Qos Improvement Using Hybrid Genetic Algorithm Based AODV In Manet

Abstract

Multi hop links are used to communicate between nodes in a Mobile Ad Hoc Network (MANET). Data packets are routed through intermediate nodes in the network to the destination node since each node functions as a router. Dynamic routing protocols are being developed for network communication efficiency. Routing protocols in MANETS face problems such as versatility, scalability, and restricted bandwidth. A fuzzy logic approach is suggested as part of the study. In this work, a fuzzy logic methodology is planned to choose the best routes in order to better QoS  End-to-end delay (Ae), when a node leaves the network (Nl), A fuzzy rule-based scheme NR includes the number of packets dropped (ND) and the number of path error RRER caused parameters. Simulations are carried out in this study using the proposed fuzzy approach process Simulations are carried out in this study using the future process fuzzy approach. The measurement criteria are throughput and the number of packets dropped. The tentative results obtained show that the proposed fuzzy approach improves the QoS better than existing regular Ad hoc On-demand Distance Vector ( AODV) routing protocol.

In the final stage of investigation, the use of a hybrid optimization approach to choose the best route is suggested. The proposed hybrid optimization is based on the Genetic Algorithm (GA) and the Hill Climbing algorithm. The hybrid optimization aids in the resolution of the local minimum problem Hill-climbing begins with an infeasible solution and continues until a viable solution is found, at which point the viable solution is returned to GA. The simulation results show that the throughput is high. When compared to the AODV protocol, the proposed Fuzzy-Hybrid GA method yields about 29.56 percent more and 6.33 percent more when compared to the Fuzzy-GA solution.