DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TSC.2013.38
Weiwei Qiu , Zhejiang University, Hangzhou
Zibin Zheng , The Chinese University of Hong Kong, Homg Kong
Xinyu Wang , Zhejiang University, Hangzhou
Xiaohu Yang , Zhejiang University, Hangzhou
Michael R. Lyu , The Chinese University of Hong Kong, Homg Kong
The on-demand use, high scalability, and low maintenance cost nature of cloud computing have attracted more and more enterprises to migrate their legacy applications to the cloud. Although the cloud platform itself promises high reliability, ensuring high quality of service is still one of the major concerns, since the enterprise applications are usually complicated and consist of a large number of distributed components. To address this problem, we propose a reliability-based optimization framework, named ROCloud, which employs the application structure information as well as the historical reliability information for component ranking. ROCloud includes two ranking algorithms. The first algorithm ranks components for the applications where all their components can be migrated to the cloud. The second algorithm ranks components for hybrid applications where only parts of their components can be migrated to the cloud. Based on the ranking result, optimal fault-tolerant strategy will be selected automatically for the most significant components with respect to their pre-defined constraints. The experimental results show that by refactoring a small number of error-prone components and tolerating faults of the most significant components, the reliability of the application can be greatly improved.
Software Reliability, Cloud Migration, Component Ranking, Fault Tolerance
W. Qiu, Z. Zheng, X. Wang, X. Yang and M. R. Lyu, "Reliability-Based Design Optimization for Cloud Migration," in IEEE Transactions on Services Computing.