An optimization model for communication networks resilient to partial multiple link failures

Yoann Fouquet, Michal Pioro, Dritan Nace, Michael Poss, Mateusz Zotkiewicz

Research output: Contribution to conferencePaper, not in proceedingpeer-review

Abstract

This submission is devoted to optimization of networks that permanently experience fluctuations
of the capacity available on their links. This is an important and novel topic since limited link availability is a fundamental feature in wireless networks and yet majority of
work in survivable network design is restricted to the total single link failures. We assume
a given finite set of network states. Each state is characterized by availability coefficients
specifying, for each link, the fraction of its reference capacity available in this state, and
by traffic coefficients specifying, for each demand, the proportion of its reference traffic to
be realized in the considered state. Our routing strategy allows for thinning/thickening the
reference path-flows, with the thickening limited by a given upper bound U of the reference
value. Thus, in each state, the value of every path-flow can range from 0 to U times its
reference value. For the corresponding link cost minimization problem (where link capacities
and state-dependent path-flows are decision variables) we present a non-compact linear programming
model together with a solution algorithm based on path generation. We illustrate
the effectiveness of the introduced routing strategy by presenting numerical results for a set
of representative network examples.
Original languageEnglish
Publication statusPublished - 2014
Event2014 INFORMS Telecommunications Conference - Lisbon, Portugal
Duration: 2014 Mar 22014 Mar 4

Conference

Conference2014 INFORMS Telecommunications Conference
Country/TerritoryPortugal
CityLisbon
Period2014/03/022014/03/04

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering

Keywords

  • survivable networks
  • partial multiple failures
  • path generation

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