Selection and ranking of optimal routes through genetic algorithm in a cognitive routing system for mobile ad-hoc network
Genetic algorithm can be used for proper selection and ranking of all possible variable route addresses in mobile ad-hoc network (MANET). Ranking is based upon priority code of the links. A priority code is calculated by respective routing protocol, which depends on different parameters and metrics. A node can change its position and new nodes may join the MANET, so genetic algorithm can better estimate such kind of variations through its crossover and mutation genetic operators. Genetic algorithm is especially useful in cases of novel cognitive routing for MANET. Cognition in MANET is either based upon learning automata method as in some wireless sensor networks or specialized cognitive neural networks. Ranking of optimal links in MANET after a regular interval through genetic algorithm enhance the performance of cognitive routing. It help in proper selection of desired routing protocol for a given set of network conditions.
component Reactive and proactive protocols Hybrid routing system Cognitive routing system Mobile ad-hoc network (MANET) Neural network Genetic algorithm learning automata
Muhammad Ishaq Afridi
College of Computer Science and Technology Harbin Engineering University Harbin, Heilongjiang, 150001 China
国际会议
杭州
英文
507-510
2012-10-28（万方平台首次上网日期，不代表论文的发表时间）