A Self-Adaptive Routing Paradigm for Wireless Mesh Networks Based on Reinforcement Learning

Classical routing protocols for WMNs are typically designed to achieve specific target objectives (e.g., maximum throughput), and they offer very limited flexibility. As a consequence, more intelligent and adaptive mesh networking solutions are needed to obtain high performance in diverse network conditions. To this end, the authors propose a reinforcement learning-based routing framework that allows each mesh device to dynamically select at run time a routing protocol from a pre-defined set of routing options, which provides the best performance.

Provided by: Association for Computing Machinery Topic: Mobility Date Added: Nov 2011 Format: PDF

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