DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 2, 4-6, 8, 10-12, 14-16, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Padi et al. (US 2023/0261980 A1), hereinafter referred to as D1, in view of Kumar et al. (US 2023/0412488 A1), hereinafter referred to as D2, in further view of Dasgupta et al. (US 2016/0219065 A1), hereinafter referred to as D5.
Regarding claims 1, 11, and 20, D1 discloses fast reroute for ethernet virtual private networks, which comprises:
reporting, by a router in a network and to a supervisor, capabilities of the route to support fast reroute; and performing, by the router, and in advance of a failure predicted, a fast reroute of at least a portion of the traffic from the primary path to a backup path in the network (Referring to Figures 1-3, nodes in communication with a server in a bidirectional manner. A centralized controller computes globally optimal FRR and/or bypass paths dynamically (performing, by the router, a FRR of at least a portion of traffic from the primary path to a backup path in the network). By considering network conditions in real-time, various embodiments can avoid congestion, packet loss, and overbuilding capacity. See paragraphs 0150-155. When making path determinations take into account the current, historical, and/or future traffic (under a broad literal reasonable interpretation, the prior art teaches accounting for future traffic, such as link or router failure by considering the forecasted future state of the network using extrapolation and/or machine learning, thereby considered in advance of a failure predicted) in a centralized algorithm. See paragraphs 0071-0074 and 0168-0170. The virtual network elements comprise the traditional network element 160 which can be an edge router. See paragraphs 0179-0181. Communication is performed between the edge router and central controller for FRR configuration (reporting by the router to a supervisor, capabilities for FFR) and the edge router performing the FRR according to the commands from the controller.)
D1 does not disclose receiving, at the router, a prediction model from the supervisor that is able to predict failures along a path in the network and FRR in advance of the failure predicted by the router.
D1 teaches virtual network elements, which comprise edge routers. See paragraphs 0178-180. D1 teaches performing FFR according to a forecasted future state. See paragraphs 0071-0074. D2 teaches aspects of controller 52 may be distributed among one or more real or virtual computing devices (under a broad literal reasonable interpretation, the distribution of the controller’s aspects, prediction module, to virtual computing devices is interpreted as receiving, at the router, a prediction model from the supervisor that is able to predict failures along a path in the network). See paragraphs 0024-0026 and 0046. Link metrics prediction module 62 executes a machine learning system to predict link stability of one or more links 9 of FIG. 1 (predicting, using the prediction model, a failure along a primary path in the network that is currently being used by the router to send traffic). In some examples, the machine learning system is a deep learning system. The machine learning system processes values of the link metric for each link 9 to generate a predicted future value 66 of the link metric for each link of the plurality of links. For example, link metrics prediction module 62 may predict a latency, a number of transitions of the link 9 from an “active” state to an “inactive” state, or an average downtime of the link at a future time. See paragraphs 0032-0037. D1 teaches a centralized approach for computing bypass/FRR according to forecasted, predicted, link failure for virtual network nodes. D2 teaches machine learning for link behavior prediction for use in path selection comprising a virtual controller whose aspects may be distributed to other virtual computing devices. Essentially, D1 teaches the claimed invention of FFR according to predicted failure along a primary path in a network according to a central controller. D1 does not explicitly disclose the distributed prediction model as claimed, receiving, at the router, a prediction model. D2, in the similar field of inventions, teaches utilizing machine learning to predict link failure utilizing virtual machines in which functionality of the controller can be distributed amongst virtual computing devices.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the computing of FFR tunnels of D1 in the distributed prediction system of D2. One of ordinary skill in the art before the effective filing date of the invention would have been motivated to do so to improve performance and scalability by placing processing power and storage closer to the data source or end-users. Thereby, improving real-time data processing, reduce latency, and minimize the need for data transfers.
D1 does not disclose executing, by the router, the prediction model to predict a failure along a primary path in the network that is currently being used by the router to send traffic.
