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首页> 外文期刊>Journal of Advanced Computatioanl Intelligence and Intelligent Informatics >Paper: Enhanced Intersystem Handover Algorithm for Heterogeneous Wireless Networks
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Paper: Enhanced Intersystem Handover Algorithm for Heterogeneous Wireless Networks

机译:纸质:增强异构无线网络的基础间切换算法

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摘要

Current and future wireless network architectures consist of several access technologies to support numerous traffic types and enable mobile devices to be connected anytime, anywhere. However, providing a rapid seamless connectivity and service continuity between such various access technologies remains a challenge. This is mainly because the previously proposed handover algorithms have failed to predict the future values of the measured received signal strength needed for rapid handover process. In addition, existing handover algorithms are not adaptable to the changes of the network conditions and user preferences. This leads to erroneous network selection, packet loss, and ping-pong effect due to high-ranking abnormality. In this study, an intersystem handover (IH) algorithm has been designed by integrating grey prediction theory, multiple-attribute decision making, fuzzy analytic hierarchy process, and multi-objective optimization ratio analysis. Network Simulator 2 has been applied to evaluate the performance of the proposed IH algorithm when compared to the fuzzy logic-based vertical handover (FLBVH) algorithm and the adaptive neuro-fuzzy inference system (ANFIS) algorithm. On average, the proposed IH algorithm has shown 1.1 s handover delay, 5% packet loss, 1.6% probability of ping-pong effect, and 97.8% better throughput performance than the ANFIS algorithm and FLBVH algorithm, respectively, for a 100-s time interval.
机译:当前和未来的无线网络架构包括几种访问技术,以支持众多流量类型并使移动设备随时随地连接移动设备。然而,在这些各种访问技术之间提供快速的无缝连接和服务连续性仍然是一个挑战。这主要是因为先前提出的切换算法未能预测快速切换过程所需的测量的接收信号强度的未来值。此外,现有的切换算法不适合网络条件和用户偏好的变化。由于高排名异常,这导致错误的网络选择,数据包丢失和平调效应。在这项研究中,通过集成灰色预测理论,多属性决策,模糊分析层次处理和多目标优化比分析,设计了一个基于网络切换(IH)算法。与基于模糊逻辑的垂直切换(FLBVH)算法和自适应神经模糊推理系统(ANFIS)算法相比,已应用网络模拟器2评估所提出的IH算法的性能。平均而言,该提出的IH算法显示了1.1秒的切换延迟,5%的丢包,比乒乓效应的1.6%概率,比ANFIS算法和FLBVH算法分别为100-S时间的97.8%间隔。

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