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https://hdl.handle.net/2440/139144
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Type: | Journal article |
Title: | Online Deployment Algorithms for Microservice Systems with Complex Dependencies |
Author: | He, X. Tu, Z. Wagner, M. Xu, X. Wang, Z. |
Citation: | IEEE Transactions on Cloud Computing, 2023; 11(2):1-1 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Issue Date: | 2023 |
ISSN: | 2168-7161 2168-7161 |
Statement of Responsibility: | Xiang He, Zhiying Tu, Markus Wagner, Xiaofei Xu, and Zhongjie Wang |
Abstract: | 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, the 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. A lot of 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 together have not been fully considered in existing work. This article 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 our proposed greedy-based algorithms. Experiments demonstrate that our models and algorithms outperform existing approaches in both qualities of the generated solutions and computation speed. |
Keywords: | Cloud computing; microservice systems; multiple instance coexistence; service dependencies; service placement |
Rights: | © 2022 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. |
DOI: | 10.1109/TCC.2022.3161684 |
Grant ID: | http://purl.org/au-research/grants/arc/DP200102364 http://purl.org/au-research/grants/arc/DP210102670 |
Published version: | http://dx.doi.org/10.1109/tcc.2022.3161684 |
Appears in Collections: | Computer Science publications |
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