Abstract

Workflow management systems (WFMS) that are geared for the orchestration of business processes across multiple organizations are complex distributed systems: they consist of multiple workflow engines, application servers, and communication middleware servers such as ORBs, where each of these server types can be replicated on multiple computers for scalability and availability. Finding an appropriate system configuration with guaranteed application-specific quality of service in terms of throughput, response time, and tolerable downtime is a major challenge for human system administrators. This paper presents a tool that largely automates the task of configuring a distributed WFMS. Based on a suite of mathematical models, the tool derives the necessary degrees of replication for the various server types in order to meet specified goals for performance and availability as well as "performability " when service is degraded due to outages of individual servers. The paper describes the configuration tool, with emphasis on how to capture the load behavior of workflows in a realistic manner. We also present extensive experiments that evaluate the accuracy of the tool's underlying models and demonstrate the practical feasibility of automating the task of configuring a distributed WFMS. The experiments use a detailed simulation which in turn has been validated through measurements with the Mentor-lite prototype system.

Citations