Frontiers of Data and Computing ›› 2020, Vol. 2 ›› Issue (4): 55-64.doi: 10.11871/jfdc.issn.2096-742X.2020.04.005

• Special Issue: Next Generation Internet Technology & Application • Previous Articles     Next Articles

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;


[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