Feng Li, Jun Luo, Shiqing Xin, Wenping Wang, Ying He
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引用次数: 23
摘要
尽管密集无线传感器网络(WSNs)的k-area覆盖问题已经得到了深入的研究,但如何在相对稀疏的WSNs中获得优化某些目标的k-coverage传感器部署仍然面临着理论和实践上的困难。在本文中,我们提出了一种实用的LAACAD (Load balancing k-Area Coverage through Autonomous Deployment)算法,将传感器节点移动到k-Area覆盖范围,旨在使节点所需的最大感知距离最小化。LAACAD支持纯粹自主的节点部署,因为它只需要本地化的计算。我们证明了算法的收敛性,以及输出的(局部)最优性。我们还表明,我们的优化目标与其他经常考虑的目标密切相关。因此,我们的实际算法设计也有助于从理论上理解k-area覆盖问题。最后,我们使用广泛的仿真结果来证实我们的理论主张并证明LAACAD的有效性。
LAACAD: Load Balancing k-Area Coverage through Autonomous Deployment in Wireless Sensor Networks
Although the problem of k-area coverage has been intensively investigated for dense wireless sensor networks (WSNs), how to arrive at a k-coverage sensor deployment that optimizes certain objectives in relatively sparse WSNs still faces both theoretical and practical difficulties. In this paper, we present a practical algorithm LAACAD (Load balancing k-Area Coverage through Autonomous Deployment) to move sensor nodes toward k-area coverage, aiming at minimizing the maximum sensing range required by the nodes. LAACAD enables purely autonomous node deployment as it only entails localized computations. We prove the convergence of the algorithm, as well as the (local) optimality of the output. We also show that our optimization objective is closely related to other frequently considered objectives. Therefore, our practical algorithm design also contributes to the theoretical understanding of the k-area coverage problem. Finally, we use extensive simulation results both to confirm our theoretical claims and to demonstrate the efficacy of LAACAD.