2014 · 38 citations · 14 references
ComputingComputer EngineeringComputer ScienceCloud NetworkingCloud Performance OptimizationComputer NetworksCongestion ControlNetwork Performance AnalysisRoutingRouting AlgorithmsSoftware-defined NetworkingData Center NetworkingData Center Traffic EngineeringLink UtilizationNetwork ResourcesNetwork Traffic EngineeringSoftware-defined Traffic EngineeringStatic RoutingTraffic Load Balancing
Today's Data Center Networks (DCNs) contain tens of thousands of hosts with significant bandwidth requirements as the needs for cloud computing, multimedia contents, and big data analysis are increasing. However, the existing DCN technologies accompany the following two problems. First, power consumptions of a DCN is constant regardless of the utilization of network resources. Second, due to a static routing scheme, a few links in DCNs are experiencing congestions while other majority links are being underutilized. To overcome these limitations of the current DCNs, we propose a Software Defined Networking (SDN)-based Traffic Engineering (TE), which consists of optimal topology composition and traffic load balancing. We can reduce the power consumptions of the DCN by turning off links and switches that are not included in the optimal subset topology. To diminish network congestions, the traffic load balancing distributes ever-changing traffic demands over the found optimal subset topology. Simulation results revealed that the proposed SDN-based TE approach can reduce power consumptions of a DCN about 41% and Maximum Link Utilization (MLU) about 60% on average in comparison with a static routing scheme.
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