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Distributed Least Squares Estimation Algorithms Design for Sensor Networks
Wanyu Lin, Jiannong Cao and Xuefeng Liu

Domain-specific applications, such as structural health monitoring, have been one of the main drivers that motivates the real world deployment of wireless sensor networks (WSNs). Due to their data-intensive nature, it is typical for these applications to make heavy uses of least squares estimation (LSE) as a foundation for their algorithms. Due to the very limited amount of energy and computation power available on sensors, it is imperative to design new distributed algorithms to perform LSE. Firstly, we propose a general framework as a basis for designing, analyzing and evaluating distributed LSE in WSNs. Then, based on the framework, we propose E3, a tree-based scheme specifically designed to guarantee the precision of LSE, with the objective of minimizing the energy consumption incurred during communication, while observing constraints on communication delays. Finally, by simulations and real experiments, we show the efficacy of our framework and E3.

Keywords: Distributed algorithms design, least squares estimation, sensor networks, energy consumption, delay

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