Energy-Aware Routing in Software-Defined Networks with Table Compression (using Wildcard Rules)

Frédéric Giroire 1 Nicolas Huin 1 Joanna Moulierac 1 Khoa Phan 2
1 COATI - Combinatorics, Optimization and Algorithms for Telecommunications
Laboratoire I3S - COMRED - COMmunications, Réseaux, systèmes Embarqués et Distribués, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Software-defined Networks (SDN), in particular OpenFlow, is a new networking paradigm enabling innovation through network programmability. Over past few years, many applications have been built using SDN such as server load balancing, virtual-machine migration, traffic engineering and access control. In this paper, we focus on using SDN for energy-aware routing (EAR). Since traffic load has a small influence on power consumption of routers, EAR allows to put unused links into sleep mode to save energy. SDN can collect traffic matrix and then computes routing solutions satisfying QoS while being minimal in energy consumption. However, prior works on EAR have assumed that the forwarding table of OpenFlow switch can hold an infinite number of rules. In practice, this assumption does not hold since such flow tables are implemented in Ternary Content Addressable Memory (TCAM) which is expensive and power-hungry. We consider the use of wildcard rules to compress the forwarding tables. In this paper, we propose optimization methods to minimize energy consumption for a backbone network while respecting capacity constraints on links and rule space constraints on routers. In details, we present two exact formulations using Integer Linear Program (ILP) and introduce efficient heuristic algorithms. Based on simulations on realistic network topologies, we show that, using this smart rule space allocation, it is possible to save almost as much power consumption as the classical EAR approach
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Submitted on : Friday, April 1, 2016 - 6:10:23 PM
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Frédéric Giroire, Nicolas Huin, Joanna Moulierac, Khoa Phan. Energy-Aware Routing in Software-Defined Networks with Table Compression (using Wildcard Rules). [Research Report] RR-8897, INRIA Sophia Antipolis - I3S. 2016. ⟨hal-01296992⟩



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