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Distributed algorithms for lifetime maximization in sensor networks via Min–Max spanning subgraphs

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Abstract

We consider the problem of static transmission-power assignment for lifetime maximization of a wireless sensor network with stationary nodes operating in a data-gathering scenario. Using a graph-theoretic approach, we propose two distributed algorithms, MLS and BSpan, that construct spanning trees with minimum maximum (minmax) edge cost. MLS is based on computation of minmax-cost paths from a reference node, while BSpan performs a binary search over the range of power levels and exploits the wireless broadcast advantage. We also present a simple distributed method for pruning a graph to its Relative Neighborhood Graph, which reduces the worst-case message complexity of MLS under natural assumptions on the path-loss. In our network simulations both MLS and BSpan significantly outperform the recently proposed Distributed Min–Max Tree algorithm in terms of number of messages required.

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Acknowledgements

A. Schumacher has been supported by the Helsinki Graduate School of Computer Science and Engineering. The MLS and BSpan simulations were conducted in collaboration with Thorn Thaler.

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Authors and Affiliations

  1. Department of Information and Computer Science, Helsinki University of Technology TKK, Helsinki, Finland

    Harri Haanpää, André Schumacher & Pekka Orponen

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  1. Harri Haanpää
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  2. André Schumacher
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  3. Pekka Orponen
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Correspondence to André Schumacher.

Additional information

Preliminary work has been reported in the Third International Conference on Mobile Ad-hoc and Sensor Networks (MSN), Beijing, China, December 12–14, 2007 and the Fifth European Conference on Wireless Sensor Networks (EWSN), Bologna, Italy, January 30–February 1, 2008.

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Haanpää, H., Schumacher, A. & Orponen, P. Distributed algorithms for lifetime maximization in sensor networks via Min–Max spanning subgraphs. Wireless Netw 16, 875–887 (2010). https://doi.org/10.1007/s11276-009-0174-1

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