Mobility prediction in mobile ad-hoc network using deep learning

机译：使用深度学习的移动自组织网络中的移动性预测

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摘要

Nowadays, ad-hoc network becomes common to predict highly moveable devices. Deep learning is a proposed technique to predict based on the node movement history to know mobile stations current mobility information based on pause time, speed and movement direction. We used random waypoint mobility (RWM) principle to create location pattern for the proposed system. The simulation result shows that the proposed system can successfully predict the mobile user's mobility through RSS values in the dynamic environments.

机译：如今，ad-hoc网络变得越来越普遍，可以预测高度可移动的设备。深度学习是一种提出的技术，可基于节点的移动历史进行预测，从而基于暂停时间，速度和移动方向来了解移动台当前的移动性信息。我们使用随机航路点移动性（RWM）原理为拟议系统创建位置模式。仿真结果表明，所提出的系统能够在动态环境中通过RSS值成功预测移动用户的移动性。

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来源
《Proceedings of 4th IEEE International Conference on Applied System Invention》|2018年|1203-1206|共4页
会议地点 Chiba(JP)
作者
Yirga Yayeh; Hsin-piao Lin; Getaneh Berie; Abebe Belay Adege; Lei Yen; Shiann-Shiun Jeng;
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作者单位

Department of Electrical Engineering and Computer Science, National Taipei University of Technology;

Department of Electronic Engineering, National Taipei University of Technology;

Department of Electrical Engineering and Computer Science, National Taipei University of Technology;

Department of Electrical Engineering and Computer Science, National Taipei University of Technology;

Department of Electronic Engineering, National Taipei University of Technology;

Department of Electrical Engineering, National Dong Hwa University;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Training; Mathematical model; Machine learning; Mobile ad hoc networks; Manganese; Predictive models;

机译：培训;数学模型;机器学习;移动自组织网络;锰;预测模型;;

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专利

1. Mobility-based multicast routing algorithm for wireless mobile Ad-hoc networks: A learning automata approach [J] . Javad Akbari Torkestani, Mohammad Reza Meybodi Computer Communications . 2010,第6期

机译：无线移动自组织网络中基于移动性的多播路由算法：一种学习自动机方法
2. An Autonomous Group Mobility Prediction Model for Simulation of Mobile Ad-hoc through Wireless Network [J] . Walisa Romsaiyud, Wichian Premchaiswadi, Nucharee Premchaiswadi Journal of Wireless Networking and Communications . 2012,第5期

机译：通过无线网络模拟移动自组织的自治团体移动性预测模型
3. Classification and Evaluation of Mobility Metrics for Mobility Model Movement Patterns in Mobile Ad-Hoc Networks [J] . Santosh Kumar S, C Sharma Bhupendra Suman International Journal on Applications of Graph Theory in Wireless ad hoc Networks and Sensor Networks . 2011,第3期

机译：移动Ad-Hoc网络中移动模型移动模式的移动度量标准分类和评估
4. Mobility prediction in mobile ad-hoc network using deep learning [C] . Yirga Yayeh, Hsin-piao Lin, Getaneh Berie, International Conference on Applied System Innovation . 2018

机译：使用深度学习的移动临时网络移动性预测
5. Mobile ad-hoc networks: Mobility-induced metrics, performance analysis, and system design. [D] . Cai, Han. 2009

机译：移动自组织网络：移动性度量，性能分析和系统设计。
6. SVM-Based Spectrum Mobility Prediction Scheme in Mobile Cognitive Radio Networks [O] . Yao Wang, Zhongzhao Zhang, Lin Ma, -1

机译：移动认知无线电网络中基于SVM的频谱移动性预测方案
7. On-Demand Routing Algorithm with Mobility Prediction in the Mobile Ad-hoc Networks [O] . Vu, Trung Kien, Kwon, Sungoh 2016

机译：移动机器人中具有移动性预测的按需路由算法 ad-hoc网络

Mobility prediction in mobile ad-hoc network using deep learning

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