Abstract
In 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.
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Research partially supported by Bilateral Grant MISAG-CNR-1, jointly from the Scientific and Technological Research Council of Turkey and the Consiglio Nazionale delle Ricerche, Italy.
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Belotti, P., Pınar, M.Ç. Optimal oblivious routing under linear and ellipsoidal uncertainty. Optim Eng 9, 257–271 (2008). https://doi.org/10.1007/s11081-007-9033-z
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DOI: https://doi.org/10.1007/s11081-007-9033-z