Unicast Quality of Service Routing in Mobile Ad Hoc Networks Based on Neuro-fuzzy Agents

This position paper presents Quality of Service (QoS) routing model in Mobile Ad hoc Networks (MANETs) by using software agents that employ fuzzy logic and neural networks for intelligent routing. It uses Dynamic Source Routing (DSR) in MANETs to find various paths and attributes. Fuzzy static agents decide whether each node on the path satisfies QoS requirement for multimedia application. The static neuro-fuzzy agents are used for training and learning to optimize the input and output fuzzy membership functions according to user requirement, and Q-learning (reinforcement learning) static agent is employed for fuzzy inference instead of experts experience. Mobile agents are used to maintain and repair the paths.

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