toward energy-aware traffic engineering in intra-domain ip networks using heuristic and meta-heuristics approaches

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%.