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Open AccessArticle

Average Consensus over Mobile Wireless Sensor Networks: Weight Matrix Guaranteeing Convergence without Reconfiguration of Edge Weights

1
Institute of Informatics, Slovak Academy of Sciences, Dúbravská Cesta 9, 845 07 Bratislava 45, Slovakia
2
Sipwise GmbH, Europaring F15, 2345 Brunn am Gebirge, Austria
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(13), 3677; https://doi.org/10.3390/s20133677
Received: 19 May 2020 / Revised: 17 June 2020 / Accepted: 27 June 2020 / Published: 30 June 2020
(This article belongs to the Collection Multi-Sensor Information Fusion)
Efficient data aggregation is crucial for mobile wireless sensor networks, as their resources are significantly constrained. Over recent years, the average consensus algorithm has found a wide application in this technology. In this paper, we present a weight matrix simplifying the average consensus algorithm over mobile wireless sensor networks, thereby prolonging the network lifetime as well as ensuring the proper operation of the algorithm. Our contribution results from the theorem stating how the Laplacian spectrum of an undirected simple finite graph changes in the case of adding an arbitrary edge into this graph. We identify that the mixing parameter of Best Constant weights of a complete finite graph with an arbitrary order ensures the convergence in time-varying topologies without any reconfiguration of the edge weights. The presented theorems and lemmas are verified over evolving graphs with various parameters, whereby it is demonstrated that our approach ensures the convergence of the average consensus algorithm over mobile wireless sensor networks in spite of no edge reconfiguration. View Full-Text
Keywords: average consensus; consensus algorithms; data aggregation; distributed algorithms; mobile computing; mobile wireless sensor networks; sensor fusion average consensus; consensus algorithms; data aggregation; distributed algorithms; mobile computing; mobile wireless sensor networks; sensor fusion
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Kenyeres, M.; Kenyeres, J. Average Consensus over Mobile Wireless Sensor Networks: Weight Matrix Guaranteeing Convergence without Reconfiguration of Edge Weights. Sensors 2020, 20, 3677.

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