数据与计算发展前沿 ›› 2020, Vol. 2 ›› Issue (4): 55-64.

doi: 10.11871/jfdc.issn.2096-742X.2020.04.005

所属专题： 下一代互联网络技术与应用

• 专刊：下一代互联网络技术与应用（下） • 上一篇    下一篇

CPN：一种计算/网络资源联合优化方案探讨

雷波(),赵倩颖()   

  1. 中国电信股份有限公司研究院,北京 102209
  • 收稿日期:2020-03-20 出版日期:2020-08-20 发布日期:2020-09-10
  • 通讯作者: 雷波
  • 作者简介:雷波,中国电信股份有限公司研究院实验室运营中心（北京）,高级工程师,主任助理,同时担任CCSA“网络 5.0技术标准推进委员会”管理与运营组组长等职务。目前主要研究方向为未来网络架构、新型IP网络技术等。
    本文主要承担工作为CPN整体架构设计及应用研究。
    Lei Bo is a senior Engineer and the director assistant of Laboratory Operations Center, China Telecom Co., Ltd. Research Institute (Beijing), and concurrently works as the management and operation team leader of CCSA TC614 “Network 5.0 Technical Standards Promotion Committee”. His currently research interests include future network architecture, and new IP network technology, etc.
    In this paper he is mainly responsible for the overall framework design and application research of CPN.
    E-mail: leibo@chinatelecom.cn|赵倩颖,中国电信股份有限公司研究院实验室运营中心（北京）,科研人员,研究生毕业于比萨大学和圣安娜高等研究学院,主要研究方向未来网络、算力网络。
    本文主要承担工作为,相关工作、相关技术发展介绍、展望与下一步工作的编写,以及文中的翻译工作。
    Zhao Qianying is a researcher of Laboratory Operations Center, China Telecom Co., Ltd. Research Institute (Beijing). She received master degree from university of Pisa and la Scuola Superiore Sant’Anna. Her currently research interests include future network, and computing power network, etc.
    In this paper she is responsible for the related work introduction, related technologies introduction, outlooks and translations.
    E-mail: zhaoqy50@chinatelecom.cn
  • 基金资助:
    国家重点研发计划(2018YFB1800100)

CPN: A joint Optimization Solution of Computing/Network Resources

Lei Bo(),Zhao Qianying()   

  1. Research institute of China Telecom, Beijing 102209, China
  • Received:2020-03-20 Online:2020-08-20 Published:2020-09-10
  • Contact: Lei Bo

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摘要：

【目的】伴随5G和人工智能（Artificial Intelligence,AI）技术的飞速发展,各类型的应用不断涌现,不同应用对计算和网络都有着特定要求。为了给用户提供更好的体验,需要为不同应用提供满足需求的计算资源和确定性的网络资源,因此计算资源与网络资源的联合优化成为一个重要的研究领域。【文献范围】文章重点调研了计算资源与网络资源联合优化的解决方案,以及相关案例在现网中的应用等。【方法】本文给出一种计算/网络资源联合优化方案：算力网络（Computing Power Network,CPN）,阐述基于CPN的实验验证平台的整体架构,并给出了相关关键技术以及典型应用示例。【结果】CPN将计算资源信息与网络资源信息有机关联在一起,能够针对客户需求提供联合优化方案以及组织相应的资源调度工作。【局限】计算/网络资源联合优化涉及多个领域的研究,CPN作为一种新型解决方案,还面临很多的挑战,需要根据业务需求与商业模式的发展,不断地完善和发展。【结论】算力网络能够有效应对未来业务对计算、存储、网络甚至算法资源的多级部署以及在各级节点之间的灵活调度,获得了相关领域专家的认可,已经在国际电信联盟电信标准分局（International Telecommunication Union Telecommunication Standardization Sector,ITU-T）、中国通信标准化协会（China Communications Standards Association,CCSA）等国际国内标准组织中立项进行标准化研究。

关键词: 计算资源, 网络资源, 联合优化, 算力网络

Abstract:

[Objective] With the rapid development of 5G and AI, various types of applications appear and have the specific requirements for computing power and network. To provide users with better service experience, it is necessary to provide various applications with sufficient computing and deterministic network resources. Therefore, the joint optimization of computing and network resources is of an important research interest. [Scope of the literature] The article focuses on the joint optimization solution of computing/network resources as well as the related use cases adopted in current network. [Methods] This paper presents a joint optimization solution for computing/network resources allocation, namely computing power network (CPN), and introduces the architecture of the test platform based on the CPN as well as the key technologies and typical instances. [Results] The CPN combines the information of computing and network resources, which enables joint optimization solution and scheduling of relevant resources on the basis of user requirements. [Limitations] The joint optimization solution involves many fields. As a new solution, it faces many challenges and needs to be further improved and developed, according to different service requirements and business modalities. [Conclusions] The CPN can schedule the computing, storage, network and algorithm resources among multi-stage nodes. It has been recognized by experts in related fields and the standardization work has been carried out in international and domestic standard organizations such as ITU-T and CCSA.

Key words: computing resources, network resources, joint optimization, computing power network