A distributed server architecture supporting dynamic resource provisioning for BPM-oriented workflow management systems

  • Authors:

  • Ching-Hong Tsai;Kuo-Chan Huang;Feng-Jian Wang;Chun-Hao Chen

  • Affiliations:

  • Department of Computer Science, National Chiao-Tung University, No. 1001, Ta-Hsueh Road, Hsinchu, Taiwan;Department of Computer and Information Science, National Taichung University, No. 140, Min-Shen Road, Taichung, Taiwan;Department of Computer Science, National Chiao-Tung University, No. 1001, Ta-Hsueh Road, Hsinchu, Taiwan;Department of Computer Science, National Chiao-Tung University, No. 1001, Ta-Hsueh Road, Hsinchu, Taiwan

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

Workflow management systems have been widely used in many business process management (BPM) applications. There are also a lot of companies offering commercial software solutions for BPM. However, most of them adopt a simple client/server architecture with one single centralized workflow-management server only. As the number of incoming workflow requests increases, the single workflow-management server might become the performance bottleneck, leading to unacceptable response time. Development of parallel servers might be a possible solution. However, a parallel server architecture with a fixed-number of servers cannot efficiently utilize computing resources under time-varying system workloads. This paper presents a distributed workflow-management server architecture which adopts dynamic resource provisioning mechanisms to deal with the probable performance bottleneck. We implemented a prototype system of the proposed architecture based on a commercial workflow management system, Agentflow. A series of experiments were conducted on the prototype system for performance evaluation. The experimental results indicate that the proposed architecture can deliver scalable performance and effectively maintain stable request response time under a wide range of incoming workflow request workloads.