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An Improved DV-Hop Scheme Based on Path Matching and Particle Swarm Optimization Algorithm

机译:一种基于路径匹配和粒子群优化算法的改进的DV跳方案

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摘要

Distance vector hop (DV-Hop) is a frequently-used localization technology for wireless sensor networks. The traditional DV-Hop scheme estimates the node-anchor distance depending on the hop-count between the network nodes. It is the advantage of the scheme because no costive direct range finding is needed, but it still is the disadvantage of the scheme because the heterogeneity of network topology will make the node-anchor distance estimation precision poor and the localization precision unstable. Since the heterogeneity of network topology is very common due to random node deployment in real applications, the effectiveness of DV-Hop scheme in these applications becomes difficult to confirm and the algorithm needs applicability improvement. Focusing on above problem of the traditional DV-Hop, improved strategies are provided.A path matching algorithm is presented to find out the optimal anchor-anchor shortest path, which is used to determine the average hop distance between anunknown node and its target anchor independently, aiming at making the estimated node-anchor distance as close as possible to the real distance; furtherly, a modified particle swarm optimization algorithm is presented to optimize the initial position of each unknown node, aiming at improving the whole node localization accuracy of the network. Simulations are carried out on different network topologies both in square area and in C-shaped area, and comparisonsaremade for our scheme with the traditional DV-Hop and the other three existed representative improved schemes. Results show that our scheme has better performance both on distance estimation accuracy and on average nodelocalization accuracy.
机译:距离矢量跳(DV-Hop)是无线传感器网络的常用本地化技术。传统的DV-Hop方案根据网络节点之间的跳数估计节点锚距离。这是该方案的优点,因为不需要耐久的直接范围发现,但它仍然是该方案的缺点,因为网络拓扑的异质性将使节点锚距离估计精度差和定位精度不稳定。由于网络拓扑的异质性由于实际应用中随机节点部署而非常普遍,因此在这些应用中的DV-Hop方案的有效性变得难以确认,并且算法需要改进。专注于上述传统DV跳的问题,提供了改进的策略。提出了路径匹配算法以找出最佳锚定锚最短路径,用于确定AnunkNown节点和其目标锚的平均跳距,旨在使估计的节点锚距离尽可能接近实际距离;此外,提出了一种修改的粒子群优化优化算法以优化每个未知节点的初始位置,旨在提高网络的整个节点定位精度。在方形区域和C形区域中的不同网络拓扑上进行模拟,以及我们的方案与传统的DV跳和其他三个存在的代表改进方案进行比较。结果表明,我们的方案在距离估计准确度和平均点心精度上具有更好的性能。

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