Research And Implementation On Load Balancing Of Data Center Network Based On SDN

In recent years,with the development of cloud computing,big data and the virtualization technology,more and more data transmitted in data center,which may increase the network link congestion probability and easily lead to low throughput and long delay and the decline of the network performance.Software Defined Network(SDN)architecture provides a new solution for problem solving flow management of data center.SDN decouples the control plane and data plane and has a centralized external controller which can control flows and has global optimal scheduling of data traffic in a data center network.The load balance of network link can be predicted in advance,and the probability of link congestion can be reduced by dynamically re-scheduling the path of flows in congestion link.However the existing SDN-based load balance algorithms dependent on data center topologies and there's no good regional division between bandwidth sensitive elephant flow and delay sensitive mouse flow in traffic scheduling.Therefore we propose a Path Load Balance(PLB)algorithm which has the universality for different SDN-based data center network topologies and deals with elephant flow and mouse flow respectively in traffic scheduling.Based on the advantage of SDN,the controller makes routing strategy for all flows inside the data center.During flow transmissions,the controller monitors the flow size and distinguishes the elephant flows.According to the load balance of network link,the proposed PLB changes paths of elephant flows,reduces the probability of link congestion and solves the delay problem caused by link congestion.We also propose a flow table update strategy based on priority to ensure that flows will be re-scheduled to a new path immediately after all flow tables of the associated switches in the old path have been updated successfully when changing the flow path so as to avoid flow transmission interrupt and packet loss problem caused by changing paths of flows.Simulation results show that the proposed PLB has better throughput per flow and bandwidth utilization compared to DFS worst-Fit and LABERIO in fully populated topology and fat-tree topology under a hot-spot traffic pattern.In addition,when traffic load continues to grow from 0.1 to 0.9 in a fully populated topology,the proposed PLB has a better average throughput per flow than that of DFS worst-Fit and LABERIO.This shows that the proposed PLB is scalable in data center networks based on SDN.