Coverage Hole Detection with Image Analysis and Heuristic for healing

Anandakrishnan U, Greeshma Sarath
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Abstract

Coverage holes in WAN are of significant issue. They reduces impact overall performance of WAN. Early detection of coverage holes in a ROI thus has great significant as it helps to plan a healing strategy. Various detection approaches has been proposed in earlier papers however they are all computationally intensive or require prior knowledge of the sensor location. In this paper we propose a image analysis based hole detection approach. The method has the advantage that it require minimum prior knowedge of the ROI and can be used in non homogenous ROI. The information extracted from the detection is used as heuristic to heal larger holes in ROI quickly. The algorithm has similar performance to existing algorithms as the no of sensors reaches 50 however has a better performance as the sensor count increase beyond 50.
基于图像分析和启发式修复的覆盖孔检测
广域网的覆盖漏洞是一个重要的问题。它们减少了对WAN整体性能的影响。因此,早期发现ROI中的覆盖漏洞非常重要,因为它有助于制定修复策略。在早期的论文中已经提出了各种检测方法,但是它们都是计算密集型的,或者需要事先知道传感器的位置。本文提出了一种基于图像分析的孔检测方法。该方法对感兴趣区域的先验知识要求最小,可用于非同质感兴趣区域。从检测中提取的信息作为启发式算法用于快速修复ROI中较大的漏洞。当传感器数量达到50时,该算法的性能与现有算法相似,但当传感器数量超过50时,该算法的性能会有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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