Ant algorithms for discrete optimization
Artificial Life
Data Gathering Algorithms in Sensor Networks Using Energy Metrics
IEEE Transactions on Parallel and Distributed Systems
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Ant Colony Optimization
Ant colony optimization theory: a survey
Theoretical Computer Science
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Journal of Network and Computer Applications
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Energy supply in wireless sensor networks (WSNs) is limited and non-replenishable, and energy efficiency is the most important feature in designing these networks. One way to reduce the energy consumption of WSNs and hence prolong the lifespan of these networks is to use adaptive clustering algorithms. In this paper, we use Ant Colony Optimization for Clustering (ACO-C) to propose a new energy aware clustering protocol for WSNs. By using appropriate cost functions, implemented at the base station, our algorithm minimizes and distributes the cost of long distance transmissions and data aggregating among all sensor nodes evenly. Simulation results show the effectiveness of our protocol over other well known clustering algorithms in terms of both network lifetime and data delivery to the base station.