Protocols and Architectures for Wireless Sensor Networks
Protocols and Architectures for Wireless Sensor Networks
The DISCO network calculator: a toolbox for worst case analysis
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
A Comprehensive Worst-Case Calculus for Wireless Sensor Networks with In-Network Processing
RTSS '07 Proceedings of the 28th IEEE International Real-Time Systems Symposium
Network calculus: a theory of deterministic queuing systems for the internet
Network calculus: a theory of deterministic queuing systems for the internet
Sensor network calculus – a framework for worst case analysis
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Optimal multi-sink positioning and energy-efficient routing in wireless sensor networks
ICOIN'05 Proceedings of the 2005 international conference on Information Networking: convergence in broadband and mobile networking
Survey of clustering algorithms
IEEE Transactions on Neural Networks
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Wireless Sensor Networks (WSN) comprise a large number of sensor nodes that possess scarce energy supplies. To minimize energy consumption and to consequently extend the lifetime of WSNs, we propose a local search technique for sink placement in WSNs. In addition, a proper sink placement plays a vital role in performance-sensitive WSN applications. Since it is not feasible for a sink to use global information, especially for large-scale WSNs, we introduce a self-organized sink placement (SOSP) strategy that combines the advantages of our previous works [7] and [8]. Besides, this paper is a substantial extension of [9]. The goal of this research is to provide a better sink placement strategy with a lower communication overhead. Avoiding the costly design of using the nodes' location information, each sink sets up its own group by communicating to its n-hop distance neighbors. While keeping the locally optimal placement, SOSP exhibits a better solution quality with respect to communication overhead and computational effort than previous solutions. To analyze performance issues, especially the worst-case delay of a given WSN, we use a methodology called sensor network calculus [10].