文章基本信息

标题：Access Network Selection Based on Fuzzy Logic and Genetic Algorithms
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作者：Mohammed Alkhawlani ; Aladdin Ayesh
期刊名称：Advances in Artificial Intelligence
印刷版ISSN：1687-7470
电子版ISSN：1687-7489
出版年度：2008
卷号：2008
DOI：10.1155/2008/793058
出版社：Hindawi Publishing Corporation
摘要：In the next generation of heterogeneous wireless networks (HWNs), a large number of different radio access technologies (RATs) will be integrated into a common network. In this type of networks, selecting the most optimal and promising access network (AN) is an important consideration for overall networks stability, resource utilization, user satisfaction, and quality of service (QoS) provisioning. This paper proposes a general scheme to solve the access network selection (ANS) problem in the HWN. The proposed scheme has been used to present and design a general multicriteria software assistant (SA) that can consider the user, operator, and/or the QoS view points. Combined fuzzy logic (FL) and genetic algorithms (GAs) have been used to give the proposed scheme the required scalability, flexibility, and simplicity. The simulation results show that the proposed scheme and SA have better and more robust performance over the random-based selection.