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A Comparative Study of Evolutionary Algorithms for Maximizing Reliability of a Flow in Cellular IP Network
Abstract
The rapid development in technology, witnessed in daily communication, especially in wireless communication, is a good motivation for performance improvement in this field. Cellular IP access network is a suitable environment where a micro mobility of mobile users is implemented and managed. The reliability of Cellular IP network during the communication is an important characteristic measure and must be considered while designing a new model. Evolutionary Algorithms are powerful tools for optimization and problem solving, which require extracting the best solution from a big search space. This chapter explores the reliability issue in Cellular IP of a flow of packets passing through the route from a source to a destination. The main aim of the chapter is to maximize the reliability of the flow passing through a route having number of routers. Two Evolutionary Algorithms (EAs), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), have been used for this purpose, and a comparative study between the two is performed. Experimental studies of the proposed work have also been performed.
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