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[ "孟令彬(1983- ),男,中国铁塔股份有限公司高级工程师,主要研究方向为 5G 网络技术、边缘计算、多制式共享产品创新与标准制定" ]
[ "李娟(1985- ),女,现就职于中国铁塔股份有限公司,主要研究方向为室分技术、小基站产品研发、边缘计算业务与产品创新" ]
[ "薛楠(1981- ),男,现就职于中国铁塔股份有限公司,主要研究方向为 5G 网络、边缘计算、物联网、工业互联网等" ]
[ "邹勇(1980- ),男,中国铁塔股份有限公司无线技术总监、高级工程师,主要研究方向为 5G 网络技术、边缘计算、多制式共享产品创新与标准制定" ]
网络出版日期:2020-06,
纸质出版日期:2020-06-20
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孟令彬, 李娟, 薛楠, 等. 5G边缘计算共享研究与展望[J]. 电信科学, 2020,36(6):38-44.
Lingbin MENG, Juan LI, Nan XUE, et al. Research and prospect of 5G edge computing sharing[J]. Telecommunications science, 2020, 36(6): 38-44.
孟令彬, 李娟, 薛楠, 等. 5G边缘计算共享研究与展望[J]. 电信科学, 2020,36(6):38-44. DOI: 10.11959/j.issn.1000-0801.2020171.
Lingbin MENG, Juan LI, Nan XUE, et al. Research and prospect of 5G edge computing sharing[J]. Telecommunications science, 2020, 36(6): 38-44. DOI: 10.11959/j.issn.1000-0801.2020171.
5G三大应用场景对网络的时延、带宽、连接、安全等方面提出了更高的要求,驱动着5G将网络、计算、存储、应用等核心能力下沉至网络边缘,而更靠近终端/用户的 5G 站址具有完备的机房、电力、运维等配套资源,将是5G边缘计算部署的最佳选择。基于点多面广的5G站址资源,结合边缘计算部署的体系架构,深入研究了多运营商 5G 边缘计算共享部署的可行性,提出了机房基础设施共享、IaaS 设施共享、PaaS平台共享3种可行的共建共享方案。通过统筹5G边缘计算发展需求,实现边缘计算的共建共享,可以大幅降低边缘计算的建设成本及运营成本,实现边缘计算的快速规模化发展,打造集约高效、经济适用、智能绿色、安全可靠的边缘计算体系。
The three application scenarios of 5G make forward higher requirements for network delay
bandwidth
connection and security
which drive 5G to sink the core capabilities of network
computing
storage and application to the edge of the network.The 5G base station which is closer to the terminal/user and has complete resources such as base station power
operation and maintenance will be the best choice for 5G edge computing deployment.Based on the multi-point 5G base station site resource and the architecture of edge computing deployment
the feasibility of multi-operator 5G edge computing shared deployment was studied
three feasible co-building and sharing schemes
such as base station infrastructure sharing
IaaS facility sharing and PaaS platform sharing were proposed.By coordinating the development needs of 5G edge computing and realizing the co-construction and sharing of edge computing
the construction cost and operation cost of edge computing can be greatly reduced
and the rapid scale development of edge computing can be realized
to build an intensive and efficient
economic and applicable
intelligent green
safe and reliable edge computing system.
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