Abstract
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.
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© 2007 Springer-Verlag Berlin Heidelberg
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Bourenane, M., Benhamamouch, D., Mellouk, A. (2007). Multi-agent Learning and Control System Using Ants Colony for Packet Scheduling in Routers. In: Ata, S., Hong, C.S. (eds) Managing Next Generation Networks and Services. APNOMS 2007. Lecture Notes in Computer Science, vol 4773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75476-3_71
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DOI: https://doi.org/10.1007/978-3-540-75476-3_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75475-6
Online ISBN: 978-3-540-75476-3
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