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首页> 外文期刊>IEEE transactions on mobile computing >Performance Analysis and Optimization of Handoff Algorithms in Heterogeneous Wireless Networks
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Performance Analysis and Optimization of Handoff Algorithms in Heterogeneous Wireless Networks

机译:异构无线网络中切换算法的性能分析与优化

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In heterogeneous wireless networks, handoff can be separated into two parts: horizontal handoff (HHO) and vertical handoff (VHO). VHO plays an important role to fulfill seamless data transfer when mobile nodes cross wireless access networks with different link layer technologies. Current VHO algorithms mainly focus on when to trigger VHO, but neglect the problem of how to synthetically consider all currently available networks (homogeneous or heterogeneous) and choose the optimal network for HHO or VHO from all the available candidates. In this paper, we present an analytical framework to evaluate VHO algorithms. Subsequently, we extend the traditional hysteresis based and dwelling-timer based algorithms to support both VHO and HHO decisions and apply them to complex heterogeneous wireless environments. We refer to these enhanced algorithms as E-HY and E-DW, respectively. Based on the proposed analytical model, we provide a formalization definition of the handoff conditions in E-HY and E-DW and analyze their performance. Subsequently, we propose a novel general handoff decision algorithm, GHO, to trigger HHO and VHO in heterogeneous wireless networks. Analysis shows that GHO can achieve better performance than E-HY and E-DW. Simulations validate the analytical results and verify that GHO outperforms traditional algorithms in terms of the matching ratio, TCP throughput and UDP throughput.
机译:在异构无线网络中,切换可以分为两部分:水平切换(HHO)和垂直切换(VHO)。当移动节点通过具有不同链路层技术的无线接入网络穿越时,VHO起着实现无缝数据传输的重要作用。当前的VHO算法主要集中在何时触发VHO上,而忽略了如何综合考虑所有当前可用网络(同质或异构)并从所有可用候选中为HHO或VHO选择最佳网络的问题。在本文中,我们提出了一种评估VHO算法的分析框架。随后,我们扩展了传统的基于滞后和基于驻留计时器的算法,以支持VHO和HHO决策,并将其应用于复杂的异构无线环境。我们将这些增强算法分别称为E-HY和E-DW。基于所提出的分析模型,我们为E-HY和E-DW中的切换条件提供了形式化定义,并分析了它们的性能。随后,我们提出了一种新颖的通用切换决策算法GHO,以在异构无线网络中触发HHO和VHO。分析表明,GHO可以实现比E-HY和E-DW更好的性能。仿真验证了分析结果,并验证了GHO在匹配率,TCP吞吐量和UDP吞吐量方面优于传统算法。

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