2017 · 13 citations · 13 references
ComputingComputer SystemsComputer NetworksMobile SystemsQueuing TheoryNetwork Flow AlgorithmsNetwork OptimizationRoutingRouting AlgorithmsSoftware-defined NetworkingEnergyEnergy ConsumptionEnergy-efficient NetworkingEnergy-efficient Resource AllocationExperimental Results InterpretationHeuristic ApproachNetwork Energy OptimizationTraffic Load Effects
5G networks are expected to be highly energy efficient, with a 10 times lower consumption than today's systems. An effective way to achieve such a goal is to act on the backhaul network by controlling the nodes operational state and the allocation of traffic flows. To this end, in this paper we formulate energy-efficient flow routing on the backhaul network as an optimization problem. In light of its complexity, which impairs the solution in large-scale scenarios, we then propose a heuristic approach. Our scheme, named EMMA, aims to both turn off idle nodes and concentrate traffic on the smallest possible set of links, which in its turn increases the number of idle nodes. We implement EMMA on top of ONOS and derive experimental results by emulating the network through Mininet. Our results show that EMMA provides excellent energy saving performance, which closely approaches the optimum. In larger network scenarios, the gain in energy consumption that EMMA provides with respect to the simple benchmark where all nodes are active, is extremely high under medium-low traffic load.
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ElasticTree: saving energy in data center networks
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Reducing Power Consumption in Backbone Networks
Luca Chiaraviglio, Marco Mellia, F. Neri · 2009 · 358 citations · Full text
Will Fisher, Martin Suchara, Jennifer Rexford · 2010 · 237 citations
Natural Sciences, Computer Engineering, Computer Networks +16
On‐line and first fit colorings of graphs
András Gyárfás, Jenő Lehel · Journal of Graph Theory · 1988 · 193 citations