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ABSTRACT
Wireless sensor networks are tightly associated with the underlying environment in which the sensors are deployed. The global topology of the network is of great importance to both sensor network applications and the implementation of networking functionalities. In this paper we study the problem of topology discovery, in particular, identifying boundaries in a sensor network. Suppose a large number of sensor nodes are scattered in a geometric region, with nearby nodes communicating with each other directly. Our goal is to find the boundary nodes by using only connectivity information. We do not assume any knowledge of the node locations or inter-distances, nor do we enforce that the communication graph follows the unit disk graph model. We propose a simple, distributed algorithm that correctly detects nodes on the boundaries and connects them into meaningful boundary cycles. We obtain as a byproduct the medial axis of the sensor field, which has applications in creating virtual coordinates for routing. We show by extensive simulation that the algorithm gives good results even for networks with low density. We also prove rigorously the correctness of the algorithm for continuous geometric domains.
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Jie Gao , Leonidas Guibas , Nikola Milosavljevic , John Hershberger, Sparse data aggregation in sensor networks, Proceedings of the 6th international conference on Information processing in sensor networks, April 25-27, 2007, Cambridge, Massachusetts, USA
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Jie Gao , Leonidas J. Guibas , Steve Y. Oudot , Yue Wang, Geodesic Delaunay triangulation and witness complex in the plane, Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms, p.571-580, January 20-22, 2008, San Francisco, California
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