Resilient Capacity-Aware Routing

Schmid, Stefan; Schnepf, Nicolas; Srba, Jǐŕı

doi:10.1007/978-3-030-72016-2_22

Cited by 2 publications

(2 citation statements)

References 35 publications

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“…In particular, it would be interesting to chart a similar landscape for the practically relevant scenarios in which links failures are random, or where the routing rules themselves can be subject to randomization. It would further be interesting to account for additional aspects which influence dependability in practice, and e.g., optimize the "hazard value" [53], [54] of the network more generally.…”

Section: Discussionmentioning

confidence: 99%

On the Price of Locality in Static Fast Rerouting

Foerster¹,

Hirvonen²,

Pignolet³

et al. 2022

Preprint

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Modern communication networks feature fully decentralized flow rerouting mechanisms which allow them to quickly react to link failures. This paper revisits the fundamental algorithmic problem underlying such local fast rerouting mechanisms. Is it possible to achieve perfect resilience, i.e., to define local routing tables which preserve connectivity as long as the underlying network is still connected? Feigenbaum et al. [1] and Foerster et al. [2] showed that, unfortunately, it is impossible in general.This paper charts a more complete landscape of the feasibility of perfect resilience. We first show a perhaps surprisingly large price of locality in static fast rerouting mechanisms: even when source and destination remain connected by a linear number of link-disjoint paths after link failures, local rerouting algorithms cannot find any of them which leads to a disconnection on the routing level. This motivates us to study resilience in graphs which exclude certain dense minors, such as cliques or a complete bipartite graphs, and in particular, provide characterizations of the possibility of perfect resilience in different routing models. We provide further insights into the price of locality by showing impossibility results for few failures and investigate perfect resilience on Topology Zoo networks.

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Section: Discussionmentioning

confidence: 99%

On the Price of Locality in Static Fast Rerouting

Foerster¹,

Hirvonen²,

Pignolet³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Our paper accounts for the physical topology explicitly, among other properties, and we model the routing with constraints. Our approach is hence orthogonal to work on resilient routing mechanisms [25]. It is also orthogonal to work studying how to verify and maintain routing and policy constraints under failures [17], [27].…”

Section: Related Workmentioning

confidence: 99%

The Hazard Value: A Quantitative Network Connectivity Measure Accounting for Failures

Cuijpers

Schmid

Schnepf

et al. 2022

2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

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To meet their stringent requirements in terms of performance and dependability, communication networks should be "well connected". While classic connectivity measures typically revolve around topological properties, e.g., related to cuts, these measures may not reflect well the degree to which a network is actually dependable. We introduce a more refined measure for network connectivity, the hazard value, which is developed to meet the needs of a real network operator. It accounts for crucial aspects affecting the dependability experienced in practice, including actual traffic patterns, distribution of failure probabilities, routing constraints, and alternatives for services with preferences therein. We analytically show that the hazard value fulfills several fundamental desirable properties that make it suitable for comparing different network topologies with one another, and for reasoning about how to efficiently enhance the robustness of a given network. We also present an optimised algorithm to compute the hazard value and an experimental evaluation against networks from the Internet Topology Zoo and classical datacenter topologies, such as fat trees and BCubes. This evaluation shows that the algorithm computes the hazard value within minutes for realistic networks, making it practically usable for network designers.

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Resilient Capacity-Aware Routing

Cited by 2 publications

References 35 publications

On the Price of Locality in Static Fast Rerouting

On the Price of Locality in Static Fast Rerouting

The Hazard Value: A Quantitative Network Connectivity Measure Accounting for Failures

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