一种从密集传感器网络中识别冗余传感器节点的分析框架

K. Sakib, Z. Tari, P. Bertók
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引用次数: 10

摘要

冗余节点的部署会影响网络的生命周期,因为冗余节点会执行不必要的重复任务,消耗多余的能量。为了消除冗余任务,提出了一种分布式节点冗余识别方法——自计算冗余校验(SCRC)。在场地上假设一个网格,通过检查其感知区域的覆盖程度,帮助每个节点计算自己的冗余。这将优化活动节点集,同时提供完整的网络覆盖和连接。利用期望值优化技术,提出了SCRC的分析框架。该框架用于预测各种节点分布下的潜在冗余节点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An analytical framework for identifying redundant sensor nodes from a dense sensor network
Redundant node deployment has an impact on network lifetime because redundant nodes consume excess energy by performing unnecessary repetitious tasks. A distributed node redundancy identification method, called Self-Calculated Redundancy Check (SCRC), is proposed to eliminate redundant tasks. A grid is assumed over the field to help each node to calculate its own redundancy by checking the coverage degree of its sensing region. This optimises the active node set while providing complete network coverage and connectivity. An analytical framework is presented for SCRC using the expected value optimisation technique. The framework is used to predict potentially redundant nodes under various node distributions.
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