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A Lightweight Alternating Direction Method of Multipliers for Decentralized Event Detection

机译：分散事件检测乘法器的轻量级交替方向方法

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摘要

In this paper we address the problem of decentralized event detection in a large-scale wireless sensor network (WSN). Comparing with existing centralized solutions, decentralized algorithms are superior in energy efficiency and network scalability, and thus fit for the distributed nature of a WSN. We formulate the event detection problem as a linear program, and solve it with the alternating direction method of multipliers (ADMM). Under mild conditions, this iterative algorithm is shown to be fully decentralized. Further, in view of the fact that the communication burden per iteration directly decides the energy consumption of sensor nodes, we simplify the classic ADMM to a lightweight one, which requires much lower communication burden while keeps the global convergence of the classic ADMM. Effectiveness of the proposed algorithm is validated with simulation results.
机译：在本文中，我们解决了大规模无线传感器网络（WSN）中分散事件检测的问题。与现有的集中解决方案相比，分散算法的能效和网络可伸缩性优异，因此适用于WSN的分布性质。我们将事件检测问题标记为线性程序，并以乘法器（ADMM）的交替方向方法解决。在温和条件下，该迭代算法显示出完全分散。此外，鉴于迭代的沟通负担直接决定传感器节点的能量消耗，我们将经典的ADMM简化为轻量级，这需要更低的通信负担，同时保持经典ADMM的全局融合。建议算法的有效性验证了仿真结果。

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