Dynamic Microservice Resource Optimization Management Based on MAPE Loop
Microservice resource management aims to ensure stable service instance loads and improve overall resource utilization through load balancing, elastic scaling, and container orchestration while meeting system service quality requirements.Existing research often focuses on localized solutions, addressing only single aspects of elastic scaling or load balancing without recognizing the systemic nature of microservice resource management. TTe complexity and dynamism of service dependencies make it challenging to quantify interactions between resource strategies and service loads. Additionally, microservice systems experience dynamic load variations inffuenced by user behavior, business activities, and external factors. TTe dynamic nature of load changes and the selection of load featuressigniffcantly increase the difffculty ofresource forecasting, further complicating microservice resource management. To address this problem, this paper proposes MDRM (MAPEbased Dynamic Resource Management), a dynamic optimization method that integrates load balancing and elastic scaling to overcome the limitations of isolated strategies. MDRM models system load based on business characteristics and service invocation relationships, accurately capturing dynamic variations. A composite model, combining parallel multi-layer CNNs and LSTMs, extracts spatiotemporal microservice features, enhancing resource forecasting accuracy. Additionally, MDRM formulates a comprehensive load balancing optimization function that synergizes with resource utilization and service response time objectives to generate optimal management strategies.Experimental results demonstrate that, compared to default resource management strategies in Docker Swarm and Kubernetes, MDRM signiffcantly improves system throughput (approximately 1000 RPS) and reduces response time (approximately 30–40 ms), proving its effectiveness.
Sat 21 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
16:00 - 17:30 | Session9: AloT & MicroservicesResearch Track / Tool Demonstration Track at Cosmos 3C Chair(s): Qingkai Shi Nanjing University | ||
16:00 15mTalk | EnvGuard: Guaranteeing Environment-Centric Safety and Security Properties in Web of Things System Research Track Bingkun Sun Fudan University, Jialin Ren Fudan University, Juntao Luo Fudan University, Liwei Shen Fudan University, Yongqiang Lu Fudan University, Qicai Chen Fudan University, China, Zhen Dong Fudan University, Xin Peng Fudan University | ||
16:30 15mTalk | Privacy-Preserving Authentication Scheme for V2G in social IoT Based on Certificateless Aggregate Signatures Research Track Zhuoqun Xia Changsha University of Science and Technology, Xin Wang Changsha University of Science and Technology | ||
16:45 15mTalk | To Split or to Merge? Exploring Multi-modal Data Flexibly for Failure Classification in Microservices Research Track Xiuhong Tan Changsha University of Science and Technology, China, Tongqing Zhou National University of Defense Technology, China, Yuan Yuan National University of Defense Technology, China, Shiming He Changsha University of Science and Technology, China, Yuqi Li National Supercomputer Center in Tianjin, Jian Zhang National Supercomputer Center in Tianjin | ||
17:00 15mTalk | Dynamic Microservice Resource Optimization Management Based on MAPE Loop Research Track Lu Wang Xidian University, Xu Fan Xidian University, Yaxiao Li , Quanwei Du Xidian University, Jialuo She Xidian University, Qingshan Li Xidian University | ||
17:15 10mTalk | Documenting Microservice Integration with MSAdoc Tool Demonstration Track | ||
Cosmos 3C is the third room in the Cosmos 3 wing.
When facing the main Cosmos Hall, access to the Cosmos 3 wing is on the left, close to the stairs. The area is accessed through a large door with the number “3”, which will stay open during the event.