Distributed Algorithms for Constructing Approximate Minimum Spanning Trees in Wireless Sensor Networks
Issue No. 01 - January (2009 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2008.57
Maleq Khan , Virginia Bioinformatics Institute, Virginia Tech, Blacksburg
Gopal Pandurangan , Purdue University, West Lafayette
V.S. Anil Kumar , Virginia Bioinformatics Institute, Virginia Tech, Blacksburg
While there are distributed algorithms for the MST problem, these algorithms require relatively large number of messages and time; this makes these algorithms impractical for resource-constrained networks such as ad hoc wireless sensor networks. In such networks, a sensor has very limited power, and any algorithm needs to be simple, local, and energy efficient for being practical. Motivated by these considerations, we design and analyze a class of simple and local distributed algorithms called Nearest Neighbor Tree (NNT) algorithms for energy-efficient construction of MSTs in a wireless ad hoc setting. We assume that the nodes are uniformly distributed in a unit square and show provable bounds on the performance with respect to both the quality of the spanning tree produced and the energy needed to construct them. In particular, we show that NNT produces a close approximation to the MST, and they can be maintained dynamically with polylogarithmic number of rearrangements under node insertions/deletions. We also perform extensive simulations of our algorithms. We tested our algorithms on both uniformly random distributions of nodes, and on a realistic distributions of nodes in an urban setting. Simulations validate the theoretical results and show that the bounds are much better in practice.
Distributed Algorthms, Minimum Spanning Tree, Sensor networks, Approximation Algorithms, Probabilistic Analysis
V. Anil Kumar, M. Khan and G. Pandurangan, "Distributed Algorithms for Constructing Approximate Minimum Spanning Trees in Wireless Sensor Networks," in IEEE Transactions on Parallel & Distributed Systems, vol. 20, no. , pp. 124-139, 2008.