Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Foundations of coverage in wireless sensor networks
Foundations of coverage in wireless sensor networks
A randomized distributed algorithm for the maximal independent set problem in growth-bounded graphs
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
High Performance Sleep-Wake Sensor Systems Based on Cyclic Cellular Automata
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Cyclic Cellular Automata: A Tool for Self-Organizing Sleep Scheduling in Sensor Networks
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Self-assembling sweep-and-sleep sensor systems
ACM SIGMETRICS Performance Evaluation Review
Self organizing sensor networks using intelligent clustering
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part IV
A centralized energy-efficient routing protocol for wireless sensor networks
IEEE Communications Magazine
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Wireless sensor networks WSN have emerged in many applications as a platform to collect data and monitor a specified area with minimal human intervention. The initial deployment of WSN sensors forms a network that consists of randomly distributed devices/nodes in a known space. Advancements have been made in low-power micro-electronic circuits, which have allowed WSN to be a feasible platform for many applications. However, there are two major concerns that govern the efficiency, availability, and functionality of the network-power consumption and fault tolerance. This paper introduces a new algorithm called Power Efficient Cluster Algorithm PECA. The proposed algorithm reduces the power consumption required to setup the network. This is accomplished by effectively reducing the total number of radio transmission required in the network setup deployment phase. As a fault tolerance approach, the algorithm stores information about each node for easier recovery of the network should any node fail. The proposed algorithm is compared with the Self Organizing Sensor SOS algorithm; results show that PECA consumes significantly less power than SOS.