Enhancing energy efficiency and load balancing in mobile ad hoc network using dynamic genetic algorithms (original) (raw)
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A Review Paper on Different Application of Genetic Algorithm for Mobile Ad-hoc Network (MANET)
International Journal of Online and Biomedical Engineering (iJOE)
A Genetic algorithm is a search algorithm depends on the methodology of natural selection and natural genetics. A Mobile Ad hoc network (MANET) is a type of wireless nodes (Devices) which are free to move anywhere in the network without any constraints. The nodes which are in range can communicate each other through radio waves and those who are not in range use any routing algorithm for communication. In this review paper, we focus on the problems of MANET that has been solved by applying GA for it and highlights the characteristic and challenges of MANET in the literature. More specifically, we present the summary of review papers and basic solutions that use and in the last, we present some future direction. Consequently, we concluded that modification in Fitness function (Evaluation function) according to the problem is the base of Genetic algorithm and variation in algorithm parameters can give solutions in a reasonable time.
Genetic Algorithms for Dynamic Routing Problems in Mobile Ad Hoc Networks
Studies in Computational Intelligence, 2013
Routing plays an important role in various types of networks. There are two main ways to route the packets, i.e., unicast and multicast. In most cases, the unicast routing problem is to find the shortest path between two nodes in the network and the multicast routing problem is to find an optimal tree spanning the source and all the destinations. In recent years, both the shortest path routing and the multicast routing have been well addressed using intelligent optimization techniques. With the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc networks (MANETs). One of the most important characteristics in MANETs is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, both routing problems turn out to be dynamic optimization problems in MANETs. In this chapter, we investigate a series of dynamic genetic algorithms to solve both the dynamic shortest path routing problem and the dynamic multicast routing problem in MANETs. The experimental results show that these specifically designed dynamic genetic algorithms can quickly adapt to environmental changes (i.e., the network topology changes) and produce high quality solutions after each change.
Reported in this paper are the results of a simulated experimental comparison of Genetic Algorithm (GA) and Ant Colony Optimization (ACO) meta-heuristics, with regards to their suitability and performance in addressing the problem of energy consumption minimization in ad-hoc wireless networks. An energy function model based on Geographic Adaptive Fidelity (GAF) topology management scheme is used in setting the simulation experiment. Results show that GA and ACO meta-heuristics are suitable optimization techniques for energy consumption minimization in ad-hoc wireless networks, with GA giving the least energy consumption in comparison to ACO.