标题：A cost-optimal service selection approach for collaborative workflow execution in clouds
作者：Wei, Yi ;Pan, Li ;Yuan, Dong ;Liu, Shijun ;Wu, Lei ;Meng, Xiangxu
作者机构：[Wei, Yi ;Pan, Li ;Liu, Shijun ;Wu, Lei ;Meng, Xiangxu ] School of Computer Science and Technology, Shandong University, Jinan; 250101, China;[Yuan, D 更多
会议名称：20th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016
会议日期：4 May 2016 through 6 May 2016
来源：Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016
关键词：cloud computing; collaborative workflow; Infrastructure as a Service; service selection
摘要：Today, there has been a strong demand of distributed collaboration in design and manufacturing, due to the acceleration of economic globalization and the popularity of virtual enterprises (VE) model. Because of the characteristics of cloud computing, such as elasticity and on-demand computing, it is promising to deploy and execute collaborative workflows that contain multiple tasks and services such as Computer-Aided Design (CAD) software components on cloud resources for supporting collaboration across enterprises. Specifically, how to cost-effectively select appropriate services to execute workflows within deadlines while without violating multiple constraints becomes an important issue. In this paper, through investigating the practical requirements of collaborative design workflow, we first formulate the issue of the cost-optimal cloud service selection for collaborative workflow executions as a multi-dimensional optimization problem with multiple constraints. Then we propose an effective approach based on genetic algorithms to address this problem for obtaining near-optimal solutions. Based on workload data derived from real-world systems, we conduct experiments which show that our approach outperforms traditional greedy algorithms in finding better solutions and it also provides real-time performance guarantees in real-world cloud computing environments. © 2016 IEEE.