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Reinforcement Learning-Based Load Shared Sequential Routing

8 years 9 months ago
Reinforcement Learning-Based Load Shared Sequential Routing
We consider event dependent routing algorithms for on-line explicit source routing in MPLS networks. The proposed methods are based on load shared sequential routing in which load sharing factors are updated using learning algorithms. The learning algorithms we employ are either based on learning automata or on online learning algorithms that were originally devised for solving the adversarial multi-armed bandit problem. While simple to implement, the performance of the proposed learning algorithms in terms of blocking probability compares favorably with the performance of other event dependent routing methods proposed for MPLS routing such as the success to the top algorithm. We demonstrate the convergence of one of the learning algorithms to the user equilibrium within a set of discrete event simulations.
Fariba Heidari, Shie Mannor, Lorne Mason
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where NETWORKING
Authors Fariba Heidari, Shie Mannor, Lorne Mason
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