DOI number:10.1109/TCC.2026.3689123
Journal:IEEE Transactions on Cloud Computing
Key Words:Microservices, Dynamic scheduling, Elastic scalability, Adaptive Awareness, Kubernetes
Abstract:With the pervasive adoption of microservices (MS) architecture, resource scheduling has become a pivotal factor in ensuring system performance, stability, and elasticity. However, current MS resource scheduling approaches frequently overlook the complexities inherent in MS architecture, particularly the interdependencies between MS instances and the rapid change of dynamic workload patterns, thus fail to meet multiple but conflict performance objectives simultaneously. To address these challenges, this paper introduces a dynamic MS scheduling model DMSM-ESAAI which integrates elastic scalability and adaptive awareness with Kubernetes' native scheduling and autoscaling pipeline at three levels: the instance and strategy levels of scheduling, and node level scaling. The experimental evaluations conducted on both real Kubernetes clusters and simulation environments demonstrated that the proposed model significantly outperforms traditional methods in terms of throughput, latency, and resource utilization, validating its effectiveness in dynamic MS environments.
Indexed by:Journal paper
Discipline:Engineering
Document Type:J
Translation or Not:no
Date of Publication:2026-06-18
Included Journals:SCI