1. 紫金山实验室,江苏 南京 211111
2. 广东省新一代通信与网络创新研究院,广东 广州 510000
3. 北京邮电大学网络与交换技术国家重点实验室,北京 100876
[ "贾庆民(1990− ),男,山东泰安人,博士,紫金山实验室研究员,主要研究方向为边缘计算、边缘智能、算力网络、工业互联网" ]
[ "丁瑞(1984− ),男,江苏南京人,广东省新一代通信与网络创新研究院研究员,主要研究方向为软件定义网络、网络安全" ]
[ "刘辉(1983− ),男,江苏沛县人,博士,紫金山实验室研究员,主要研究方向为移动边缘计算、边缘智能技术、工业互联网" ]
[ "张晨(1992− ),男,辽宁兴城人,硕士,紫金山实验室研究员,主要研究方向为未来网络体系架构、软件定义网络、云网融合、云原生网络" ]
[ "谢人超(1984− ),男,福建南平人,博士,北京邮电大学教授、博士生导师,主要研究方向为信息中心网络、工业互联网、标识解析技术、边缘计算、无服务器计算" ]
网络首发:2021-10,
纸质出版:2021-10-15
移动端阅览
贾庆民, 丁瑞, 刘辉, 等. 算力网络研究进展综述[J]. 网络与信息安全学报, 2021,7(5):1-12.
Qingmin JIA, Rui DING, Hui LIU, et al. Survey on research progress for compute first networking[J]. Chinese Journal of Network and Information Security, 2021, 7(5): 1-12.
贾庆民, 丁瑞, 刘辉, 等. 算力网络研究进展综述[J]. 网络与信息安全学报, 2021,7(5):1-12. DOI: 10.11959/j.issn.2096-109x.2021034.
Qingmin JIA, Rui DING, Hui LIU, et al. Survey on research progress for compute first networking[J]. Chinese Journal of Network and Information Security, 2021, 7(5): 1-12. DOI: 10.11959/j.issn.2096-109x.2021034.
摘 要:随着新型网络业务和应用的不断发展与成熟,云计算、边缘计算、智能终端设备得到了快速发展,计算资源呈现出泛在部署的趋势,如何高效协同地利用这些泛在计算资源成为当前网络领域研究的一项重要新课题。在此背景下,算力网络(CFN,compute first networking)的概念被提出,并引起了广泛的关注,其基本思想是将算力和网络深度融合,协同分布式的计算资源,提升计算资源的利用率,同时改善用户的网络服务体验。首先分析了算力网络的提出背景和研究现状,然后介绍算力网络的基本架构、工作流程,以及算力网络的关键技术,最后对算力网络发展方向以及面临挑战进行分析。
With the development of 5G and mobile Internet technology
cloud computing
edge computing and intelligent terminal devices have been developed rapidly.Computing resources indicate a trend of ubiquitous deployment.How to use ubiquitous computing resources efficiently and collaboratively has become a hot topic at present in network field.In this context
the concept of compute first networking (CFN) has been proposed and attracted wide attention.Its basic idea is to enhance utilization of computing resources and improve user experience of network services
by converging computing and network deeply as well as coordinating distributed computing resources.Firstly the background and research status of CFN were analyzed
and then basic structure
workflow
and key technologies about CFN were explicated.Finally
future research directions and challenges about CFN were summarized.
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