计算机技术与发展2026，Vol.36Issue(8)：1-9,9.DOI:10.20165/j.cnki.ISSN1673-629X.2026.0039
基于DQDG与DA-DDPG的容器分组调度算法研究
Container Grouping and Scheduling Algorithm Based on DQDG and DA-DDPG
摘要
Abstract
We address the container scheduling challenge in edge computing,where low-latency online tasks and delay-tolerant offline tasks with complex inter-container dependencies require mixed deployment.To overcome the lack of quantitative dependency assessment and low fragmented resource utilization,we propose an optimized strategy based on the Dependency Quantification and Grouping Algorithm(DQDG)and the Dependency-Aware Deep Deterministic Policy Gradient(DA-DDPG).the proposed method begins by constructing a multi-metric model to precisely quantify dependency strength.The DQDG then groups strongly interdependent containers to minimize cross-node communication.Subsequently,the DA-DDPG enhances the experience replay and policy network by incorporating dependency information for long-term optimal scheduling.Experimental results confirm that the proposed method ensures online service quality while significantly improving cluster load balancing and fragmented resource utilization,offering an end-to-end solution for deploying heterogeneous tasks with complex dependencies in edge environments.关键词
边缘场景/容器调度/依赖强度量化/容器分组算法/深度强化学习Key words
edge scenario/container scheduling/dependency intensity quantification/container grouping algorithm/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
汪学镜,齐凤亮,光晓俐,顾进广..基于DQDG与DA-DDPG的容器分组调度算法研究[J].计算机技术与发展,2026,36(8):1-9,9.基金项目
国家重点研发计划(2022YFC3300801) （2022YFC3300801）
