Dynamic fine-grained localization in Ad-Hoc networks of sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
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
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
An adaptive energy-efficient MAC protocol for wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Wakeup scheduling in wireless sensor networks
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Adaptive regression algorithm for distributed dynamic clustering in wireless sensor networks
WD'09 Proceedings of the 2nd IFIP conference on Wireless days
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The coverage problem in sensor networks studies how to turn redundant sensors off while maintaining a required level of coverage. The existing algorithms and protocols are proven to be effective to conserve energy and prolong network lifetime, but only support a static level of sensing coverage. In contrast, many sensor network applications may require a dynamic level of coverage, which changes from area to area and from time to time. To this end, new algorithms must be designed. In this paper, we propose to adapt the sensing scheduling of sensor nodes to the dynamic level of coverage. In the proposed scheme, the lifetime of a sensor node is divided into epochs. At each epoch, the base station computes a minimum set of active nodes based on the current level of coverage requirement. Each sensor samples the field only if it is determined by the base station to sense. The problem of selecting a minimum set of active sensor nodes for a required level of sensing coverage is formulated as an integer programming problem and a heuristic algorithm is proposed. The algorithm is shown to have an approximation factor close to 2 ln n. The scheme eliminates redundant sensing by adapting the sensing scheduling to the dynamic sensing coverage requirement at each epoch. The simulation results show that the proposed scheme can extend the network lifetime significantly, in comparison with existing schemes for static sensing scheduling when the coverage load is low on the field.