Cloud computing is the latest market-oriented computing paradigm which brings software design and development into a new era characterized by XaaS, i.e. everything as a service. Cloud workflows, as typical software applications in the cloud, are composed of a set of partially ordered cloud software services to achieve specific goals. However, due to the low QoS (quality of service) nature of the cloud environment, the design of workflow systems in the cloud becomes a challenging issue for the delivery of high quality cloud workflow applications. To address such an issue, this book presents a systematic investigation to the three critical aspects for the design of a cloud workflow system, viz. system architecture, system functionality and quality of service. Specifically, the system architecture for a cloud workflow system is designed based on the general four-layer cloud architecture, viz. application layer, platform layer, unified resources layer and fabric layer. The system functionality for a cloud workflow system is designed based on the general workflow reference model but with significant extensions to accommodate software services in the cloud. The support of QoS is critical for the quality of cloud workflow applications. This book presents a generic framework to facilitate a unified design and development process for software components that deliver lifecycle support for different QoS requirements. While the general QoS requirements for cloud workflow applications can have many dimensions, this book mainly focuses on three of the most important ones, viz. performance, reliability and security. In this book, the architecture, functionality and QoS management of our SwinDeW-C prototype cloud workflow system are demonstrated in detail as a case study to evaluate our generic design for cloud workflow systems. To conclude, this book offers a general overview of cloud workflow systems and provides comprehensive introductions to the design of thesystem architecture, system functionality and QoS management.

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Autorentext

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 System. 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 workflow, business process management and quality of service. Dong Yuan received the Bachelor degree in 2005 and Master degree in 2008 both from Shandong University, Jinan, China, all in Computer Science. He is currently a PhD student in the Faculty of Information and Communication Technologies at Swinburne University of Technology, Melbourne, Australia. His research interests include data management in workflow systems, scheduling and resource management, grid and cloud computing. Gaofeng Zhang received the Bachelor and Master degrees in Computer Science from Hefei University of Technology, Hefei, China, in 2005 and 2008 respectively. He is currently working toward the PhD degree in Information and Communication Technology under the supervision of A/Prof. Jinjun Chen and Prof. Yun Yang in Faulty of Information and Communication Technologies, Swinburne University of Technology, Melbourne, Australia. His research interests include privacy protection strategy, risk evaluation, and security mechanism in cloud computing. Wenhao Li obtained his Bachelor and Master degree of Engineering from Shan Dong University in China in 2007 and 2010 respectively. He participated in a program funds by National Natural Science Foundation of China during his postgraduate studies and published several papers in national and international journals. He is currently a first-year PhD candidate in Faculty of Information and Communication Technologies, Swinburne University of Technology, supervised by Prof. Yun Yang and A/Prof. Jinjun Chen. He s research interests include parallel and distributed computing, cloud and grid computing, workflow technologies and data management in distributed computing environment. Dahai Cao received his master degree in software engineering from Tsinghua University, Beijing, China, 2005. He is currently a PhD student in Swinburne University Centre for Computing and Engineering Software Systems, Melbourne, Australia. His research interests include cloud-based large-scale workflow management systems, adaptive workflow management and cloud computing. received his master degree in software engineering from Tsinghua University, Beijing, China, 2005. He is currently a PhD student in Swinburne University Centre for Computing and Engineering Software Systems, Melbourne, Australia. His research interests include cloud-based large-scale workflow management systems, adaptive workflow management and cloud computing. Qiang He received his first Ph. D. degree in information and communication technology from Swinburne University of Technology (SUT), Australia, in 2009 and his second Ph. D. degree in computer science and engineering from Huazhong University of Science and Technology (HUST), China, in 2010. He is now a research fellow at SUT. His research interests include services computing, cloud computing, P2P system, workflow management and agent technologies. 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 andapplications, workflow management and applications in Web service or SOC environments, workflow manag

Inhalt
Introduction.- Workflow Systems in the Cloud.- Cloud Workflow System Architecture.- Cloud Workflow System Functionality.- Cloud Workflow System Quality of Service.- Case Study: SWINDEW-C Cloud Workflow System.- Bibliography.- Appendices.