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  • 梁广俊,王群,辛建芳,李梦,许威.移动边缘计算资源分配综述[J].信息安全学报,2021,6(3):227-256    [点击复制]
  • LIANG Guangjun,WANG Qun,XIN Jianfang,LI Meng,XU Wei.Survey of Mobile Edge Computing Resource Allocation[J].Journal of Cyber Security,2021,6(3):227-256   [点击复制]
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移动边缘计算资源分配综述
梁广俊1,2, 王群1, 辛建芳3,4, 李梦1, 许威2
0
(1.江苏警官学院计算机信息与网络安全系 南京 中国 210031;2.东南大学信息科学与工程学院 南京 中国 211189;3.安徽工程大学电气工程学院 芜湖 中国 241000;4.南京邮电大学通信与信息工程学院 南京 中国 210003)
摘要:
在万物互联的物联网时代,云计算凭借超强的计算能力和存储能力提供了主流的大数据处理方案。随着5G的正式商用,面对5G+物联网呈爆炸式增长的终端设备以及低时延、低功耗的用户需求,基于云计算的大数据处理方案逐渐显露弊端。分布式的面向移动终端的大数据处理方案——移动边缘计算呼之欲出。本文通过对比云计算、边缘计算和移动边缘计算的概念和相关特征,引入移动边缘计算的定义及八大典型应用场景,进一步列举出移动边缘计算的发展历程。随后,归纳出移动边缘计算的几种国际标准模型以及框架设计的相关研究,结合移动边缘计算资源分配的关键问题进行梳理。最后,提出移动边缘计算的未来的研究方向和挑战。
关键词:  移动边缘计算  标准模型  资源分配  卸载
DOI:10.19363/J.cnki.cn10-1380/tn.2021.05.15
投稿时间:2020-05-26修订日期:2020-10-23
基金项目:本研究得到江苏警官学院高层次引进人才科研启动项目(No.JSPI19GKZL407),安徽省高等教育研究计划一般项目(No.GrantTSKJ2015B18)资助。
Survey of Mobile Edge Computing Resource Allocation
LIANG Guangjun1,2, WANG Qun1, XIN Jianfang3,4, LI Meng1, XU Wei2
(1.Department of Computer Information and Network Security, Jiangsu Police Institute, Nanjing 210031, China;2.School of Information Science and Engineering, Southeast University, Nanjing 211189, China;3.School of Electrical Engineering, Anhui University of Engineering, Wuhu 241000, China;4.School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China)
Abstract:
In the era of Internet of Things, cloud computing provides mainstream big data processing solutions with its super computing power and storage capabilities. With the official commercialization of 5G, in the face of the explosive growth of 5G+ Internet of Things terminal equipment and user needs with low latency and low power consumption, cloud computing-based big data processing solutions have gradually revealed their drawbacks. A distributed big data processing solution for mobile terminals-mobile edge computing is just around the corner. This article compares the concepts and related characteristics of cloud computing, edge computing and mobile edge computing, and further enumerates the development history of mobile edge computing. Subsequently, several international standard models for mobile edge computing and research on frame design were summarized, and combing the key issues of mobile edge computing resource allocation. Finally, the future research directions and challenges of mobile edge computing are proposed.
Key words:  mobile edge computing  standard model  resource allocation  offloading