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Network Lifetime Maximization for Estimation in Multihop Wireless Sensor Networks

机译:多跳无线传感器网络中用于估计的网络寿命最大化

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摘要

We consider the distributed estimation by a network consisting of a fusion center and a set of sensor nodes, where the goal is to maximize the network lifetime, defined as the estimation task cycles accomplished before the network becomes nonfunctional. In energy-limited wireless sensor networks, both local quantization and multihop transmission are essential to save transmission energy and thus prolong the network lifetime. The network lifetime optimization problem includes three components: i) optimizing source coding at each sensor node, ii) optimizing source throughput of each sensor node, and iii) optimizing multihop routing path. Fortunately, source coding optimization can be decoupled from source throughput and multihop routing path optimization, and is solved by introducing a concept of equivalent 1-bit MSE function. Based on the optimal source coding, the source throughput and multihop routing path optimization is formulated as a linear programming (LP) problem, which suggests a new notion of character-based routing. The proposed algorithm is optimal and the simulation results show that a significant gain is achieved by the proposed algorithm compared with heuristic methods.
机译:我们考虑由融合中心和一组传感器节点组成的网络的分布式估计,其目标是最大化网络寿命,定义为在网络无法正常工作之前完成的估计任务周期。在能量有限的无线传感器网络中,本地量化和多跳传输对于节省传输能量并延长网络寿命至关重要。网络寿命优化问题包括三个组成部分:i) 优化每个传感器节点的源编码,ii) 优化每个传感器节点的源吞吐量,以及 iii) 优化多跳路由路径。幸运的是,源编码优化可以与源吞吐量和多跳路由路径优化解耦,并通过引入等效 1 位 MSE 函数的概念来解决。基于最优源编码,将源吞吐量和多跳路由路径优化表述为线性规划(LP)问题,提出了基于字符的路由的新概念。所提算法最优,仿真结果表明,与启发式方法相比,所提算法取得了显著的增益。

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