公开(公告)号：US20230208720A1

公开(公告)日：2023-06-29

申请号：US18175127

申请日：2023-02-27

Applicant: Google LLC

Inventor： Min Wen ,  Wenjie Jiang ,  Anurag Sharma ,  Matthew Johnston ,  Rodolfo Enrique Alvizu Gomez

IPC: H04L41/12 ,  H04L41/14 ,  H04L45/02

CPC classification number: H04L41/12 ,  H04L41/14 ,  H04L45/02 ,  H04L45/08

Abstract: Methods, systems, and apparatus, including computer-readable storage media, optimizing interior gateway protocol (IGP) metrics using reinforcement learning (RL) for a network domain. The system can receive a topology (G) of a network domain, a set of flows (F), and an objective function. The system can optimize, using reinforcement learning, the objective function based on the received topology and the one or more flows F. The system can determine updated IGP metrics based on the optimization of the objective function. The IGP metrics for the metric domain may be updated with the updated IGP metrics.

公开(公告)号：US20230110983A1

公开(公告)日：2023-04-13

申请号：US17498918

申请日：2021-10-12

Applicant: Google LLC

Inventor： Jinjie He ,  Matthew Johnston ,  Anurag Sharma

IPC: H04L12/24

Abstract: The subject matter described herein provides systems and techniques for a network planning and optimization tool that may allow for network capacity planning using key network failures for an arbitrary pair of network topology and demands. Performing network capacity planning with key network failures, instead of using other techniques, may avoid over-building the topology of a network. In particular, key network failures may be generated from the probabilistic failures, and the impact of these failures on a network may be computed. Expected flow availability SLO or a function thereof may be computed, using this information, and used by the tool to design a robust network. With an embedded flow availability calculation and updated risk framework, the capacitated cross-layer network topologies output by the tool may meet network demands/flows with their respective SLO type at the lowest cost.

公开(公告)号：US20220376984A1

公开(公告)日：2022-11-24

申请号：US17323464

申请日：2021-05-18

Applicant: Google LLC

Inventor： Min Wen ,  Wenjie Jiang ,  Anurag Sharma ,  Matthew Johnston ,  Rodolfo Enrique Alvizu Gomez

IPC: H04L12/24 ,  H04L12/751

Abstract: Methods, systems, and apparatus, including computer-readable storage media, optimizing interior gateway protocol (IGP) metrics using reinforcement learning (RL) for a network domain. The system can receive a topology (G) of a network domain, a set of flows (F), and an objective function. The system can optimize, using reinforcement learning, the objective function based on the received topology and the one or more flows F. The system can determine updated IGP metrics based on the optimization of the objective function. The IGP metrics for the metric domain may be updated with the updated IGP metrics.

公开(公告)号：US12218808B2

公开(公告)日：2025-02-04

申请号：US18195974

申请日：2023-05-11

Applicant: Google LLC

Inventor： Jinjie He ,  Matthew Johnston ,  Anurag Sharma

IPC: H04L41/5025 ,  H04L41/0631

Abstract: The subject matter described herein provides systems and techniques for a network planning and optimization tool that may allow for network capacity planning using key network failures for an arbitrary pair of network topology and demands. Performing network capacity planning with key network failures, instead of using other techniques, may avoid over-building the topology of a network. In particular, key network failures may be generated from the probabilistic failures, and the impact of these failures on a network may be computed. Expected flow availability SLO or a function thereof may be computed, using this information, and used by the tool to design a robust network. With an embedded flow availability calculation and updated risk framework, the capacitated cross-layer network topologies output by the tool may meet network demands/flows with their respective SLO type at the lowest cost.

公开(公告)号：US11695651B2

公开(公告)日：2023-07-04

申请号：US17498918

申请日：2021-10-12

Applicant: Google LLC

Inventor： Jinjie He ,  Matthew Johnston ,  Anurag Sharma

IPC: H04L12/24 ,  H04L12/26 ,  H04L41/5025 ,  H04L41/0631

CPC classification number: H04L41/5025 ,  H04L41/065

Abstract: The subject matter described herein provides systems and techniques for a network planning and optimization tool that may allow for network capacity planning using key network failures for an arbitrary pair of network topology and demands. Performing network capacity planning with key network failures, instead of using other techniques, may avoid over-building the topology of a network. In particular, key network failures may be generated from the probabilistic failures, and the impact of these failures on a network may be computed. Expected flow availability SLO or a function thereof may be computed, using this information, and used by the tool to design a robust network. With an embedded flow availability calculation and updated risk framework, the capacitated cross-layer network topologies output by the tool may meet network demands/flows with their respective SLO type at the lowest cost.

