Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
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
Differentiated surveillance for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Fault Tolerance in Collaborative Sensor Networks for Target Detection
IEEE Transactions on Computers
Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems
Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems
Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms
Proceedings of the 3rd international symposium on Information processing in sensor networks
On deriving the upper bound of α-lifetime for large sensor networks
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
Energy-efficient surveillance system using wireless sensor networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
On k-coverage in a mostly sleeping sensor network
Proceedings of the 10th annual international conference on Mobile computing and networking
Integrated coverage and connectivity configuration for energy conservation in sensor networks
ACM Transactions on Sensor Networks (TOSN)
The coverage problem in a wireless sensor network
Mobile Networks and Applications
Percentage coverage configuration in wireless sensor networks
ISPA'05 Proceedings of the Third international conference on Parallel and Distributed Processing and Applications
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Wireless sensor networks are employed in many critical applications. The K-coverage configuration is usually adopted to guarantee the quality of surveillance. A sensor node can be determined to be ineligible to stay active when its sensing range is K-covered. Although many algorithms have been proposed to reduce the complexity of the K-coverage configuration, the accuracy cannot be preserved when the number of deployed sensor nodes increases. In this paper, we propose an efficient K-coverage eligibility (EKE) algorithm to accurately and cheaply determine the eligibility of each sensor node. The algorithm focuses on the regions having a lower degree of coverage for each sensor node. Therefore, the complexity of the EKE algorithm is reduced substantially while retaining accuracy. Experimental studies indicated that the computational cost of the EKE algorithm could be reduced by up to 89% and that the correct percentage was larger than 90%.