Title
Computing Refined Ordering Relations with Uncertainty for Acyclic Process Models
Abstract
Since the behavior is the essential characteristic of business process models, and ordering relations between execution of tasks can be used to describe the behavior of process models, we need to compute the ordering relations between tasks in process models. This computation can be used for compliance checking and querying process models based on behavior. There are three basic types of ordering relations between two events in a concurrent system, i.e., causal, conflict, and concurrency. In this paper, we refine the causal and concurrency relations with uncertainty according to whether one task is always executed with the other task in the same instance. To compute the refined ordering relations with uncertainty efficiently, we propose some rules for adjacent tasks and some transitive laws for nonadjacent tasks together with their proofs. Based on these rules and laws, we propose an algorithm to compute the refined ordering relations for acyclic process models based on unfolding technology. The algorithm has a biquadrate time to the size of complete prefix unfolding of the original model.
Year
DOI
Venue
2014
10.1109/TSC.2013.19
IEEE T. Services Computing
Keywords
DocType
Volume
refined ordering relations,nonadjacent tasks,workflow,concurrency relation,unfolding technology,acyclic process models,concurrency control,uncertain,business process models,refine,prefix unfolding,ordering relation,Business process,task execution,transitive laws,concurrent system,causal relation,business data processing,biquadrate time,compliance checking,querying process models,query processing
Journal
7
Issue
ISSN
Citations 
3
1939-1374
2
PageRank 
References 
Authors
0.38
0
4
Name
Order
Citations
PageRank
Tao Jin1695.71
Jianmin Wang22446156.05
Lijie Wen345244.34
Gen Zou420.38