Neuro Fuzzy Model Based Routing Protocol in Mobile Ad-Hoc Networks

• Published in: International journal of computer network and information security 2022-12, Vol.14 (6), p.54-75
• Main Authors: Siddesh, G K, Anu, H, Chaithanya, S, Sathish, Shet K
• Format: Article
• Language: English
• Subjects: Artificial neural networks; Computer simulation; Fuzzy logic; Genetic algorithms; Mobile ad hoc networks; Probabilistic methods; Protocol; Protocol (computers); Regression models; Routing (telecommunications); Simulation; Statistical analysis; Wireless communications; Wireless networks
• ISSN: 2074-9090; 2074-9104
• DOI: 10.5815/ijcnis.2022.06.05

Mobile Ad-Hoc Networks (MANETs for short) are gaining the importance in the field of wireless communication. The promising feature of MANET is that it can be deployed immediately in demanding situations as they do not require the infrastructure or any centralized structures as compared to traditional wired and wireless networks.An intelligent system has been designed to select an optimum route for various contexts.An efficient protocol is designed to overcome the limits of route finding and link formation in MANET’s. This can be done by making use of the application of soft-computing techniques such as artificial neural networks, fuzzy logic and genetic algorithms. Traditional techniques are based on statistical techniques such as regression models and probabilistic methods.It can be seen from the simulation outcomes that the route finding time using the HYPER-NF-NET simulator which use soft computingtechniques is 20% to the routing finding time using NS-2 simulator. It is also seen from the simulation results that the HYPER-NF-NET protocol performance is better compared to AODV, DSR and OLSR routing protocols for different node population and various degree of congestion. The simulation results showcase a superiority of HYPER-NF-NET simulator over NS-2 and associated HFNET protocol over other existing protocols.