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Design and Realisation of Scalable Business Process Management Systems for Deployment in the Cloud

Published: 08 September 2021 Publication History

Abstract

Business Process Management Systems (BPMSs) provide automated support for the execution of business processes in modern organisations. With the emergence of cloud computing, BPMS deployment considerations are shifting from traditional on-premise models to the Software-as-a-Service (SaaS) paradigm, aiming at delivering Business Process Automation as a Service. However, scaling up a traditional BPMS to cope with simultaneous demand from multiple organisations in the cloud is challenging, since its underlying system architecture has been designed to serve a single organisation with a single process engine. Moreover, the complexity in addressing both the dynamic execution environment and the elasticity requirements of users impose further challenges to deploying a traditional BPMS in the cloud. A typical SaaS often deploys multiple instances of its core applications and distributes workload to these application instances via load balancing. But, for stateful and often long-running process instances, standard stateless load balancing strategies are inadequate. In this article, we propose a conceptual design of BPMS capable of addressing dynamically varying demands of end users in the cloud, and present a prototypical implementation using an open source traditional BPMS platform. Both the design and system realisation offer focused strategies on achieving scalability and demonstrates the system capabilities for supporting both upscaling, to address large volumes of user demand or workload, and downscaling, to release underutilised computing resources, in a cloud environment.

