期刊名称:International Journal of Grid and Distributed Computing
印刷版ISSN:2005-4262
出版年度:2016
卷号:9
期号:1
页码:25-36
DOI:10.14257/ijgdc.2016.9.1.03
出版社:SERSC
摘要:In order to improve the performance of data transmission in SDN, this paper proposes a load balance solution scheme by taking advantage of the global network view of SDN. We collect 4 load features from each transmission path. These features are bandwidth utilization ratio, packet loss rate, transmission latency and transmission hops. By using this 4 load features, BP Artificial Neural Network model is trained to predict the integrated load for different path and to choose one with least load as the data-flow transmission path. The contrast experiment results show that load balancing strategy proposed in this paper can select more rational transmission path for data-flow and achieve 19.3% network latency decrease at most.
关键词:Software Defined Network; Load Balance; BP Artificial Neural Network