Multi-agent-based clustering approach to wireless sensor networks

This paper presents a multi-agent system for hierarchical routing in a Wireless Sensor Network (WSN). The agents communicate and collaborate with each other and benefit from learning techniques, more specifically genetic algorithms. The proposed system consists of four types of agents, including regional, interface, cluster and query agents. The regional agent resides on the base-station and performs genetic algorithm intense computing. The interface agent interacts with the users to fulfil their interests. The cluster agents manage all agents within clusters for query dissemination and efficiency in network. The query agents reside in each sensor and acquire, aggregate, process the useful data, and transmit the desired results. A prototype of all agents is simulated. For a given radio model our test results revealed that our multi-agent-based approach for hierarchical routing not only outperforms other routing protocols such as LEACH, but also determines the set of optimum clusters for various topologies.