New Generation Routing Protocol over Mobile Ad Hoc Wireless Networks based on Neuro-Fuzzy-Genetic Paradigm

There is a vast amount of researched literature available on Route Finding and Link Establishment in MANET protocols based on various concepts such as “pro-active”, “reactive”, “power awareness”, “cross-layering” etc. Most of these techniques are rather restrictive, taking into account a few of the several aspects that go into effective route establishment. When we look at practical implementations of MANETs, we have to take into account various factors in totality, not in isolation. The several factors that decide and influence the routing have to be considered as a whole in the difficult task of finding the best solution in route finding and optimization. The inputs to the system are manifold and apparently unrelated. Most of the parameters are imprecise or non-crisp in nature. The uncertainty and imprecision lead to think that intelligent routing techniques are essential and important in evolving robust and dependable solutions to route finding. The obvious method by which this can be achieved is the deployment of soft computing techniques such as Neural Nets, Fuzzy Logic and Genetic algorithms. Neural Networks help us to solve the complex problem of transforming the inputs to outputs without apriori knowledge of what the relationship is between inputs and outputs. Fuzzy Logic helps us to deal with imprecise and ill-conditioned data. Genetic Algorithms help us to select the best possible solution from the solution space in an optimal sense. Our paper presented here below seeks to explore new horizons in this direction. The results of our experimentation have been very satisfactory and we have achieved the goal of optimal route finding to a large extent. There is of course considerable room for further refinements.