Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Seamless Service Handoff for Ubiquitous Mobile Multimedia
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A multicriteria handoff decision scheme for the next generation tactical communications systems
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Military communications systems and technologies
Access network selection based on fuzzy logic and genetic algorithms
Advances in Artificial Intelligence
A Vertical Handoff Decision Algorithm for Next Generation Wireless Networks
BROADCOM '08 Proceedings of the 2008 Third International Conference on Broadband Communications, Information Technology & Biomedical Applications
Mobility Management Incorporating Pattern Recognition in the Handoff Decision
ICACC '09 Proceedings of the 2009 International Conference on Advanced Computer Control
Adaptive Vertical Handoff Decision Algorithm for Wireless Heterogeneous Networks
HPCC '09 Proceedings of the 2009 11th IEEE International Conference on High Performance Computing and Communications
Artificial Neural Network Based Vertical Handoff Algorithm for Reducing Handoff Latency
Wireless Personal Communications: An International Journal
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Handoff decision making is one of the most important topics in wireless heterogeneous networks architecture as there are many parameters which have to be considered when triggering handoff and selecting suitable access point. More intelligent approaches which reckon user profiles, application requirements, and network conditions must be improved so that desired performance results for both user and network could be provided. In this paper we introduce a new adaptive vertical handoff decision making algorithm in which fuzzy membership functions are optimized by means of genetic algorithm. Genetic algorithm is an adaptive search technique based on natural selection and genetic rules. In addition to that, it takes places in various scientific applications and can be used to adjust the membership functions in fuzzy systems. The purpose of the study is to adjust the shape of fuzzy membership functions, properly, using genetic algorithm in order to achieve optimum handoff performance. The results show that, compared to the several different algorithms performance of the proposed approach with genetic algorithm is significantly improved for both user and network in terms of number of handoff while the other requirements are still satisfied.