References

[1]
Mourad Amziani, Tarek Melliti, and Samir Tata. 2012. A generic framework for service-based business process elasticity in the cloud. In Proceedings of the 10th International Conference on Business Process Management (BPM’12). 194–199.
[2]
Rajkumar Buyya, Satish Narayana Srirama, Giuliano Casale, Rodrigo N. Calheiros, Yogesh Simmhan, Blesson Varghese, Erol Gelenbe, Bahman Javadi, Luis Miguel Vaquero, Marco A. S. Netto, Adel Nadjaran Toosi, Maria Alejandra Rodriguez, Ignacio Martín Llorente, Sabrina De Capitani di Vimercati, Pierangela Samarati, Dejan S. Milojicic, Carlos A. Varela, Rami Bahsoon, Marcos Dias de Assunção, Omer Rana, Wanlei Zhou, Hai Jin, Wolfgang Gentzsch, Albert Y. Zomaya, and Haiying Shen. 2019. A manifesto for future generation cloud computing: Research directions for the next decade. ACM Computing Survey 51, 5 (2019), 105:1–105:38.
[3]
Frederick Chong and Gianpaolo Carraro. 2006. Architecture strategies for catching the long tail. MSDN Library (April 2006).
[4]
Marlon Dumas, Marcello La Rosa, Jan Mendling, and Hajo A. Reijers. 2018. Fundamentals of Business Process Management (2nd ed.). Springer.
[5]
Schahram Dustdar, Yike Guo, Benjamin Satzger, and Hong Linh Truong. 2011. Principles of elastic processes. IEEE Internet Computing 15, 5 (2011), 66–71.
[6]
Seven Euting, Christian Janiesch, Robin Fischer, Stefan Tai, and Ingo Weber. 2014. Scalable business process execution in the cloud. In 2014 IEEE International Conference on Cloud Engineering. 175–184.
[7]
Vincenzo Ferme, Ana Ivanchikj, and Cesare Pautasso. 2016. Estimating the cost for executing business processes in the cloud. In International Conference on Business Process Management. Springer, 72–88.
[8]
V. Ferme, A. Ivanckikj, C. Pautasso, M. Skouradaki, and F. Leymann. 2016. A container-centric methodology for benchmarking workflow management systems. In Proceedings of the 6th International Conference on Cloud Computing and Service Science. SciTePress, 74–84.
[9]
Terry Halpin. 2015. Object-Role Modeling Fundamentals: A Practical Guide to Data Modeling with ORM. Technics Publications, LLC.
[10]
Alan R. Hevner, Salvatore T. March, Jinsoo Park, and Sudha Ram. 2004. Design science in information systems research. MIS Quarterly 28, 1 (2004), 75–105.
[11]
Philipp Hoenisch, Dieter Schuller, Stefan Schulte, Christoph Hochreiner, and Schahram Dustdar. 2016. Optimization of complex elastic processes. IEEE Transactions on Services Computing 9, 5 (2016), 700–713.
[12]
Philipp Hoenisch, Stefan Schulte, Schahram Dustdar, and Srikumar Venugopal. 2013. Self-adaptive resource allocation for elastic process execution. In 2013 IEEE 6th International Conference on Cloud Computing. 220–227.
[13]
David Hollingsworth. 1995. Workflow Management Coalition: The Workflow Reference Model. Technical Report TC00-1003.
[14]
Kiranbir Kaur, Sandeep Sharma, and Karanjeet Singh Kahlon. 2017. Interoperability and portability approaches in inter-connected clouds: A review. ACM Computing Surveys 50, 4 (2017), 49:1–49:40.
[15]
OMG. December, 2017. OMG Unified Modeling Language (OMG UML), Version 2.5.1. Technical Report. https://www.omg.org/spec/UML/2.5.1/PDF.
[16]
Milinda Pathirage, Srinath Perera, Indika Kumara, and Sanjiva Weerawarana. 2011. A multi-tenant architecture for business process executions. In 2011 IEEE International Conference on Web Services. IEEE, 121–128.
[17]
Guillaume Rosinosky, Samir Youcef, and F. Charoy. 2017. Efficient migration-aware algorithms for elastic BPMaaS. In Proceedings of the 15th International Conference on Business Process Management (BPM’17). 147–163.
[18]
Stefan Schulte, Christian Janiesch, Srikumar Venugopal, Ingo Weber, and Philipp Hoenisch. 2015. Elastic business process management: State of the art and open challenges for BPM in the cloud. Future Generation Computer Systems 46 (2015), 36–50.
[19]
D. M. M. Schunselaar, H. M. W. Verbeek, H. A. Reijers, and W. M. P. van der Aalst. 2014. YAWL in the cloud: Supporting process sharing and variability. In International BPM Conference Workshops. Springer, 367–379.
[20]
M. Skouradaki, V. Ferme, C. Pautasso, F. Leymann, and A. van Hoorn. 2016. Micro-benchmarking BPMN 2.0 workflow management systems with workflow patterns. In 28th International Conference on Advanced Information Systems Engineering. Springer, 67–82.
[21]
Yutian Sun, Jianwen Su, and Jian Yang. 2016. Universal artifacts: A new approach to business process management (BPM) systems. ACM Transactions on Management Information Systems 7, 1 (2016), 3:1–3:26.
[22]
Arthur H. M. ter Hofstede, Wil M. P. van der Aalst, Michael Adams, and Nick Russell (Eds.). 2010. Modern Business Process Automation—YAWL and Its Support Environment. Springer.
[23]
W. M. P. van der Aalst and A. H. M. ter Hofstede. 2005. YAWL: Yet another workflow language. Information Systems 30, 4 (June 2005), 245–275.
[24]
Wil M. P. van der Aalst, Arthur H. M. ter Hofstede, Bartek Kiepuszewski, and Alistair P. Barros. 2003. Workflow patterns. Distributed and Parallel Databases 14, 1 (2003), 5–51.
[25]
John Venable. 2006. A framework for design science research activities. In 2006 Information Resource Management Association International Conference. Idea Group Publishing, 184–187.
[26]
Mathias Weske. 2019. Business Process Management—Concepts, Languages, Architectures. (3rd ed.) Springer.

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      cover image ACM Transactions on Management Information Systems
      ACM Transactions on Management Information Systems  Volume 12, Issue 4
      December 2021
      225 pages
      ISSN:2158-656X
      EISSN:2158-6578
      DOI:10.1145/3483349
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      New York, NY, United States

      Publication History

      Published: 08 September 2021
      Accepted: 01 April 2021
      Revised: 01 March 2021
      Received: 01 October 2019
      Published in TMIS Volume 12, Issue 4

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      Author Tags

      1. Business process management systems
      2. software-as-a-service
      3. scalability
      4. business process engine
      5. load balancing

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      • Refereed

      Funding Sources

      • Research Foundation of Science and Technology Plan Project in Guangdong Province
      • Australian Research Council Discovery

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      • (2022)InteliRank: A Four-Pronged Agent for the Intelligent Ranking of Cloud Services Based on End-Users’ FeedbackSensors10.3390/s2212462722:12(4627)Online publication date: 19-Jun-2022

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