Online Deployment Algorithms for Microservice Systems with Complex Dependencies
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Abstract (arXiv)
Cloud and edge computing have been widely adopted in many application scenarios. With the increasing demand of fast iteration and complexity of business logic, it is challenging to achieve rapid development and continuous delivery in such highly distributed cloud and edge computing environment. At present, microservice-based architecture has been the dominant deployment style, and a microservice system has to evolve agilely to offer stable Quality of Service (QoS) in the situation where user requirement changes frequently. Many research have been conducted to optimally re-deploy microservices to adapt to changing requirements. Nevertheless, complex dependencies between microservices and the existence of multiple instances of one single microservice in a microservice system have not been fully considered in existing works. This paper defines SPPMS, the Service Placement Problem in Microservice Systems that feature complex dependencies and multiple instances, as a Fractional Polynomial Problem (FPP) . Considering the high computation complexity of FPP, it is then transformed into a Quadratic Sum-of-Ratios Fractional Problem (QSRFP) which is further solved by the proposed greedy-based algorithms. Experiments demonstrate that our models and algorithms outperform existing approaches in both quality and computation speed.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jul 2021.
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Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.
- 2025Microservice Deployment in Space Computing Power Networks via Robust Reinforcement Learningcited by 1
- 2024Optimizing Airline Reservation Systems with Edge-Enabled Microservices: A Framework for Real-Time Data Processing and Enhanced User Responsivenesscited by 0
- 2026MCRL2: Multi-resource Cross-attention-based Representation Learning-augmented Reinforcement Learning for Cloud Microservice Schedulingcited by 0
- 2026MCRL2: Multi-resource Cross-attention-based Representation Learning-augmented Reinforcement Learning for Cloud Microservice Scheduling11 Sep 2026
- 2025Microservice Deployment in Space Computing Power Networks via Robust Reinforcement Learning8 Jan 2025
- 2024Optimizing Airline Reservation Systems with Edge-Enabled Microservices: A Framework for Real-Time Data Processing and Enhanced User Responsiveness19 Nov 2024