Parallel and Distributed Computation: Numerical Methods
Parallel and Distributed Computation: Numerical Methods
Synchronous distributed load balancing on dynamic networks
Journal of Parallel and Distributed Computing - Special issue: Design and performance of networks for super-, cluster-, and grid-computing: Part II
A scheme for robust distributed sensor fusion based on average consensus
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Distributed computation of averages over ad hoc networks
IEEE Journal on Selected Areas in Communications
Self-stabilizing consensus average algorithm in distributed sensor networks
Transactions on Large-Scale Data- and Knowledge-centered systems IX
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In sensor networks, sensor nodes are usually deployed randomly over an area to collect the information of interest. Data fusion is the phase of processing the collected information by sensor nodes before they are sent to the end user. This paper introduces a distributed consensus algorithm that allows the nodes of a sensor network to track the average of n sensor measurements. The study of the above mentioned algorithm showed that it is robust to asynchronism and dynamic topology changes. It is also put in evidence that the algorithm is fully distributed and does not require any global coordination. Moreover, The proposed method doesn't involve explicit point-to-point message or routing, it diffuses information across the network. Accordingly, simulation results are provided illustrating the effectiveness of the studied algorithm.