EdgeFlow移动边缘计算在物联网中的应用研究
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摘要
为应对未来物联网更高计算速率、更低通信时延和更高接入密度的要求,提出了移动边缘计算框架EdgeFlow,考虑了阻塞态和非阻塞态的任务卸载算法。通用软件无线电平台模拟实验表明,EdgeFlow可以显著提高计算效率、降低通信时延,为解决物联网更高计算需求的问题指明了新的发展方向,奠定了理论与实践基础,可以广泛应用于物联网场景中。
In order to meet the requirements of higher computing speed, lower communication delay and higher access density in the future Internet of things, a computational framework of EdgeFlow for mobile edge computing and a task unloading algorithm considering blocking and non-blocking state were proposed. The simulation experiments on the universal software radio platform show that the computational efficiency can be improved significantly and the communication delay can be reduced by EdgeFlow. It points out a new development direction, lays a theoretical and practical foundation for solving the problem of higher computational requirements of the Internet of things. And it will be widely used in the Internet of things scenarios.
In order to meet the requirements of higher computing speed, lower communication delay and higher access density in the future Internet of things, a computational framework of EdgeFlow for mobile edge computing and a task unloading algorithm considering blocking and non-blocking state were proposed. The simulation experiments on the universal software radio platform show that the computational efficiency can be improved significantly and the communication delay can be reduced by EdgeFlow. It points out a new development direction, lays a theoretical and practical foundation for solving the problem of higher computational requirements of the Internet of things. And it will be widely used in the Internet of things scenarios.
引文
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[2]MOHAMMAD A R,MARIJA M J,ANDREI P,et al.Middleware for Internet of things:a survey[J].IEEE Internet of Things Journal,2017,3(1):70-95.
[3]JEFFREY B.Cisco:SDN,collaboration,Internet of things to drive future trends[J].eWEEK,2013(12):5.
[4]EVANS D.The Internet of things:how the next evolution of the Internet is changing everything[J].CISCO White Paper,2011(1):11.
[5]ALEKSANDRA C,HENRIK L C,YING Y,et al.Cloud RAN for mobile networks--a technology overview[J].IEEE Communications Surveys and Tutorials,2015,17(1):405-426.
[6]WANG S,ZHANG X,ZHANG Y,et al.A survey on mobile edge networks:convergence of computing,caching and communications[J].IEEE Access,2017:1.
[7]YI S H,LI C,LI Q.A survey of fog computing[C]//The 2015 Workshop on Mobile Big Data.ACM,2015:9-16.
[8]SHI W S,CAO J,ZHANG Q,et al.Edge computing:vision and challenges[J].IEEE Internet of Things Journal,2016,3(5):637-646.
[9]TANG L,HE S B.Multi-user computation offloading in mobile edge computing:a behavioral perspective[J].IEEE Network,2018,32(1):48-53.
[10]LIU J,MAO Y Y,ZHANG J,et al.Delay-optimal computation task scheduling for mobile-edge computing systems[C]//IEEE International Conference on Distributed Computing Systems.IEEE,2016:1451-1455.