期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2013
卷号：3
期号：2
页码：221-229
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Optimizing location of controllers in wireless networks is an important problem in the cellular mobile networks designing. In this paper, I present two algorithms based on Genetic Algorithm (GA) and Ant Colony Optimization (ACO) to solve it. In the first algorithm, my objective function is determined by the total distance based on finding maximum flow in a bipartite graph using Ford-Fulkerson algorithm. In the second algorithm, I generate pheromone matrix of ants and calculate the pheromone content of the path from controller i to base station j using the neighborhood includes only locations that have not been visited by ant k when it is at controller i. At each step of iterations, I choose good solutions satisfying capacity constraints and update step by step to find the best solution depending on my cost functions. I evaluate the performance of my algorithms to optimize location of controllers in wireless networks by comparing to SA, SA-Greedy, LB-Greedy algorithm. Numerical results show that my algorithms proposed have achieved much better more than other algorithms.DOI:http://dx.doi.org/10.11591/ijece.v3i2.2290
其他摘要：Optimizing location of controllers in wireless networks is an important problem in the cellular mobile networks designing. In this paper, I present two algorithms based on Genetic Algorithm (GA) and Ant Colony Optimization (ACO) to solve it. In the first algorithm, my objective function is determined by the total distance based on finding maximum flow in a bipartite graph using Ford-Fulkerson algorithm. In the second algorithm, I generate pheromone matrix of ants and calculate the pheromone content of the path from controller i to base station j using the neighborhood includes only locations that have not been visited by ant k when it is at controller i. At each step of iterations, I choose good solutions satisfying capacity constraints and update step by step to find the best solution depending on my cost functions. I evaluate the performance of my algorithms to optimize location of controllers in wireless networks by comparing to SA, SA-Greedy, LB-Greedy algorithm. Numerical results show that my algorithms proposed have achieved much better more than other algorithms. DOI: http://dx.doi.org/10.11591/ijece.v3i2.2290
关键词：Telecommunication; Computer and Informatics;Terminal Assignment; Optimal Location of Controllers Problem; Genetic Algorithm; Ant Colony Optimization; Wireless Networks
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