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作 者:赵克华 陈友荣[1] 万锦昊 任条娟[1] 王章权[1] 周骏华 ZHAO Kehua;CHEN Yourong;WAN Jinhao;REN Tiaojun;WANG Zhangquan;ZHOU Junhua(College of Information Science and Technology,Zhejiang Shuren University,Hangzhou 310015,China;China Mobile(Hangzhou)Information Technology Co.Ltd.,Hangzhou 311100,China)
机构地区:[1]浙江树人大学信息科技学院,杭州310015 [2]中移(杭州)信息技术有限公司,杭州311100
出 处:《传感技术学报》2019年第12期1895-1903,共9页Chinese Journal of Sensors and Actuators
基 金:浙江省公益技术应用研究项目(LGF19F010006,LGF19F010005,LGG19F010011);国家自然科学基金项目(61501403);浙江省教育厅项目(Y201840757)
摘 要:为克服三维静态无线传感网中的能量空穴问题和提高网络生存时间,考虑Sink节点移动,提出一种Sink节点移动的三维无线传感网数据收集算法(DCA_TWSN)。在DCA_TWSN中,提出三维环境下的正方体网格划分方法,建立包括Sink移动路径选择约束、数据流量约束、能耗约束、链路约束等约束条件的数据收集优化模型。采用最优化方法求解已知Sink节点移动路径的数据收集优化问题,采用修正的蚁群算法求解Sink节点的移动路径问题,获得最优方案。仿真结果表明:不管Sink节点的最大数据收集跳数和传感节点数量如何变化,DCA_TWSN都能寻找到较优的移动路径和数据传输方案,从而提高了网络生存时间和传感节点的平均数据传输率,降低了移动路径长度、平均节点能耗方差和丢包率,比RAND、GREED和EDG_3D更优。To overcome energy hole problem and prolong network lifetime in three-dimensional static wireless sensor network,considering the movement of Sink node,a data collection algorithm of three-dimensional wireless sensor network with mobile Sink node(DCA_TWSN)is proposed.In the DCA_TWSN,a cube network division method in three-dimensional environment is proposed,and the data collection optimization model including Sink node’s moving path selection constraint,data flow constraint,energy constraint and link constraint is established.The optimization method is used to solve the data collection optimization problem with known Sink node’s moving path.The modified ant colony algorithm is used to solve the moving path problem of Sink node,and the optimal solution is obtained.The simulation result shows that DCA_TWSN algorithm can find the optimal moving path of Sink node and optimal data transmission scheme regardless of Sink node’s maximum data collection hop count and the number of sensor nodes.It can improve the network lifetime and the average data transmission rate of sensor node,reduce the length of moving path,average node energy variance and packet loss rat,and is better than RAND,GREED and EDG_3D.
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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