Load-optimal local fast rerouting for dense networks

Michael Borokhovich, Yvonne Anne Pignolet, Stefan Schmid, Gilles Tredan

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Reliable and highly available computer networks must implement resilient fast rerouting mechanisms: Upon a link or node failure, an alternative route is determined quickly, without involving the network control plane. Designing such fast failover mechanisms capable of dealing with multiple concurrent failures, however, is challenging, as failover rules need to be installed proactively, i.e., ahead of time, without knowledge of the actual failures happening at runtime. Indeed, only little is known today about the design of resilient routing algorithms. This paper introduces a general framework to reason about and design local failover algorithms that minimize the resulting load after failover on dense networks, beyond destination-based routing. We show that due to the inherent locality of the failover decisions at runtime, the problem is fundamentally related to the field of distributed algorithms without coordination. We derive an intriguing lower bound on the inherent network load overhead any local fast failover scheme that will introduce in the worst case, even though globally seen, much more balanced traffic allocations exist. We then present different randomized and deterministic failover algorithms and analyze their overhead load. In particular, we build upon the theory of combinatorial designs and develop a novel deterministic failover mechanism based on symmetric block design theory, which tolerates a maximal number of link failures while ensuring low loads.

Original languageEnglish
Article number8476208
Pages (from-to)2583-2597
Number of pages15
JournalIEEE/ACM Transactions on Networking
Volume26
Issue number6
DOIs
StatePublished - 1 Dec 2018
Externally publishedYes

Keywords

  • Computer network reliability
  • distributed algorithms

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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