Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
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
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
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
Integrated coverage and connectivity configuration in wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Differentiated surveillance for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Set k-cover algorithms for energy efficient monitoring in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Sensor networks: a bridge to the physical world
Wireless sensor networks
Towards optimal sleep scheduling in sensor networks for rare-event detection
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
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In this paper, we have done thorough mathematical analysis and extensive simulations on the distributed, lightweight and location-free node scheduling scheme proposed in [11]. The basic idea of this scheduling scheme is to organize sensor nodes into disjoint node sets, which work alternately to extend network lifetime effectively. Distinguished from the work in [11], we reevaluate the performance of this scheduling scheme under different assumption that sensor nodes are deployed randomly in the target region according to a Poisson point process, which is a more realistic deployment model in large scale randomly deployed sensor networks. We also analyze the performance in terms of average event detection latency, which is another straightforward coverage quality measure. Our analysis results reveal the relationship among coverage quality, expected network lifetime and node deployment intensity. Impact of normally distributed time asynchrony on network coverage quality is also investigated.