一种基于选择框的有向κ-栅栏构建算法  

A Strong κ-Barrier Construction Scheme Based on Selecting Box for Directional Sensor Networκs

作　　者：范兴刚[1] 王超[1] 杨静静[1] 任勇默 车志聪 

机构地区：[1]浙江工业大学计算机科学与技术学院,杭州310023

出　　处：《计算机学报》2016年第5期946-960,共15页Chinese Journal of Computers

基　　金："十二五"国家科技支撑计划项目(2012BAD10B01);国家自然科学基金(40241461;11405145)资助

摘　　要：κ-栅栏覆盖是有向传感器网络的研究热点之一.该文提出了一种含有最少节点的有向强栅栏覆盖模型（MDNSB）.在这个强栅栏模型中,感知角度不管是小于60°还是大于等于60°,有向节点的最大感知距离都在栅栏方向.在此基础上,提出一种基于有向节点选择框的有向强κ-栅栏覆盖构建算法（DSBCSB）,以节点目标位置为基准构建有向节点选择框,选择框内运动能耗最少的有向移动节点运动到有向强K-栅栏的目标位置,形成有向强1-栅栏覆盖.其中的节点运动能耗由移动能耗和转动能耗两部分组成.水平相邻子区域的1-栅栏通过竖直栅栏联合起来构成强1-栅栏覆盖,多个强1-栅栏构成有向强κ-栅栏覆盖.仿真结果证明了在形成G-栅栏的过程中,该方法比其他算法节省了40%～50%的节点,能耗降低了30%～40%.该文的研究对提升有向无线传感器网络的性能具有重要的理论与实际意义.K-barrier coverage is one of the hot spot in directional sensor network.This paper models MDNSB （strong barrier of minimum directional node）and mainly proposes DSBCSB （directional strong barrier construction based on selecting box）scheme.In MDNSB,sensors with both sensing angle less than 60°and greater than 60°have the largest sense distance toward the direction of barriers.Actuation energy consumption is firstly modeled as the sum of mobility and motility energy consumption.In DSBCSB,first,Barrier location with the largest number of nodes is chosen as barrier target by barrier selection box.Second,directional node selecting box with target location as a center is created.The node with least actuation energy consumption in selecting box moves to target location and turns its sensing direction for 1-barrier construction. Then,vertical barrier is built up between two horizontal adjacent subareas.Finally,these barriers are merged into strong 1-barrier coverage;k strong 1-barriers could build up directional strong K-barriers coverage in area of interest.Simulation results show that our method could effectively constitute K-barrier coverage with 50% less quantity of nodes and 30%—40% less energy consumption than other methods.This research has important theoretical and practical significance.

关 键 词：有向传感器网络 强K-栅栏覆盖 感知距离 目标位置 节点选择 能耗模型 竖直栅栏 物联网 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]