Tao Shi
ABSTRACT
The multi-cloud composite applications deployment problem (MCADP) aims to select proper cloud resources from multiple cloud providers at different locations to deploy applications with shared constituent services in order to optimize performance and cost. In this paper, we propose divide-and-conquer seeding strategies to find diverse and high-quality deployment plans as seeds. By using the real-world datasets, the experimental results demonstrate that the proposed seeding strategies can outperform recently proposed approaches, i.e. AO-Seed and SO-Seed, for MCADP.
- Tao Chen, Miqing Li, and Xin Yao. 2018. On the effects of seeding strategies: a case for search-based multi-objective service composition. In Proceedings of the Genetic and Evolutionary Computation Conference. ACM, 1419--1426.Google Scholar
Digital Library
- Kuo-Chan Huang and Bo-Jun Shen. 2015. Service deployment strategies for efficient execution of composite SaaS applications on cloud platform. Journal of Systems and Software 107 (2015), 127--141.Google ScholarDigital Library
- Tao Shi, Hui Ma, and Gang Chen. 2019. A Genetic-Based Approach to Location-Aware Cloud Service Brokering in Multi-Cloud Environment. In 2019 IEEE International Conference on Services Computing (SCC). IEEE, 146--153.Google ScholarCross Ref
- T. Shi, H. Ma, G. Chen, and S. Hartmann. 2020. Location-Aware and Budget-Constrained Service Deployment for Composite Applications in Multi-Cloud Environment. IEEE Transactions on Parallel and Distributed Systems 31, 8 (2020), 1954--1969.Google ScholarCross Ref
Index Terms
- Divide and conquer: Seeding strategies for multi-objective multi-cloud composite applications deployment
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