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A distributed algorithmic framework for coverage problems in wireless sensor networks

机译:无线传感器网络中覆盖问题的分布式算法框架

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One of the key challenges in wireless sensor networks (WSNs) is that of extending the lifetime of the network while meeting some coverage requirements. In this paper, we present a distributed algorithmic framework to enable sensors to determine their sleep-sense cycles based on specific coverage goals. The framework is based on our earlier work on the target coverage problem. We give a general version of the framework that can be used to solve network/graph optimisation problems for which melding compatible neighbouring local solutions directly yields globally feasible solutions such as the maximal independent set problem. We also apply this framework to several variations of the coverage problem, namely, target coverage, area coverage and k-coverage problems, to demonstrate its general applicability. Each sensor constructs minimal cover sets for its local coverage objective. The framework entails each sensor prioritising these local cover sets and then negotiating with its neighbours for satisfying mutual constraints. We employ a dependency graph model that can capture the interdependencies among the cover sets. Detailed simulations are carried out to further demonstrate the resulting performance improvements and effectiveness of the framework. These show an improvement of between 10 and 20% over existing algorithms.
机译:无线传感器网络(WSN)的主要挑战之一是在满足某些覆盖要求的同时延长网络寿命。在本文中,我们提出了一种分布式算法框架,使传感器能够根据特定的覆盖目标确定其睡眠感知周期。该框架基于我们在目标覆盖率问题上的早期工作。我们给出了该框架的通用版本,可用于解决网络/图形优化问题,将兼容的相邻本地解决方案融合在一起直接产生全局可行的解决方案,例如最大独立集问题。我们还将这个框架应用于覆盖问题的几种变体,即目标覆盖,区域覆盖和k覆盖问题,以证明其一般适用性。每个传感器为其本地覆盖目标构建最少的覆盖集。该框架要求每个传感器对这些本地覆盖物集进行优先排序,然后与它的邻居协商以满足相互约束。我们采用了一个依赖图模型,该模型可以捕获封面集之间的相互依赖关系。进行了详细的模拟,以进一步证明所产生的性能改进和框架的有效性。与现有算法相比,这些算法显示出了10%到20%的改进。

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