公开(公告)号：US11601336B2

公开(公告)日：2023-03-07

申请号：US17323464

申请日：2021-05-18

Applicant: Google LLC

Inventor： Min Wen ,  Wenjie Jiang ,  Anurag Sharma ,  Matthew Johnston ,  Rodolfo Enrique Alvizu Gomez

IPC: H04L12/28 ,  H04L41/12 ,  H04L45/02 ,  H04L41/14

Abstract: Methods, systems, and apparatus, including computer-readable storage media, optimizing interior gateway protocol (IGP) metrics using reinforcement learning (RL) for a network domain. The system can receive a topology (G) of a network domain, a set of flows (F), and an objective function. The system can optimize, using reinforcement learning, the objective function based on the received topology and the one or more flows F. The system can determine updated IGP metrics based on the optimization of the objective function. The IGP metrics for the metric domain may be updated with the updated IGP metrics.

公开(公告)号：US20230283534A1

公开(公告)日：2023-09-07

申请号：US18195974

申请日：2023-05-11

Applicant: Google LLC

Inventor： Jinjie He ,  Matthew Johnston ,  Anurag Sharma

IPC: H04L41/5025 ,  H04L41/0631

CPC classification number: H04L41/5025 ,  H04L41/065

Abstract: The subject matter described herein provides systems and techniques for a network planning and optimization tool that may allow for network capacity planning using key network failures for an arbitrary pair of network topology and demands. Performing network capacity planning with key network failures, instead of using other techniques, may avoid over-building the topology of a network. In particular, key network failures may be generated from the probabilistic failures, and the impact of these failures on a network may be computed. Expected flow availability SLO or a function thereof may be computed, using this information, and used by the tool to design a robust network. With an embedded flow availability calculation and updated risk framework, the capacitated cross-layer network topologies output by the tool may meet network demands/flows with their respective SLO type at the lowest cost.

公开(公告)号：US11811614B2

公开(公告)日：2023-11-07

申请号：US18175127

申请日：2023-02-27

Applicant: Google LLC

Inventor： Min Wen ,  Wenjie Jiang ,  Anurag Sharma ,  Matthew Johnston ,  Rodolfo Enrique Alvizu Gomez

IPC: H04L12/28 ,  H04L41/12 ,  H04L41/14 ,  H04L45/02

CPC classification number: H04L41/12 ,  H04L41/14 ,  H04L45/02 ,  H04L45/08

Abstract: Methods, systems, and apparatus, including computer-readable storage media, optimizing interior gateway protocol (IGP) metrics using reinforcement learning (RL) for a network domain. The system can receive a topology (G) of a network domain, a set of flows (F), and an objective function. The system can optimize, using reinforcement learning, the objective function based on the received topology and the one or more flows F. The system can determine updated IGP metrics based on the optimization of the objective function. The IGP metrics for the metric domain may be updated with the updated IGP metrics.

公开(公告)号：US11329900B1

公开(公告)日：2022-05-10

申请号：US17316242

申请日：2021-05-10

Applicant: Google LLC

Inventor： Matthew Johnston ,  Anurag Sharma ,  Robert Nygaard ,  Ray Bennett ,  Robert Withrow

IPC: H04L12/24 ,  H04L41/5041 ,  H04L41/5003 ,  H04L41/14 ,  H04L41/12 ,  H04L41/082

Abstract: Determining an upgrade path from a starting topology to a target topology of a network is computationally intense and does not guarantee a steadily increasing usable capacity of the network at each stage within the upgrade path. The disclosed technology allows for a sequence of stages related to network upgrades to be generated. The technology ensures that networks can be upgraded in a sequential manner, where each step in the sequence does not violate service level objectives related to the network, ensures operational continuity of the network by users of the network, and ensures that the available network resources increase as the sequential upgrades are rolled out. The pathway determined is determined in a computationally efficient manner.