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On Optimal Clustering in Mobile Wireless Sensor Networks Under Uncertainty

机译:不确定条件下移动无线传感器网络的最优聚类研究

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摘要

Wireless sensor networks are comprised of geographically distributed sensors that collect and convey time-critical information without human intervention, making them particularly useful for military applications; however, network performance may be limited by the typically small energy supplies of the sensors. One strategy for dealing with limited energy storage in such networks is to allow sensor nodes to aggregate sensed data at particular nodes known as cluster heads. We examine the problem of optimally locating and relocating cluster heads over a finite time horizon. The objective is to simultaneously maximize the demand coverage and minimize the costs of relocating cluster heads. Our main contribution is to consider explicitly the random evolution of mobile sensor nodes, which requires periodic updating of their precise locations. Computational experiments illustrate the usefulness of such dynamic information updates to help mitigate the uncertainty in sensor node locations and ensure reliable demand coverage by cluster heads.
机译:无线传感器网络由分布在地理位置上的传感器组成,这些传感器无需人工干预即可收集和传达对时间要求严格的信息,这使其特别适用于军事应用;但是,网络性能可能会受到传感器通常较小的能量供应的限制。处理这种网络中有限的能量存储的一种策略是允许传感器节点在被称为簇头的特定节点上聚合感测到的数据。我们研究了在有限的时间范围内最佳定位和重新定位簇头的问题。目标是同时最大程度地扩大需求范围并最大程度地减少重新安置群集头的成本。我们的主要贡献是明确考虑移动传感器节点的随机演化,这需要定期更新其精确位置。计算实验说明了这种动态信息更新的有用性,以帮助减轻传感器节点位置的不确定性并确保簇头可靠地满足需求。

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