Intelligent adaptation and integrated scheduling method for computing and networking resources - Weiting ZHANG; Chenghui SUN; Hongchao WANG; Jianing DAI (Dianxin kexue)
To effectively support the development needs of the deep integration of networking and computing, a novel computing and network convergence architecture has emerged.In this context, how to realize the intelligent perception of computing and networking resources and the efficient scheduling of computational tasks are key problems.To this end, the new network scenario for computing and networking convergence were analyzed, a scheduling model for computing tasks and nodes was designed, and a deep reinforcement learning-based resource scheduling algorithm was proposed.The proposed algorithm was able to intelligently make scheduling decisions that minimize the system cost by sensing key information such as user devices, available capacity of computing and networking resources, and link status.Finally, the effectiveness of the proposed algorithm in saving system cost was verified by simulation experiments.