基于小世界网络模型的工业企业物联网数据感知网络拓扑优化  

作　　者：郑涛[1] 刘聪颖[1] 

机构地区：[1]燕山大学经济管理学院

出　　处：《企业经济》2015年第1期78-81,共4页Enterprise Economy

基　　金：河北省教育厅科研项目"物联网与工业企业决策支持系统深度融合方法研究"(批准号:QN2014212);燕山大学青年教师自主研究计划课题"物联网环境下工业企业决策支持系统研究"(批准号:13SKA001)

摘　　要：党的十八大提出工业化与信息化深度融合命题。工业企业通过改变传统的生产模式,实现与物联网融合应用将给工业企业带来新的发展潜力。本文针对物联网感知设备大量应用所导致的"热点问题"进行分析,研究工业企业物联网数据感知设备节点布局优化问题,以小世界网络模型具备的高集聚系数特性作为算法的基础,提出改进型分簇算法,并对节点的拓朴结构以及数据传输路径进行优化。最后得出网络数据仿真模型能够实现降低数据传输能耗、延长网络生命周期的结论。The 18th National Congress of CPC proposed a proposition of the deep integration of industrialization and information. The industrial enterprises introduce the concept of the internet of things to break the traditional mode of production. The fusion applications of both will bring new development potentials to the industrial enterprises. This paper will focus on analysis of the excessive application of the sensing device on the internet of things and research the problems to optimize the layout of the sensing device nodes. We will use the high clustering coefficient characteristics with small- world network model as a basis for the algorithm, and on this basis, put forward the improved algorithm to optimize the topology of the nodes and the data transmission paths. At last, it is concluded that the simulation model of the data can achieve the purpose to reduce da- ta transmission energy consumption and prolong the network life cycle.

关 键 词：物联网 感知层 小世界网络 分簇算法 

分 类 号：F272.3[经济管理—企业管理]