Temporal QOS Management in Scientific Cloud Workflow Systems

1. Introduction
2. Literature Review and Problem Analysis
3. A Scientific Cloud Workflow System
4. Novel Probabilistic Temporal Framework
5. Forecasting Scientific Cloud Workflow Activity Duration Intervals
6. Temporal Constraint Setting
7. Temporal Checkpoint Selection and Temporal Verification
8. Temporal Violation Handling Point Selection
9. Temporal Violation Handling
10. Conclusions and Contribution
Bibliography
Appendix: Notation Index

Xiao Liu received his PhD degree in Computer Science and Software Engineering from the Faculty of Information and Communication Technologies at Swinburne University of Technology, Melbourne, Australia in 2011. He received his Master and Bachelor degree from the School of Management, Hefei University of Technology, Hefei, China, in 2007 and 2004 respectively, all in Information Management and Information Systems. He is currently a postdoctoral research fellow in the Centre of Computing and Engineering Software System at Swinburne University of Technology. His research interests include workflow management systems, scientific workflows, cloud computing, business process management and quality of service.Jinjun Chen received his PhD degree in Computer Science and Software Engineering from Swinburne University of Technology, Melbourne, Australia in 2007. He is currently an Associate Professor in the Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia. His research interests include Scientific workflow management and applications, workflow management and applications in Web service or SOC environments, workflow management and applications in grid (service)/cloud computing environments, software verification and validation in workflow systems, QoS and resource scheduling in distributed computing systems such as cloud computing, service oriented computing, semantics and knowledge management, cloud computing.