A prototype for view-based monitoring of BPEL processes

This report describes the initial version of a tool for business process monitoring based on process viewing techniques. The tool, Business Process Illustrator (BPI), has been developed in the course of a Diploma Thesis which has been conducted at the Institute of Architecture of Application Systems. BPI is a Web-based tool for monitoring the execution of business processes. It displays the current state of a process instance in form of a process graph which is refreshed regularly. The initial version of the prototype supports regular process monitoring of processes based on the Business Process Execution Language (BPEL), plus process view transformations to reduce complexity and to ease analysis of process instances

STATE PROPAGATION FOR BUSINESS PROCESS MONITORING ON DIFFERENT LEVELS OF ABSTRACTION

Modeling and execution of business processes is often performed on different levels of abstraction. For example, when a business process is modeled using a high-level notation near to business such as Event-driven Process Chains (EPC), a technical refinement step is required before the process can be executed. Also, model-driven process design allows modeling a process on high-level, while executing it in a more detailed and executable low-level representation such as processes defined in the Business Process Execution Language (BPEL) or as Java code. However, current approaches for graphical monitoring of business processes are limited to scenarios in which the process that is being executed and the process that is being monitored are either one and the same or on the same level of abstraction. In this paper, we present an approach to facilitate business-oriented process monitoring while considering process design on high-level. We propose process views for business process monitoring as projections of activities and execution states in order to support business process monitoring of running process instances on different levels of abstraction. In particular, we discuss state propagation patterns which can be applied to define advanced monitoring solutions for arbitrary graph-based process languages