On calculating connected dominating set for efficient routing in ad hoc wireless networks
DIALM '99 Proceedings of the 3rd international workshop on Discrete algorithms and methods for mobile computing and communications
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
On k-coverage in a mostly sleeping sensor network
Proceedings of the 10th annual international conference on Mobile computing and networking
DEEPS: Deterministic Energy-Efficient Protocol for Sensor networks
SNPD-SAWN '06 Proceedings of the Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
IEEE Communications Magazine
A distributed algorithmic framework for coverage problems in wireless sensor networks
International Journal of Parallel, Emergent and Distributed Systems - Advances in Parallel and Distributed Computational Models
HiPC'08 Proceedings of the 15th international conference on High performance computing
Mini-sink mobility with diversity-based routing in wireless sensor networks
Proceedings of the 8th ACM Symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
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We present a new set of distributed algorithms for scheduling sensors to enhance the total lifetime of a wireless sensor network. These algorithms are based on constructing minimal cover sets each consisting of one or more sensors which can collectively cover the local targets. Some of the covers are heuristically better than others for a sensor trying to decide its own sense-sleep status. This leads to various ways to assign priorities to the covers. The algorithms work by having each sensor transition through these possible prioritized cover sets, settling for the best cover it can negotiate with its neighbors. A local lifetime dependency graph consisting of the cover sets as nodes with any two nodes connected if the corresponding covers intersect captures the interdependencies among the covers. We present several variations of the basic algorithmic framework. The priority function of a cover is derived from its degree or connectedness in the dependency graph - usually lower the better. Lifetime improvement is 10% to 20% over the existing algorithms, while maintaining comparable communication overheads. We also show how previous algorithms can be formulated within our framework.