一种基于聚类算法的机会网络路由算法  

An Opportunistic Network Routing Algorithm Based on Clustering Algorithm

作　　者：何志立 潘达儒[1] 宋晖[1] HE Zhili;PAN Daru;SONG Hui(School of Physics and Telecommunication Engineering,South China Normal University,Guangzhou 510006,China)

机构地区：[1]华南师范大学物理与电信工程学院

出　　处：《华南师范大学学报（自然科学版）》2019年第4期120-128,共9页Journal of South China Normal University(Natural Science Edition)

基　　金：国家自然科学基金项目(61471175,61771206)

摘　　要：在传统的历史路径算法的基础上,提出一种基于聚类算法的历史路径机会网络路由算法(RACA算法).该算法使用无监督学习中的k-means++算法对节点进行编码,并使用编码的方式更新历史路径算法,具有缓存空间占用低、节点搜索速度快和在拓扑结构多变的环境的适应性强等特点.实验结果表明:RACA算法在多个方面有着较好的表现,特别是在传输成功率和开销比率方面有较好的表现;出色的网络性能表现使得RACA算法能够在资源有限的场景和网络环境变化较大的场景使用,例如车载网络环境.A historical path routing algorithm of opportunistic network is proposed on the basis of clustering algorithm in order to optimize the traditional historical path algorithm.The algorithm uses the k-means++algorithm in unsupervised learning to encode the nodes and uses the coding method to update the historical path algorithm.It is characterized by low cache space occupation,high node search speed and strong adaptability in the environment with varied topology.The experimental results show that the RACA algorithm has better performance in many aspects,especially in terms of delivery ratio and overhead ratio.The good network performance enables RACA algorithm to be used in scenarios of limited resources and changeable network environment,for example,the in-vehicle network environments.

关 键 词：聚类算法 无监督学习 路由算法 机会网络 时延容忍网络 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]