TEEN: ARouting Protocol for Enhanced Efficiency in Wireless Sensor Networks
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
BROADNETS '04 Proceedings of the First International Conference on Broadband Networks
A Minimum Cost Heterogeneous Sensor Network with a Lifetime Constraint
IEEE Transactions on Mobile Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 12 - Volume 13
An Energy-Efficient Voting-Based Clustering Algorithm for Sensor Networks
SNPD-SAWN '05 Proceedings of the Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Networks
A Configurable Time-Controlled Clustering Algorithm for Wireless Sensor Networks
ICPADS '05 Proceedings of the 11th International Conference on Parallel and Distributed Systems - Workshops - Volume 02
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
A clustering algorithm for wireless sensor networks based on density of sensors
Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia
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Wireless nodes in sensor network detect surrounding events and then deliver the sensed information to a base station. Organizing these sensors into clusters enables efficient utilization of the limited network resources. Many clustering algorithms have been proposed such as LEACH, HEED, GAF and so on. While LEACH has many excellent features such as highly adaptive, self-configuring cluster formation, application-specific data aggregation, etc., it does not scale well when the network size or coverage increases. In this paper, the Enhanced Multihop Clustering Algorithm (EMCA) is proposed which utilizes multihop links for both intra-cluster and inter-cluster communication. To model the energy consumption more accurately, each cluster is modeled as a Voronoi Cell instead of a circle. The optimal parameter values are determined to minimize the total energy consumption so as to prolonging the lifetime of the whole network. Numerical results show that when both LEACH and EMCA operate with optimal parameter values, the total energy consumption of EMCA is much smaller than that of LEACH. Moreover, EMCA scales much well when the network scale increases, which proves that EMCA is highly scalable and is especially suitable for relatively large-scale wireless sensor networks.