Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
A coverage-preserving node scheduling scheme for large wireless sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Connected sensor cover: self-organization of sensor networks for efficient query execution
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
PEAS: A Robust Energy Conserving Protocol for Long-lived Sensor Networks
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Differentiated surveillance for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
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In this paper, we consider the connected coverage problem and aim to construct a minimal connected cover set that is sufficient for a given query in wireless sensor networks. We propose a centralized, Voronoi tessellation (CVT) based algorithm to select the minimum number of active sensor nodes needed to cover the target region completely. The constructed sensor set proves to be connected when sensor node’s communication range is at least twice of its sensing range. For other situations where the CVT algorithm alone cannot guarantee the network connectivity, we design a Steiner minimum tree (SMT) based algorithm to ensure the network connectivity. Theoretical analysis and simulation results show that our algorithm outperforms the greedy algorithm in terms of both the time complexity and the needed number of sensor nodes that must be kept active to respond to a given query.