摘要
针对物联网移动感知场景中节点移动性、随机性在时间和空间两方面给数据感知、数据传递造成的问题,提出一种基于节点社会关系认知的目标区域感知服务节点发现算法.引入交互因子和距离因子对节点社会关系进行量化,构建节点移动概率表和凝聚子群,通过信任传递与社会关系最优路径树的计算,确定目标区域感知服务节点集.仿真实验表明,该算法缩短了移动节点间最短距离以及网络平均距离,提高了感知服务节点的发现效率,解决了稀疏网络的感知空洞问题,改善了物联网感知服务质量.
An awareness algorithm to discover service nodes is proposed to deal with the problem of data-awareness and data-transmit in both time and space in mobility-aware of Internet of Things（IoT）,which is caused by nodes mobility and random.The algorithm bases on social relations cognition,and quantizes the social relation of all nodes by introducing interconnection factor and distance factor.Then,cohesive subgroups and a node-mobile probability table are constructed to predict the trace of mobile nodes.Finally,awareness service nodes in the objective regions are determined through trust-transference and probability tree calculation.Simulation experiments show that the proposed method effectively reduces both the shortest distance among mobile nodes and the network average distance,improves the way of date acquisition and increases the quality of awareness service in IoT.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2011年第12期6-9,共4页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(60873071
91018011
61172090)
国家"863计划"资助项目(2008AA01Z410)
IBM共享大学研究(SUR)资助项目(SUR201001X)
关键词
物联网
移动感知
感知服务节点发现算法
最短距离
服务质量
Internet of Things
mobile-awareness
awareness service nodes discovery algorithm
shortest distance
quality of service
作者简介
安健（1983-），男，博士生；
桂小林（通信作者），男，教授，博士生导师．
