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dc.contributor.authorBelotti, P.en_US
dc.contributor.authorPınar, M. Ç.en_US
dc.date.accessioned2016-02-08T10:07:55Z
dc.date.available2016-02-08T10:07:55Z
dc.date.issued2008en_US
dc.identifier.issn1389-4420
dc.identifier.urihttp://hdl.handle.net/11693/23024
dc.description.abstractIn telecommunication networks, a common measure is the maximum congestion (i.e., utilization) on edge capacity. As traffic demands are often known with a degree of uncertainty, network management techniques must take into account traffic variability. The oblivious performance of a routing is a measure of how congested the network may get, in the worst case, for one of a set of possible traffic demands. We present two models to compute, in polynomial time, the optimal oblivious routing: a linear model to deal with demands bounded by box constraints, and a second-order conic program to deal with ellipsoidal uncertainty, i.e., when a mean-variance description of the traffic demand is given. A comparison between the optimal oblivious routing and the well-known OSPF routing technique on a set of real-world networks shows that, for different levels of uncertainty, optimal oblivious routing has a substantially better performance than OSPF routing.en_US
dc.language.isoEnglishen_US
dc.source.titleOptimization and Engineeringen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s11081-007-9033-zen_US
dc.subjectTraffic engineeringen_US
dc.subjectOblivious routingen_US
dc.subjectLinear programmingen_US
dc.subjectSecond order cone programmingen_US
dc.titleOptimal oblivious routing under linear and ellipsoidal uncertaintyen_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.citation.spage257en_US
dc.citation.epage271en_US
dc.citation.volumeNumber9en_US
dc.citation.issueNumber3en_US
dc.identifier.doi10.1007/s11081-007-9033-zen_US
dc.publisherSpringeren_US
dc.identifier.eissn1573-2924


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