D5 teaches that CE-2 (router, executing the prediction model to predict an anomaly) acts as a DLA (distributed learning agent), receives configuration information from the SLA (supervisory learning agent), see paragraph 0049, that monitors traffic flows associated with the devices of local network 160 (e.g., by comparing the monitored conditions to one or more machine-learning models). For example, assume that device/node 10 sends a particular traffic flow 302 to server 154. In such a case, router CE-2 may monitor the packets of traffic flow 302 and, based on its local anomaly detection mechanism, determine that traffic flow 302 is anomalous. Anomalous traffic flows may be incoming, outgoing, or internal to a local network serviced by a DLA, in various cases. Referring to Figures 3 and see paragraph 0051 and see also paragraphs 0052-0054. A learning machine may dynamically make future predictions based on current or prior network measurements, may make control decisions based on the effects of prior control commands, etc. See paragraph 0039.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement at the router, which executes the machine learning model, of D5 in the system of D1 and D2, thereby, performing FFR according to a forecasted future state, predicted failure, at the router. One of ordinary skill in the art before the effective filing date of the invention would have been motivated to do so to reduce rerouting time requirements by placing processing, configuration, and detection closer to a data source or end-users.
Regarding claims 2 and 12, the primary reference further teaches wherein the router is a P router or a provider edge (PE) router (Referring to Figures 1-3, The virtual network elements comprise the traditional network element 160 which can be an edge router. See paragraphs 0179-0181.)
Regarding claims 4 and 14, the primary reference further teaches wherein the router uses Internet Protocol (IP) Fast Reroute (IP FRR) to perform the fast reroute (Referring to Figures 1-3, virtual network elements performing FRR comprising IP edge routers. See paragraphs 0180-0183.)
Regarding claims 5 and 15, the primary reference further teaches obtaining, by the router, pre-reroute telemetry by probing the backup path in response to predicting the failure; and obtaining, by the router, post-reroute telemetry by continuing to probe the backup path after performing the fast reroute to the backup path (Referring to Figures 1-3, performing FRR and/or bypass paths dynamically by considering network conditions in real-time various embodiments can avoid congestion, packet loss, and overbuilding capacity. See paragraphs 0150-155. When making path determinations take into account the current, historical, and/or future traffic, under a broad literal reasonable interpretation, the Examiner interprets the consideration of network conditions in real-time according to current, historical, and future traffic as pre-reroute telemetry and post-reroute telemetry as the system constantly monitors network traffic and conditions on pathways before and after rerouting. See paragraphs 0071-0074 and 0168-0170.)
Regarding claims 6 and 16, the primary reference further teaches determining a performance of the prediction model based on the pre-reroute telemetry and on the post-reroute telemetry (Referring to Figures 1-3, performing FRR and/or bypass paths dynamically by considering network conditions in real-time various embodiments can avoid congestion, packet loss, and overbuilding capacity. See paragraphs 0150-155. When making path determinations take into account the current, historical, and/or future traffic, under a broad literal reasonable interpretation, the Examiner interprets the consideration of network conditions in real-time according to current, historical, and future traffic determining a performance of the prediction model as the system is constantly updating according to changing network conditions. See paragraphs 0071-0074 and 0168-0170.)
Regarding claims 8 and 18, the primary reference further teaches selecting, by the router, the portion of the traffic to be fast rerouted onto the backup path based on one or more applications associated with it (Referring to Figures 1-3, performing FRR and/or bypass paths dynamically by considering network conditions in real-time (applications associated with it), various embodiments can avoid congestion, packet loss, and overbuilding capacity. See paragraphs 0150-155. When making path determinations take into account the current, historical, and/or future traffic. See paragraphs 0071-0074 and 0168-0170. The virtual network elements, comprise edge routers, which perform the FRR.)
Regarding claim 10, the primary reference further teaches wherein the backup path is a tunnel in the network pre-established by the router before predicting the failure of the primary path (Referring to Figures 1-3, virtualized communication network 300 can facilitate in whole or in part dynamic re-routing of network traffic depending upon total traffic flow on a path from one network node to another network node (in various specific examples, the dynamic re-routing can be in real-time or near real-time); thereby, establishing backup path before predicted failure of the primary path. See paragraphs 0176-0178.)
