A Reinforcement Learning Scheme for Adaptive Link Allocation in ATM Networks

نویسندگان

  • Ernst Nordström
  • Jakob Carlström
چکیده

This paper presents an adaptive scheme for a sub-function in Asynchronous Transfer Mode (ATM) network routing, called link allocation. The scheme adapts the link allocation policy to the offered Poisson call traffic such that the long-term revenue in maximized. It decomposes the link allocation task into a set of link admission control (LAC) tasks, formulated as semi-Markov Decision Problems (SMDPs). The LAC policies are directly adapted by reinforcement learning. Simulations show that the direct adaptive SMDP scheme outperforms static methods, which maximize the short-term revenue. It also yields a long-term revenue comparable to an indirect adaptive SMDP method.

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تاریخ انتشار 1995