Abstract-Current networks are typically over-provisioned to ensure low delays, redundancy and reliability. These Quality of Service (QoS) guarantees are typically achieved using high end, high power network equipments. Their use, however, has led to concerns regarding green house gas emissions, which garnered a lot of attention recently and have resulted in a number of global initiatives aim at reducing the carbon footprint of Internet Service Providers (ISPs). These initiatives have motivated ISPs and researchers to design novel network algorithms and hardware that scale the usage or active time of a network according to traffic load. To this end, this paper considers the problem of shutting down a subset of bundled links during off-peak periods in order to minimize energy expenditure. Unfortunately, identifying the cables that minimize this objective is an NP-complete problem. Henceforth, we propose several practical heuristics based on Dijkstra's algorithm and Yen's k-shortest paths algorithm.We evaluated our heuristics on the Abilene network -with both real and synthetic traffic matrices and several larger random topologies with various loads. Our results show that the proposed heuristics to be effective and efficient. Moreover, our approaches could potentially reduce the energy usage of cables used in the Abilene network by up to 56.7%, assuming the traffic demands recorded on September 5, 2004.

Current network infrastructures are over-provisioned and thus exhibit poor power efficiency at low traffic load. In this paper, we consider networks comprising of bundled links, whereby each link has one or more physical cables that can be switched off independently. The problem at hand is then to switch off redundant cables during off peak periods, while retaining the QoS provided to existing traffic demands. Unfortunately, the problem to maximally shutdown redundant cables is an NP-complete problem. Henceforth, we design a fast heuristic, called Multiple Paths by Shortest Path First (MSPF), that aims to maximize the number of switched-off cables subject to satisfying maximum link utilization (MLU) and end-to-end delay requirements. We have extensively evaluated the performance of MSPF on both real and synthetic topologies and traffic demands. Further, we have compared its performance against two state-of-the-art techniques: GreenTE usable only when each link has one cable, and FGH that supports bundled links but usable only for networks without MLU and delay constraints. MSPF improves the energy saving on average by 5% as compared to GreenTE incurring only 1% the CPU time. While yielding equivalent energy savings, MSPF requires only 0.35% of the running time of FGH. Finally, for MLU at most 50% and end-to-end delay no longer than the network diameter, MSPF reduces the power usage of the GÉANT topology up to 91% and bundled links consisting of ten cables.

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Current network infrastructures are over‐provisioned and thus exhibit poor power efficiency at low traffic load. We consider networks consisting of bundled links, whereby each link has one or more physical cables that can be switched off independently. The problem at hand is to switch off redundant nodes and cables during off‐peak periods, while retaining the quality of services provided to existing traffic demands. Unfortunately, the problem to maximally shutdown redundant nodes and cables is Non‐deterministic Polynomial‐time (NP)‐complete. Henceforth, we design a fast heuristic, called Multiple Paths by Shortest Path First (MSPF), that aims to maximise the number of switched‐off nodes and cables subject to satisfying maximum link utilisation (MLU) and path length (PL) constraints. We have extensively evaluated the performance of MSPF on both real and synthetic topologies and traffic demands. Further, we have compared its performance against two state‐of‐the‐art techniques: GreenTE, usable when each link has one cable, and Fast Greedy Heuristic (FGH), which supports bundled links but only for networks without MLU and PL constraints. On the Sprint network, MSPF can save on average 5% more power as compared to GreenTE while incurring only 1% of GreenTE's running time. While yielding equivalent power savings, MSPF requires only 0.35% of FGH's running time. Finally, setting MLU to at most 50% and PL to no longer than the network diameter, MSPF reduces the power usage of the GÉANT topology by up to 91% for links consisting of 10 cables. For experiments on synthetic topologies with bundle size of 30, MSPF yields a power saving of 89.81%. Copyright © 2014 John Wiley & Sons, Ltd.

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