Toward Energy-Aware Traffic Engineering in Intra-Domain IP Networks Using Heuristic and Meta-Heuristics Approaches
Subject Areas : Network Management
1 - Bu-Ali Sina University
Keywords: Energy-aware traffic engineering, Green Networking, Greedy Algorithms, Genetic Algorithms,
Abstract :
Because of various ecological, environmental, and economic issues, energy efficient networking has been a subject of interest in recent years. In a typical backbone network, all the routers and their ports are always active and consume energy. Average link utilization in internet service providers is about 30-40%. Energy-aware traffic engineering aims to change routing algorithms so that low utilized links would be deactivated and their load would be distributed over other routes. As a consequence, by turning off these links and their respective devices and ports, network energy consumption is significantly decreased. In this paper, we propose four algorithms for energy-aware traffic engineering in intra-domain networks. Sequential Link Elimination (SLE) removes links based on their role in maximum network utilization. As a heuristic method, Extended Minimum Spanning Tree (EMST) uses minimum spanning trees to eliminate redundant links and nodes. Energy-aware DAMOTE (EAD) is another heuristic method that turns off links with low utilization. The fourth approach is based on genetic algorithms that randomly search for feasible network architectures in a potentially huge solution space. Evaluation results on Abilene network with real traffic matrix indicate that about 35% saving can be obtained by turning off underutilized links and routers on off-peak hours with respect to QoS. Furthermore, experiments with GA confirm that a subset of links and core nodes with respect to QoS can be switched off when traffic is in its off-peak periods, and hence energy can be saved up to 37%.
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