Liu) further in view of US PGPub 2007/0027974 A1 (Lee) . Regarding Claim 17: Agarwal (as modified by Liu & Lee) teaches on the invention of Claim 15 as described. Agarwal teaches on end-to-end communication path performance information. (The minimum latency measurement observed in the aggregated latency records 504 involving the cell site, APN 612, and signal strength specified in the request represents the inherent latency between the first computing device and the APN 612. The first latency value is then subtracted from the determined latency between the first computing device and the access point to obtain the second latency value, Col 10 ln 23-42) Agarwal teaches on end-to-end communication path performance information (Col 10 ln 23-42). However, Agarwal (as modified by Liu & Lee) is silent on wherein the second entity is not a user equipment. Zheng teaches wherein the second entity is not a user equipment (ie. vendor with vendor device w analyzer component) . (The vendors may be associated with a vendor device 120 having an analyzer component 122 that may be running tests on their own UEs, such as UE 118, and/or be developing variations on software that report a same version number to the network device 112 as those UEs, such as UE 102, provided to users by the network provider. The vendor tests are often stress tests (e.g., intensive drive tests) that measure upper-bound limits of the UE 118 capabilities, Col 4-5 ln 61-67, 1-2) It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Agarwal (as modified by Liu & Lee) by modifying Agarwal per Zheng to include wherein the second entity is not a user equipment. This would be advantageous as discussed above, as it would allow the combined system to provide further accuracy in the latency determination, by utilizing third-party information, ie. stress tests that measure upper-bound limits of the UE 118 capabilities, see Zheng, Col 4-5 ln 61-67, 1-2. Conclusion & Contact Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to RACHEL J HACKENBERG whose telephone number is (571)272-5417. The examiner can normally be reached 9am-5pm M-F. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Glenton B Burgess can be reached at (571)272-3949. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /RACHEL J HACKENBERG/Primary Examiner, Art Unit 2454 Application/Control Number: 19/007,364 Page 2 Art Unit: 2454 Application/Control Number: 19/007,364 Page 3 Art Unit: 2454 Application/Control Number: 19/007,364 Page 4 Art Unit: 2454 Application/Control Number: 19/007,364 Page 5 Art Unit: 2454 Application/Control Number: 19/007,364 Page 6 Art Unit: 2454 Application/Control Number: 19/007,364 Page 7 Art Unit: 2454 Application/Control Number: 19/007,364 Page 8 Art Unit: 2454 Application/Control Number: 19/007,364 Page 9 Art Unit: 2454 Application/Control Number: 19/007,364 Page 10 Art Unit: 2454 Application/Control Number: 19/007,364 Page 11 Art Unit: 2454 Application/Control Number: 19/007,364 Page 12 Art Unit: 2454 Application/Control Number: 19/007,364 Page 13 Art Unit: 2454 Application/Control Number: 19/007,364 Page 14 Art Unit: 2454 Application/Control Number: 19/007,364 Page 15 Art Unit: 2454 Application/Control Number: 19/007,364 Page 16 Art Unit: 2454 Application/Control Number: 19/007,364 Page 17 Art Unit: 2454 Application/Control Number: 19/007,364 Page 18 Art Unit: 2454 Application/Control Number: 19/007,364 Page 19 Art Unit: 2454 Application/Control Number: 19/007,364 Page 20 Art Unit: 2454 Application/Control Number: 19/007,364 Page 21 Art Unit: 2454 Application/Control Number: 19/007,364 Page 22 Art Unit: 2454 Application/Control Number: 19/007,364 Page 23 Art Unit: 2454 Application/Control Number: 19/007,364 Page 24 Art Unit: 2454 Application/Control Number: 19/007,364 Page 25 Art Unit: 2454 Application/Control Number: 19/007,364 Page 26 Art Unit: 2454 Application/Control Number: 19/007,364 Page 27 Art Unit: 2454 Application/Control Number: 19/007,364 Page 28 Art Unit: 2454 Application/Control Number: 19/007,364 Page 29 Art Unit: 2454 Application/Control Number: 19/007,364 Page 30 Art Unit: 2454 Application/Control Number: 19/007,364 Page 31 Art Unit: 2454 Application/Control Number: 19/007,364 Page 32 Art Unit: 2454 Application/Control Number: 19/007,364 Page 33 Art Unit: 2454 Application/Control Number: 19/007,364 Page 34 Art Unit: 2454 Application/Control Number: 19/007,364 Page 35 Art Unit: 2454 Application/Control Number: 19/007,364 Page 36 Art Unit: 2454 Application/Control Number: 19/007,364 Page 37 Art Unit: 2454 Application/Control Number: 19/007,364 Page 38 Art Unit: 2454 Application/Control Number: 19/007,364 Page 39 Art Unit: 2454 Application/Control Number: 19/007,364 Page 40 Art Unit: 2454 Application/Control Number: 19/007,364 Page 41 Art Unit: 2454 Application/Control Number: 19/007,364 Page 42 Art Unit: 2454 Application/Control Number: 19/007,364 Page 43 Art Unit: 2454 Application/Control Number: 19/007,364 Page 44 Art Unit: 2454 Application/Control Number: 19/007,364 Page 45 Art Unit: 2454 Application/Control Number: 19/007,364 Page 46 Art Unit: 2454 Application/Control Number: 19/007,364 Page 47 Art Unit: 2454 Application/Control Number: 19/007,364 Page 48 Art Unit: 2454 Application/Control Number: 19/007,364 Page 49 Art Unit: 2454 Application/Control Number: 19/007,364 Page 50 Art Unit: 2454 Application/Control Number: 19/007,364 Page 51 Art Unit: 2454 Application/Control Number: 19/007,364 Page 52 Art Unit: 2454 Application/Control Number: 19/007,364 Page 53 Art Unit: 2454 Application/Control Number: 19/007,364 Page 54 Art Unit: 2454 Application/Control Number: 19/007,364 Page 55 Art Unit: 2454 Application/Control Number: 19/007,364 Page 56 Art Unit: 2454 Application/Control Number: 19/007,364 Page 58 Art Unit: 2454 Application/Control Number: 19/007,364 Page 59 Art Unit: 2454 Application/Control Number: 19/007,364 Page 60 Art Unit: 2454 Application/Control Number: 19/007,364 Page 61 Art Unit: 2454
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