基于最佳距离估计和粒子群优化的无线传感器网络节点定位算法

发布时间：2018-11-23 16:20

【摘要】：无线传感器网络节点定位算法是其应用中的关键基础性技术。无线传感器网络具有节点大规模随机分布、资源有限和应用环境复杂等特点,给兼容性能与功耗的节点定位算法带来了挑战。本文基于非测距定位技术,研究含有空洞的2D/3D无线传感器网络节点定位算法,以扩展无线传感器网络的应用方法。本文主要工作如下:(1)介绍了无线传感器网络定位算法和路由协议的研究现状;对现有节点定位方法进行了分类;分析讨论了典型基于非测距节点定位算法对存在空洞的2D/3D传感器网络的实际应用限制。(2)提出了一种基于链路相关性的覆盖优先和能量均衡机会式泛洪路由算法(CCEP)。基于节点相对覆盖和剩余能量大小作为分配转发节点的顺序,依据链路相关性对转发子集ACK聚合。通过逐个增加转发节点,估算转发节点信息传输预期可靠性,并统计ACK得到实时可靠性,动态比较评判确定出最小转发节点子集与重传次数。仿真实验验证,本算法在满足目标可靠性同时,有效减小了网络通信负载,降低了节点能耗,促进网络节点剩余能量均衡,进而延长了网络生命周期。(3)提出了一种基于最短路径置信度的节点间最佳距离估计算法(ODESPC)。通过识别泛洪路由算法生成的最短路径树中各级子树的网络空洞边缘特殊节点,利用网络连通性和特殊节点,计算出最短路径置信度,提高了节点间距离估计精度。仿真实验结果表明,本算法能对含有空洞的网络节点进行定位估计,提高了网络节点定位覆盖率。(4)提出了一种基于最佳距离估计和粒子群优化的非测距定位算法(PSO-LAODE)。在ODESPC算法的基础上,基于加权平均法进行节点间平均跳距修正,基于改进的粒子群算法对坐标计算的结果进行优化,完成未知节点的定位。仿真实验分析了信标节点数量对算法定位精度的影响,并且将PSO-LAODE算法与典型的DV-Hop算法进行了比较分析。结果表明,PSO-LAODE算法在信标节点较少时也能够达到较高的定位覆盖率和精度。可以适用于含有空洞的较大规模2D/3D无线传感器网络节点定位应用。
[Abstract]:Node location algorithm in wireless sensor networks is the key basic technology in its application. Wireless sensor networks (WSN) are characterized by large scale random distribution of nodes, limited resources and complex application environments, which bring challenges to node localization algorithms with compatible performance and power consumption. Based on the non-ranging localization technology, this paper studies the node localization algorithm of 2D/3D wireless sensor networks with holes in order to extend the application method of wireless sensor networks. The main work of this paper is as follows: (1) the research status of wireless sensor network localization algorithms and routing protocols is introduced, and the existing node location methods are classified. This paper analyzes and discusses the practical application limitation of typical location algorithm based on non-ranging nodes to 2D/3D sensor networks with holes. (2) A coverage priority and energy balance opportunistic flooding based on link correlation is proposed. Routing algorithm (CCEP). Based on the relative coverage of the nodes and the residual energy as the order of allocating the forwarding nodes, the ACK of the forwarding subset is aggregated according to the link correlation. By increasing the forwarding nodes one by one, the expected reliability of the forwarding node information transmission is estimated, and the real-time reliability is obtained by statistical ACK. The minimal subset of forwarding nodes and the number of retransmissions are determined by dynamic comparison and evaluation. Simulation results show that the proposed algorithm can effectively reduce the network communication load, reduce the energy consumption of the nodes and promote the balance of the residual energy of the network nodes at the same time that the reliability of the target is satisfied. Furthermore, the network life cycle is prolonged. (3) an optimal distance estimation algorithm (ODESPC).) based on the shortest path confidence is proposed. By identifying the special nodes in the subtree of the shortest path tree generated by the flooding routing algorithm, the network connectivity and special nodes are used to calculate the confidence of the shortest path, and the accuracy of the distance estimation between nodes is improved. The simulation results show that the algorithm can estimate the location of network nodes with holes. The network node location coverage is improved. (4) A non-ranging localization algorithm (PSO-LAODE) based on optimal range estimation and particle swarm optimization is proposed. On the basis of ODESPC algorithm, the average hopping distance between nodes is modified based on weighted average method, and the results of coordinate calculation are optimized based on improved particle swarm optimization algorithm to locate unknown nodes. The effect of the number of beacon nodes on the localization accuracy of the algorithm is analyzed by simulation, and the PSO-LAODE algorithm is compared with the typical DV-Hop algorithm. The results show that the PSO-LAODE algorithm can achieve high localization coverage and accuracy when there are fewer beacon nodes. It can be used in large scale 2D/3D wireless sensor network node localization applications with holes.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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