Flexible Process Aware Information Systems (PAIS) and Autonomic Process Performance Improvement Research Line
Summary:
This research line builds on our expertise and previous work in adaptive workflows and workflow management systems and service compositions research. It focuses in on both concepts and realization approached for making PAIS more flexible, as well as enabling the autonomic process performance improvement on the level of process models and by the PAIS architecture and realizations. There are several sub-topics we address:
- Architectures, technologies and realizations of flexible PAIS
- Autonomous proactive adaptation of processes/service compositions/workflows
- Establishing the relationships between relevant KPIs, adaptation triggers and the adaptation mechanisms and patterns to react to KPI violations.
- KPIs are Key Performance Indicators and we consider both process performance indicators like execution times, cost, resource availability and others, as well as security properties and concerns in dynamic, Cloud-aware scenarios.
- Learning from process adaptation
Participants
- Dimka Karastoyanova
- Arash Yadegari
- Nafiseh Soveizi
Students:
- Ana Roman: MSc Thesis Adaptable Processes: Concepts, Design and Implementation in Camunda, 2021.
- Exi Xhelo: MSc Thesis: Building a software system to automate business
process adaptation,2021.
- Andris Jakubovskis: MSc Thesis: Defining, Deploying and Monitoring Process KPIs: Design and Implementation for the Camunda Process Engine.
Publications
- Yadegari Ghahderijani, A., & Karastoyanova, D. (2021). Autonomic Process Performance Improvement. In IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW) (pp. 299-307). (IEEE International Enterprise Distributed Object Computing Conference workshops). IEEE. https://doi.org/10.1109/EDOCW52865.2021.00061