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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Multi-agent Learning and Control System Using Ants Colony for Packet Scheduling in Routers
verfasst von : Malika Bourenane, Djilali Benhamamouch, Abdelhamid Mellouk
Erschienen in: Managing Next Generation Networks and Services
Verlag: Springer Berlin Heidelberg
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This paper describes a novel method of achieving packet scheduling in several routers of network, in order to optimize the end to end delay. We use a multi-agent system to model this problem, where each agent of this system tries to optimize the local scheduling and through a communication with each other, attempts to make global coordination in order to optimize the total scheduling. The communication between agents is done by mobile agents like ants colony. A pheromone-Q learning approach is presented in this paper, which consists to applying the standard Q-learning technique adapted to our architecture with a synthetic pheromone that acts as a communication medium speeding up the learning process of cooperating agents.