Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy-efficient collision-free medium access control for wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks
IEEE Transactions on Mobile Computing
Scheduling sleeping nodes in high density cluster-based sensor networks
Mobile Networks and Applications
Wireless sensor network localization techniques
Computer Networks: The International Journal of Computer and Telecommunications Networking
A survey on clustering algorithms for wireless sensor networks
Computer Communications
Layered Diffusion-based Coverage Control in Wireless Sensor Networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
IEEE Transactions on Mobile Computing
Balanced-energy sleep scheduling scheme for high-density cluster-based sensor networks
Computer Communications
Coverage-aware sleep scheduling for cluster-based sensor networks
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Coverage Control in Sensor Networks
Coverage Control in Sensor Networks
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
Coverage-Preserving Routing Protocols for Randomly Distributed Wireless Sensor Networks
IEEE Transactions on Wireless Communications
Journal of Network and Computer Applications
A density-barrier construction algorithm with minimum total movement in mobile WSNs
Computer Networks: The International Journal of Computer and Telecommunications Networking
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In energy-limited wireless sensor networks, network clustering and sensor scheduling are two efficient techniques for minimizing node energy consumption and maximizing network coverage lifetime. When integrating the two techniques, the challenges include how to decide the most energy-efficient cluster size and how to select cluster heads and active nodes. In this paper, we provide a computation method for the optimal cluster size to minimize the average energy consumption rate per unit area. In the proposed coverage-aware clustering protocol, we define a cost metric that favors those nodes being more energy-redundantly covered as better candidates for cluster heads and select active nodes in a way that tries to emulate the most efficient tessellation for area coverage. Our simulation results validate our computation and show the significant improvement of the network coverage lifetime.