ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2018, Vol. 55 ›› Issue (3): 512-523.doi: 10.7544/issn1000-1239.2018.20170793

所属专题: 2018边缘计算专题

• 网络技术 • 上一篇    下一篇

边缘计算环境下应用驱动的网络延迟测量与优化技术

符永铨,李东升   

  1. (国防科技大学计算机学院 长沙 410073) (国防科技大学并行与分布处理重点实验室 长沙 410073) (yongquanf@nudt.edu.cn)
  • 出版日期: 2018-03-01
  • 基金资助: 
    国家“九七三”重点基础研究发展计划基金项目(2014CB340303);国家自然科学基金项目(61402509)

Application Driven Network Latency Measurement Analysis and Optimization Techniques Edge Computing Environment: A Survey

Fu Yongquan , Li Dongsheng   

  1. (College of Computer, National University of Defense Technology, Changsha 410073) (Science and Technology on Parallel and Distributed Laboratory, National University of Defense Technology, Changsha 410073)
  • Online: 2018-03-01

摘要: 互联网、移动计算、物联网技术的进步推动了人-机-物环境的深度融合,催生了一大批面向边缘用户的网络搜索、在线社会网络、电子商务、视频监控、智能助理等类型的边缘计算应用.边缘计算应用具有规模巨大、服务质量敏感等特性,对延迟性能提出迫切需求,然而,由于用户访问请求跨边缘网络、广域网、数据中心异构环境,“长尾延迟”问题导致边缘用户的体验质量严重下降.首先综述边缘计算应用的系统架构特征,然后分析长尾延迟的产生原因,分类介绍网络延迟测量的主要理论和方法,并归纳对长尾延迟的优化技术,最后提出在线优化运行环境的思想以及面临的挑战.

关键词: 边缘网络, 边缘计算应用, 长尾延迟, 测量, 优化

Abstract: The technical advancements of Internet, mobile computing and Internet of things (IoT) have been pushing the deep integration of human, machine and things, which fostered a lot of end-users oriented network search, online social networks, economical business, video surveillance and intelligent assistant tools, which are typically referred to as online data-intensive applications. These new applications are of large scale and sensitive to the service quality, requiring stringent latency performance. However, end-user requests traverse heterogeneous environments including edge network, wide-area network and the data center, which naturally incurs a long-tail latency issue that significantly degrades users’ experience quality. This paper surveys architectural characteristics of edge-computing applications, analyzes causes of the long-tail latency issue, categorizes key theories and methods of the network latency measurement, summarizes long-tail latency optimization techniques, and finally proposes the idea of constructing an online optimization runtime environment and discusses some open challenges.

Key words: edge network, edge-computing applications, long-tail latency, measurement, optimization

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