Claim(s) 3, 9, 13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Padi et al. (US 2023/0261980 A1), hereinafter referred to as D1, in view of Kumar et al. (US 2023/0412488 A1), hereinafter referred to as D2, in view of Dasgupta et al. (US 2016/0219065 A1), hereinafter referred to as D5, in further view of Ye (US 2015/0304214 A1), hereinafter referred to as D3.
Regarding claims 3 and 13, D1 does not disclose wherein the router uses Multiprotocol Label Switching Fast Reroute (MPLS FRR) to perform the fast reroute.
D3 teaches fast reroute in MPLS traffic engineered networks. See paragraphs 0028-0030.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the MPLS FRR of D3 in the system of D1, D2, and D5. One of ordinary skill in the art before the effective filing date of the invention would have been motivated to do so to comply with well-known standards. In so doing, unexpected results are not achieved.
Regarding claims 9 and 19, D1 does not disclose wherein the capabilities of the router to support fast reroute are reported by the router to the supervisor via an Open Shortest Path First (OSPF) or Intermediate-System-to-Intermediate-System (ISIS) message.
D3 teaches o intelligently compute a topology for network 60, topology element 112 may in some cases include topology module 116 to receive traffic engineering information, such as traffic engineering data 21 of FIG. 1, describing available resources of network 60, including routers 4 and interfaces thereof and interconnecting network links 9. Topology module 116 may execute one or more southbound protocols, such as Open Shortest Path First with Traffic Engineering extensions (OSPF-TE), Intermediate System to Intermediate System with Traffic Engineering extensions (ISIS-TE), BGP Link State (BGP-LS), to learn traffic engineering information for network 60. See paragraphs 0049-0051.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the protocols of D3 in the system of D1, D2, and D5. One of ordinary skill in the art before the effective filing date of the invention would have been motivated to do so to comply with well-known standards. In so doing, unexpected results are not achieved.
Claim(s) 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Padi et al. (US 2023/0261980 A1), hereinafter referred to as D1, in view of Kumar et al. (US 2023/0412488 A1), hereinafter referred to as D2, in view of Dasgupta et al. (US 2016/0219065 A1), hereinafter referred to as D5, in further view of Chundri (US 2024/0235984 A1), hereinafter referred to as D4.
Regarding claims 7 and 17, D1 does not disclose wherein the failure predicted by the router is a predicted violation of a service level agreement (SLA) by the primary path.
D4 teaches traffic engineering, which comprises traffic for certain PPRs may have more stringent requirement accounting for critical service level agreements (SLAs) (e.g., 5G non-eMBB slice, and/or the like) and should account for any link/node failures along the path. Optional per path attributes like Packet Traffic Accounting” and “Traffic Statistics” instructs all the respective nodes along the path to provision the hardware and to account for the respective traffic statistics. Traffic accounting should be applied based on the PPR-ID. This capability allows a more granular and dynamic measurement of traffic statistics for only certain PPRs as needed. See paragraphs 0116-0120.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the SLA considerations of D4 in the system of D1, D2, and D5. One of ordinary skill in the art before the effective filing date of the invention would have been motivated to do so to improve customer satisfaction by accounting for customer service demands.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection as necessitate by the amendment to the independent claims. The newly cited prior art in light of previously cited prior art teach the claimed invention as explained in the rejection above. See rejection above for further explanation.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mukhopadhyaya et al. (US 10567252 B1) - The computing system applies high availability evaluation metrics to the data to determine a high availability capability score for each network device feature of each network device. Further, the computing system determines, based on the high availability capability scores, an indication of the high availability for the network connection service. The computing system outputs, for display, the indication of the high availability of the network connection service.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DONALD L MILLS whose telephone number is (571)272-3094. The examiner can normally be reached Monday through Friday from 9-5 PM EST.
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DONALD L. MILLS
Primary Examiner
Art Unit 2462
/Donald L Mills/ Primary Examiner, Art Unit 2462