FUZZY MULTIPLE METRICS LINK ASSESSMENT FOR ROUTING IN MOBILE AD-HOC NETWORK
Ai Luang Soo, Chong Eng Tan, Kai Meng Tay, Nader Nassif Barsoum, Jeffrey Frank Webb, Pandian Vasant · AIP conference proceedings · 2011
In this work, we investigate on the use of Sugeno fuzzy inference system (FIS) in route selection for mobile Ad‐Hoc networks (MANETs). Sugeno FIS is introduced into Ad‐Hoc On Demand Multipath Distance Vector (AOMDV) routing protocol, which is derived from its predecessor, Ad‐Hoc On Demand Distance Vector (AODV). Instead of using the conventional way that considering only a single metric to choose the best route, our proposed fuzzy decision making model considers up to three metrics. In the model, the crisp inputs of the three parameters are fed into an FIS and being processed in stages, i.e., fuzzification, inference, and defuzzification. Finally, after experiencing all the stages, a single value score is generated from the combination metrics, which will be used to measure all the discovered routes credibility. Results obtained from simulations show a promising improvement as compared to AOMDV and AODV.