Geography-informed energy conservation for Ad Hoc routing
Proceedings of the 7th annual international conference on Mobile computing and networking
Proceedings of the 7th annual international conference on Mobile computing and networking
Exposure in wireless Ad-Hoc sensor networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks
IEEE Transactions on Computers
Optimal Mutation Rates in Genetic Search
Proceedings of the 5th International Conference on Genetic Algorithms
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
PEAS: A Robust Energy Conserving Protocol for Long-lived Sensor Networks
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Integrated coverage and connectivity configuration in wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
IEEE Communications Magazine
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To extend the lifetime of the sensor networks as far as possible while maintaining the quality of network coverage is a major concern in the research of coverage control. A systematical analysis on the relationship between the network lifetime and cover sets alternation is given, and by introducing the concept of time weight factor, the network lifetime maximization model is presented. Through the introduction of the solution granularity T, the network lifetime optimization problem is transformed into the maximization of cover sets. A solution based on NSGA-II is proposed. Compared with the previous method, which has the additional requirement that the cover sets being disjoint and results in a large number of unused nodes, our algorithm allows the sensors to participate in multiple cover sets, and thus makes fuller use of the whole sensor nodes to further increase the network lifetime. Simulation results are presented to verify these approaches.