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An Optimum Vertical Handoff Decision Algorithm Based on Adaptive Fuzzy Logic and Genetic Algorithm

机译:基于自适应模糊逻辑和遗传算法的最优垂直切换决策算法。

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摘要

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.
机译:切换决策是无线异构网络体系结构中最重要的主题之一,因为触发切换和选择合适的接入点时必须考虑许多参数。必须改进考虑用户配置文件,应用程序要求和网络条件的更智能的方法,以便可以为用户和网络提供所需的性能结果。本文介绍了一种新的自适应垂直切换决策算法,其中遗传算法对模糊隶属度函数进行了优化。遗传算法是一种基于自然选择和遗传规则的自适应搜索技术。除此之外,它还发生在各种科学应用中,并可用于调整模糊系统中的隶属函数。该研究的目的是使用遗传算法适当地调整模糊隶属函数的形状,以实现最佳的切换性能。结果表明,与几种不同的算法相比,所提出的遗传算法的性能在切换数量上显着提高了用户和网络的性能,同时仍然满足了其他要求。

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