Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Data Gathering in SEnsor Networks using the Energy Delay Metric
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Lightweight sensing and communication protocols for target enumeration and aggregation
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Application-specific protocol architectures for wireless networks
Application-specific protocol architectures for wireless networks
An analysis of a large scale habitat monitoring application
SenSys '04 Proceedings of the 2nd 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
Scalable data aggregation for dynamic events in sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Energy-efficient coverage problems in wireless ad-hoc sensor networks
Computer Communications
IEEE Communications Magazine
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A large number of sensors are usually deployed around some discrete targets in wireless sensor networks for target surveillance purpose. In such networks, clustering is beneficial not only to network management and data aggregation, but also to the target coverage issues. This paper builds a target coverage relation model for target surveillance networks. Based on this model, we abstract the clustering as finding the minimum K-hop dominating set which is proved to be NP complete. Then, we propose a distributed energy-efficient target-oriented clustering protocol (EETO). EETO partitions the network into multiple connected sub-branches based on the corresponding target-oriented relation graph. Each sub-branch is a cluster, where the cluster members are all the K-hop coverage neighbors of the cluster head. EETO groups the sensors which cover the same target set into one cluster. Therefore, related data can be aggregated timely and completely at the cluster head. The message overhead of EETO is only O(1), which is scalable. Detailed simulation results show that EETO reduces energy consumption, improves load balancing and prolongs the coverage lifetime of the network.