Evolutionary fuzzy multi-objective routing for wireless mobile ad hoc networks

The complexity involved in implementing multi-objective routing in computer networks has led to many researchers exploring alternate solutions with the use of heuristic based techniques. The rationale underlying the use of heuristic based priorities in achieving multiple objectives appears to be ad hoc and unclear due to the complex interactions among the various objectives. However these uncertainties can be effectively modeled using fuzzy set theory. This work introduces the notion of multi-objective route selection in mobile ad hoc networks (MANET) using a evolutionary fuzzy cost function to deliberately calculate cost adaptively. The fuzzy cost function is a continuous function of the metrics describing the state of a route. Simulation results demonstrate the superiority of the proposed technique over conventional MANET routing schemes.