无线传感器网络中分布式无坐标边界节点识别

Linna Wei, Yuanxia Shen
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引用次数: 2

摘要

在无线传感器网络(WSN)中,由于传感器随机部署或节点故障,可能会出现覆盖漏洞。它们可能会限制网络为最终用户提供全面和高质量的数据。为了修复覆盖漏洞,网络首先需要对覆盖漏洞进行定位,其主要思想是找到覆盖漏洞上的边界节点。虽然对无线传感器网络中边界节点的识别问题进行了深入的研究,但大多数都是利用传感器的坐标来完成的。然而,由于为传感器配备gps等定位设备的成本相对较高,在低预算网络中往往无法获得坐标。现有的无坐标算法通常在节点密度较高且分布均匀的传感器网络中工作。因此,在一般网络中,如何在没有坐标辅助的情况下完成任务仍然是一个难点。本文提出了一种根据网络的1跳邻居来区分边界节点和内部节点的分布式算法。在我们的方法中,传感器首先发现在它的附近是否有一个哈密顿圆。然后,基于邻域三角剖分技术和无坐标三角点测试技术,对圆的特征进行分析,判断圆的位置是在旁边还是在周围;仿真结果表明,该方法在随机和不均匀传感器部署的网络中,特别是在具有小分散覆盖孔的网络中,能够有效地识别边界节点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Coordinate-free Boundary Nodes Identification in Wireless Sensor Networks
In a wireless sensor network (WSN), coverage holes may appear due to sensor random deployment or node failure. They may restrain the network from providing comprehensive and quality data for end users. In order to heal the coverage holes, the network first needs to localize them and the main idea is to find the boundary nodes on them. Although the problem of identifying the boundary nodes in WSNs has been intensively studied, most of them accomplished the work by using the coordinates of sensors. However, due to the comparatively expansive cost for equipping sensors with localization devices such as GPSs, coordinates are often unavailable in low-budget networks. Existing coordinate-free algorithms often perform their works in evenly distributed sensor networks with relatively high node density. Therefore, how to complete the task without assistance of coordinates still faces difficulties in general networks. In this paper, we present a distributed algorithm to distinguish the boundary nodes from inner ones in a network according to their 1-hop neighbors. In our approach, a sensor first finds out if there is a Hamiltonian circle in the neighborhood of it. Then, it analyzes characteristics of the circle to decide if the circle is located beside or around, based on techniques of neighborhood triangulation and point in triangle test without coordinates. Simulation results show the performance effectiveness of our method in identifying boundary nodes in networks with random and uneven sensor deployment, especially in the ones with small scattered coverage holes.
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