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Performance Analysis of Vertical Handoff Algorithms with QoS Parameter Differentiation

机译:QoS参数区分的垂直切换算法性能分析

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Despite recent interests in developing vertical handoff decision algorithms, an essential component of the architecture of the next generation heterogeneous wireless networks, very few studies have so far reported any meaningful comparative performance analysis. This paper attempts to fill this gap in the literature by presenting a comprehensive study on the performance of three vertical handoff decision algorithms, namely, SAW (Simple Additive Weighting), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and MDP (Markov Decision Process). We have used both analytical and simulation tools (ns-2.29) to evaluate and compare expected total QoS offerings in the mean duration of a service under different state transition probability distributions, user perception models on the importance of QoS parameters, and network switching costs. To our surprise, we have observed TOPSIS achieving the best performance despite MDPȁ9;s using the optimal policy. We suspect that the user satisfiability model used in MDP to estimate link rewards might have contradicted the underlying user perception model used to estimate normalised weight of each QoS parameter, which will be investigated in future.
机译:尽管最近对开发垂直切换决策算法(下一代异构无线网络体系结构的重要组成部分)感兴趣,但迄今为止,很少有研究报告任何有意义的比较性能分析。本文试图通过对三种垂直切换决策算法的性能进行全面研究来填补文献中的空白,这三种算法分别是SAW(简单加法加权),TOPSIS(类似于理想解决方案的订单偏好技术)和MDP(马尔可夫决策过程)。我们已经使用了分析和仿真工具(ns-2.29)来评估和比较在不同状态转移概率分布下的服务平均持续时间,服务质量参数重要性的用户感知模型以及网络交换成本方面的预期总QoS产品。令我们惊讶的是,尽管MDPȁ9使用了最佳策略,但我们仍观察到TOPSIS取得了最佳性能。我们怀疑在MDP中用于估计链接奖励的用户可满足性模型可能与用于估计每个QoS参数的标准化权重的基础用户感知模型相矛盾,将在以后进行研究。

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