物联网学报2024，Vol.8Issue(4)：34-44,11.DOI:10.11959/j.issn.2096-3750.2024.00446
基于深度强化学习的多租户算网资源分配算法
Multi-tenant computing network resource allocation algorithm based on deep reinforcement learning
摘要
Abstract
With the rapid advancement of intelligent businesses,the pre-existing relationship between traditional network architectures and computing capabilities has made it difficult to meet the current demands,making the implementation of computing-network convergence inevitable.Under the new computing power network framework brought about by the convergence of computing networks,efficient and intelligent resource scheduling strategy has become a key link to im-prove user experience.However,the existing resource scheduling algorithms have a single optimization objective and can-not meet the differentiated business needs of multi-tenants.To this end,a Multi objective deep reinforcement learning re-source scheduling(MODRLRS)was proposed to call the computing resources and network resources in the computing power network.The algorithm performs multi-objective scheduling optimization of computing network resources by con-structing a Pareto optimal solution set to meet the personalized business needs of different tenants.Simulation experimen-tal results show that compared with other multi-objective resource scheduling algorithms,the proposed algorithm im-proves the request acceptance rate by 4.9%and the compliant delay request rate by 4.78%,which can flexibly adapt to the unique requirements of various computing services.关键词
算网融合/算力网络/资源调度/多目标优化/深度强化学习Key words
integration of computing and networking/computing power network/resource scheduling/multi objective optimization/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
胡宇翔,冯旭,董永吉,和孟佯,庄雷,宋艳蕊..基于深度强化学习的多租户算网资源分配算法[J].物联网学报,2024,8(4):34-44,11.基金项目
国家重点研发计划(No.2023YFB2903902) （No.2023YFB2903902）
中原科技创新领军人才项目(No.244200510038) （No.244200510038）
河南省科技攻关-嵩山实验室资助项目(No.232102210154)The National Key Research and Development Program of China(No.2023YFB2903902),The Science and Techno-logy Innovation Leading Talents Subsidy Project of Central Plains(No.244200510038),The Scientific and Technological Project in Henan Province-Pre-Research Project of Songshan Laboratory(No.232102210154). （No.232102210154）
