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This paper focuses on estimating the maximum of the initial measures in a Wireless Sensor Network. Two different algorithms are studied : the random gossip, relying on pair-wise exchanges between the nodes, and the broadcast in which each sensor sends its value to all its neighbors; both are asynchronous and distributed. The authors prove the convergence of these algorithms and provide tight bounds for their convergence speed. Distributed estimation algorithms over Wireless Sensors Networks (WSN) have been widely studied since the seminal work of Tsitsiklis.
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