Dynamic QoS-Aware Scheduling Framework for Microservice in Edge Computing

Cross machine traffic caused by distributed microservice deployment in edge computing significantly affects service performance. And the dynamics of the edge computing, such as fluctuating user request patterns and different network delay make static scheduling stategies challenging. To address these two issue, we first propose a Cross-Machine Traffic-Aware Scheduling Algorithm (CTSA), which models the microservice deployment process as a Markov Decision Process and utilizes a Dueling DQN-based approach to minimize cross-machine traffic while balancing node resource usage. Furthermore, we propose a Dynamic QoS-Aware Scheduling Framework (DQSF) that adapts deployment decisions in real time based on system monitoring to address the challenge of dynamics. Experimental evaluations using a real-world microservice application show that our approach significantly reduces request response time up to 30.2%, improves throughput to 36.7% and ensure Quality of Service (QoS) under dynamic edge computing continuum.