Task coalition formation and self-adjustment in the wireless sensor networks.

SUMMARY Coalition is an essential mechanism in the multi-agent systems in the research of task-oriented area. Self-interested agents coordinate their behaviors in a coalition to pursue a common goal and obtain payoffs. We propose the clustering-based coalition formation and self-adjustment mechanisms for tasks in the wireless sensor network. Before coalition formation, the management center clusters attributes of sensors to reduce the scale of searching space during coalition formation. And then an improved MAX-MIN ant colony optimization algorithm is adopted to resolve the problem of coalition formation. If a coalition member fails to fulfill a task, it can sponsor a negotiation with some noncoalition nodes to execute coalition self-repairing autonomously. The stimulus-response mechanism of wasp colony is introduced to determine the probability of response to the task invitation to avoid consuming extra energy. Simulation results show that our model efficiently reduces energy consumption and network traffic, decreases the number of dead nodes, and prolongs the lifetime of the networks. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]