Abstract:

[Objective] With the development of the digital economy and the emergence of new industry application scenarios, the demand for computing resources in the whole society grows continually. The gradual implementation of several national strategies such as the East-West Computing Requirement Transfer project has been promoting the development of advanced network technologies represented by the computing power network (CPN). At present, the computing resources in the network are ubiquitous, belonging to various owners. Therefore, the matching of computing resource demand for diverse computing resources has become an important research direction. [Methods] This paper presents a method for the matching of computing service demand based on computing power identification and a unique method of computing power identification based on computing-network convergence, where the matching of computing service demand is achieved by using the hierarchical mapping of the communication address of the computing resources, the acquisition of computing resource information and the combined information of computing and network. [Results] By combining communication properties and computing properties of the computing resources, the system matches the optimal computing resources for the computing resource consumers. The computing power identification is flexible and universal in describing the properties of the computing resources comprehensively. [Limitations] The research on computing power measurement and computing power identification is at the early stage and facing the complexity and diversity of computing resources. In the future, it can be further improved with the progress in research and standardization work. [Conclusions] Computing power identification proposed in this paper can completely describes the properties of the computing resources and achieve management of the computing resources in the network and the matching of computing service demand, which is the basis of computing power scheduling and joint management of computing and network.

Key words: computing power network, computing-network convergence, computing service, computing power identification