会议专题

Clustering Application of SVM in Mobile Ad-hoc Network

Support vector machine (SVM) is trained to classify the mobile nodes as cluster-head nodes or member nodes in this paper. The improved method of SVM is presented. Based on SVM, The process of the classification and clustering is designed. The trained SVM was used to recognize the mobile nodes in MANet. It properly chooses the function subsets and the discrimination function to make the learning machine least risk. The SVM classifier is made to learn the result of the WCA clustering algorithm so as to cluster mobile Ad-hoc network as the WCA. Simulation results show that compared to other methods, the method presented is more easily to simplify the clustering process in MANet. And the request of real-time clustering of nodes in mobile network can be satisfied. The end is new design thinking and the conclusion for the research.

Chen Haixia Du Ronghua Li Ping Li Xiaying

Changsha University of Science and Technology, Changsha, 410076, China

国际会议

International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

长沙

英文

2215-2217

2008-10-20(万方平台首次上网日期,不代表论文的发表时间)