Ideally, the network should be dynamically reconfigured as traffic evolves. Yet, even within the software defined network paradigm, network reconfigurations cannot be too frequent due to a number of reasons related to route consistency, forwarding rules instantiation, individual flows dynamics, traffic monitoring overhead, and so on. In this paper, we focus on the fundamental issue of deciding whether, when, and how to reconfigure the network while traffic evolves. We consider a problem of optimizing semi‐stable routing in the capacitated multicommodity flow network when one may use at most a given maximum number of routing configurations (called routing clusters) and when each routing configuration must be used for at least a given minimum amount of time. We propose an efficient solution approach based on routing cluster generation that provides a tight lower bound on the minimum of a selected objective function (like maximum link delay or a sum of link delays) and suboptimal solutions very close to the calculated bound. The approach scales well with the size of the network.

An efficient approach to optimization of semi‐stable routing in multicommodity flow networks

Filippini, Ilario;Capone, Antonio
2021-01-01

Abstract

Ideally, the network should be dynamically reconfigured as traffic evolves. Yet, even within the software defined network paradigm, network reconfigurations cannot be too frequent due to a number of reasons related to route consistency, forwarding rules instantiation, individual flows dynamics, traffic monitoring overhead, and so on. In this paper, we focus on the fundamental issue of deciding whether, when, and how to reconfigure the network while traffic evolves. We consider a problem of optimizing semi‐stable routing in the capacitated multicommodity flow network when one may use at most a given maximum number of routing configurations (called routing clusters) and when each routing configuration must be used for at least a given minimum amount of time. We propose an efficient solution approach based on routing cluster generation that provides a tight lower bound on the minimum of a selected objective function (like maximum link delay or a sum of link delays) and suboptimal solutions very close to the calculated bound. The approach scales well with the size of the network.
2021
integer programming
multicommodity flows
semi-stable routing
software defined networks
time-dependent traffic
integer programming; multicommodity flows; semi‐stable routing; software defined networks; time‐dependent traffic
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1194451
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