面向边缘计算的资源优化技术研究进展

doi:10.11959/j.issn.2096-0271.2019011

大数据 ›› 2019, Vol. 5 ›› Issue (2): 17-33.doi: 10.11959/j.issn.2096-0271.2019011

所属专题：边缘计算

面向边缘计算的资源优化技术研究进展

屈志昊¹,叶保留²,陈贵海²,唐斌²,郭成昊³

¹ 河海大学计算机与信息学院，江苏南京 211100
² 南京大学计算机科学与技术系，江苏南京 210046
³ 中国电子科技集团公司第二十八研究所，江苏南京 210007

出版日期:2019-03-15 发布日期:2019-04-04
作者简介:屈志昊（1989- ），男，河海大学计算机与信息学院博士生，主要研究方向为移动边缘计算、移动流媒体。|叶保留（1976- ），男，博士，南京大学计算机科学与技术系教授、博士生导师，中国计算机学会（CCF）理事、分布式计算与系统专业委员会秘书长，主要研究方向为云计算、边缘计算、无线网络。|陈贵海（1963- ）男，博士，南京大学计算机科学与技术系教授、博士生导师，CCF会士、分布式计算与系统专业委员会主任，主要研究方向为云计算、边缘计算、计算机网络。|唐斌（1986- ），男，博士，南京大学计算机科学与技术系助理研究员，CCF会员，主要研究方向为网络编码、无线网络、边缘计算。|郭成昊（1981- ），男，博士，就职于中国电子科技集团公司第二十八研究所，主要研究方向为边缘计算、分布式系统、机器学习。
基金资助:
国家重点研发计划基金项目资助(2018YFB1004704);国家自然科学基金资助项目(61832005);江苏省重点研发计划基金资助项目(BE2017152)

State-of-the-art survey on resource optimization in edge computing

Zhihao QU¹,Baoliu YE²,Guihai CHEN²,Bin TANG²,Chenghao GUO³

¹ College of Computer and Information,Hohai University,Nanjing 211100,China
² Department of Computer Science and Technology,Nanjing University,Nanjing 210046,China
³ The 28th Research Institute of China Electronics Technology Group Corporation,Nanjing 2100007,China

Online:2019-03-15 Published:2019-04-04
Supported by:
National Key Research and Development Program of China(2018YFB1004704);The National Natural Science Foundation of China(61832005);Provincial Key Research and Development Program of Jiangsu(BE2017152)

摘要/Abstract

摘要：

以云计算模型为代表的集中式数据处理关键技术已不能高效、及时地处理边缘设备产生的数据。针对这一问题，以“数据处理应更靠近数据源头”为核心理念的边缘计算模型应运而生。首先介绍了微数据中心、微云、雾计算、移动边缘计算等计算范型，并讨论了边缘资源整合的优势。然后，回顾了近年来边缘计算中与资源优化领域相关的工作，以计算、存储和通信3种资源为切入点，分别从计算卸载、分布式缓存和高性能传输这3个研究热点，对国内外的研究进展进行总结和讨论。最后，展望了该领域未来的发展趋势和主要的研究方向。

关键词: 边缘计算, 计算卸载, 分布式缓存, 高性能传输

Abstract:

The traditional centralized architecture,known as cloud computing,cannot accommodate such user demands in an efficient and timely manner.To cope with this problem,edge computing architectures have been proposed with the core concept of that“data processing should be close to the data source”.Firstly,paradigms of edge computing was introduced,including micro data center,cloudlet,fog computing,and mobile edge computing,and the advantages of edge computing from the perspective of resource integration was discussed.Then,related works of resource optimization in edge computing was reviewed and summarized,and these works was discussed via three directions,i.e.,computation offloading,distributed caching and high performance transmission,corresponding to core resources as computing,storage and communication.Finally,trends of development and future directions were presented as well.

Key words: edge computing, computation offloading, distributed caching, high performance transmission

中图分类号:

TP393

屈志昊, 叶保留, 陈贵海, 唐斌, 郭成昊. 面向边缘计算的资源优化技术研究进展[J]. 大数据, 2019, 5(2): 17-33.

Zhihao QU, Baoliu YE, Guihai CHEN, Bin TANG, Chenghao GUO. State-of-the-art survey on resource optimization in edge computing[J]. Big Data Research, 2019, 5(2): 17-33.

图/表 5

参考文献 71

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面向边缘计算的资源优化技术研究进展

State-of-the-art survey on resource optimization in edge computing

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