Low power signal processing architectures for network microsensors
ISLPED '97 Proceedings of the 1997 international symposium on Low power electronics and design
Next century challenges: scalable coordination in sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
PEAS: A Robust Energy Conserving Protocol for Long-lived Sensor Networks
ICNP '02 Proceedings of the 10th IEEE International Conference on Network Protocols
HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks
IEEE Transactions on Mobile Computing
Cluster-Head Election Using Fuzzy Logic for Wireless Sensor Networks
CNSR '05 Proceedings of the 3rd Annual Communication Networks and Services Research Conference
Energy Adaptive Cluster-Head Selection for Wireless Sensor Networks
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
Adaptive clustering for mobile wireless networks
IEEE Journal on Selected Areas in Communications
Computer Networks: The International Journal of Computer and Telecommunications Networking
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One of the main challenges in wireless sensor networks is to obtain long system lifetime. We propose an algorithm for electing the cluster head node based on the maximum residual energy for the purpose of even distribution of energy consumption in the overall network and obtaining the longest network lifetime. To maintain the original performance of the network, the lifetime is suggested to be expressed as to both the maximum last node dying time and the minimum time difference between the last node dying and the first node dying. The key parameter — the electing coefficient (θ) was obtained and evaluated. The optimal θ value is related to number of nodes, energy consumption of cluster members (ECCM), and energy consumption of the cluster head (ECCH). θ descends when number of nodes and ECCM decrease, and when ECCH increases. However, when energy consumptions of the cluster head and cluster members change proportionally, θ seems to be affected slightly. Results show that network lifetime can be prolonged when cluster heads are elected with the optimal θ value.