I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams
Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
ACM DIGITAL LIBRARY
Abstract
Online conformance checking deals with finding discrepancies be tween real-life and modeled behavior on data streams. The current
state-of-the-art output of online conformance checking is a prefix alignment, which is used for pinpointing the exact deviations in
terms of the trace and the model while accommodating a trace’s
unknown termination in an online setting. Current methods for
producing prefix-alignments are computationally expensive and
hinder the applicability in real-life settings.
This paper introduces a new approximate algorithm – I Will
Survive (IWS). The algorithm utilizes the trie data structure to
improve the calculation speed, while remaining memory-efficient.
Comparative analysis on real-life and synthetic datasets shows
that the IWS algorithm can achieve an order of magnitude faster
execution time while having a smaller error cost, compared to the
current state of the art. In extreme cases, the IWS finds prefix alignments roughly three orders of magnitude faster than previous
approximate methods. The IWS algorithm includes a discounted
decay time setting for more efficient memory usage and a look ahead limit for improving computation time. Finally, the algorithm
is stress tested for performance using a simulation of high-traffic
event streams.
Description
Keywords
online conformance checking, event-based
Citation
Raun, K., Tommasini, R. and Awad, A. (2023) “I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams,” in Proceedings of the 17th ACM International Conference on Distributed and Event-based Systems.