Hybrid Optimization of OLSR Routing Protocol in MANETs: Uniting Genetic Algorithm and Particle Swarm Optimization
Keywords:
Manets, PSO, GA, NS2, Routing Protocols, Optimization, OLSRAbstract
The acronym MANET stands for Mobile Ad-hoc Network, which describes a network of mobile nodes that may connect to one another and operate together even in the absence of a central server or other permanent location. Since MANETs are not dependent on any one specific infrastructure for their operation, the nodes that make up these networks are free to migrate anywhere they like. This mobility of the nodes makes routing a difficult task. It also drains the energy of the nodes which affects the performance as well as the lifetime of the network. Hence, MANETs are challenging due to frequent dynamically changing network topology and frequent route breakage. To achieve this compromise between natural selection and appropriate knowledge sharing, we proposed a hybrid approach that integrates the advantages of GA and PSO to conduct a more absolute and effective search of the solution space. To modify the OLSR performance, the adjustable hybrid model makes use of two driving factors, one of which gives precedence to PSO and the other to GA. To avoid having to rebuild the path whenever there is a change in the path due to a node/link failure, the suggested technique is used in conjunction with an effective dynamic component. The result of the simulation indicates that the suggested hybrid methodology enhances the quality-of-service performance of the OLSR routing protocol. The research results indicate that the hybrid model is superior to the PSO and GA models that are often used because of the hybrid model's greater flexibility in parameter selection.
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