摘要
考虑实际无线传感网系统中数据传输时延和跳数受限情况,且为降低算法的时间复杂度,提出一种移动无线传感网的Sink节点移动路径选择算法(MPSA)。在MPSA算法中,Sink节点采用分布式最短路径树算法收集k+1跳通信范围内传感节点的相关信息和感知数据,采用虚拟力理论计算边界、障碍物和空洞区域的虚拟斥力、第k+1跳未覆盖传感节点的虚拟引力和所有虚拟力的合力,根据停留次数、合力大小和方向等信息计算当前网格中心的停留时间和下一个停留网格中心。仿真结果表明:MPSA算法根据传感节点的位置、剩余能量等信息,寻找到一条较优的移动路径,从而提高Sink节点的数据收集量和节点覆盖率,降低传感节点的感知数据丢弃量。总之,在数据传输时延和跳数受限下,MPSA算法比RAND算法、GMRE算法和EASR算法更优。
Considering that data transmission delay and hops are limited in actual system,and to reduce the timecomplexity of algorithm,sink node moving path selection algorithm(MPSA)in mobile wireless sensor networks isproposed. In MPSA algorithm,sink node uses distributed shortest path tree algorithm to gather relevant informationand data of sensor nodes in k+1-hop communication range. It uses virtual force theory to calculate the virtual repul-sive forces of boundaries,obstacles and void regions,virtual gravitational forces of non-covered k+1-hop sensornodes and resultant force of all virtual forces. It calculates residence time at present grid center and next residencegrid center based on the information such as number of residence,size and direction of the resultant force. Simula-tion results show that according to the information such as node position and residual energy,MPSA algorithm canfind an appropriate moving path of sink node,improve the gathering data amount and node coverage rate of sinknode,and reduce the drop amount of sensor nodes' sensed data. In short,when data transmission delay and hopsare limited,MPSA algorithm outperforms RAND algorithm,GMRE algorithm and EASR algorithm.
出处
《传感技术学报》
CAS
CSCD
北大核心
2016年第4期583-592,共10页
Chinese Journal of Sensors and Actuators
基金
浙江省自然科学基金项目(LY14F030006
LY15F030004)
国家自然科学基金项目(61501403)
浙江省公益性技术应用研究计划项目(2015C33028)
浙江省教育厅项目(Y201432498)
关键词
移动无线传感网
路径选择
虚拟力
数据传输时延
数据传输跳数
mobile wireless sensor networks
path selection
virtual force
data transmission delay
data transmission hop