Enhancing Business Process Flexibility by Flexible Batch Processing

Pufahl, Luise; Karastoyanova, Dimka

doi:10.1007/978-3-030-02610-3_24

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…The more recent adaptation approaches are focusing on service compositions/orchestrations, e.g. aspect based adaptation using process fragments [22], Model-as-you-Go approach for rewinding and repeating of service composition logic [29], service substitution [21], batch processing of process instances [30] with focus on BPMN, and others. The available solutions do not realize a generic solution of identifying the adaptation triggers and mapping the predicted violation to a specific type of trigger, but rather either follow a technology and implementation-specific path or simply allow for a user to both trigger the adaptation and specify the type of adaptation to be performed.…”

Section: Process Execution Environmentmentioning

confidence: 99%

Autonomic Process Performance Improvement

Ghahderijani

Karastoyanova

2021

2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW)

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The main motivation for the extraordinary advances in the field of predictive process monitoring has been to enable data-driven prediction of potential violations in process performance and the subsequent improvement of processes in organizations through continuous process re-engineering in enterprises. The contribution of predictive process monitoring is instrumental and is a first step stone towards automating process performance improvement. Building on the advances in predictive process monitoring, in this paper we focus on the next steps towards autonomic process performance improvement. The other essential contribution towards this goal is served partly by the research in the field of process adaptation and flexibility. We show that the link and interplay between predictive monitoring and process adaptation, both in terms of underlying concepts and technological realization, have been inadequately researched, as revealed by our review of existing literature, leaving a huge gap towards completely automating the reaction to predictions produced by runtime monitoring techniques, or business experts for that matter. We also define and present a functional architecture that aims at assisting enterprises in developing solutions and the research communities when positioning their research findings in the broader fields of predictive process monitoring, process adaptation and enterprise architectures. Towards that goal, we also contribute a road map highlighting potential pitfalls and pointing to best engineering practices towards the realization of autonomic process performance improvement in enterprise systems.

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Section: Process Execution Environmentmentioning

confidence: 99%

Autonomic Process Performance Improvement

Ghahderijani

Karastoyanova

2021

2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW)

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Microservice compositions based on the choreography of BPMN fragments: facing evolution issues

2022

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Business Processes (BPs) are commonly used by organizations to describe their goals. However, the existent decentralization found in many organizations forces them to build such BPs by coordinating distributed and fragmented BPs. Within this context, microservices arise as a very interesting and convenient way to address the implementation of such processes due to their low coupling characteristic. In this case, the coordination of such fragmented BPs is usually achieved by means of event-based choreographies. One of the main challenges to be faced by choreographies is their evolution due to the complexity that introduces the need of integrating changes among autonomous and independent partners. We face the challenge of evolving a microservice composition that is globally defined in a BPMN model but executed through a choreography of BPMN fragments. We introduce a protocol to manage the propagation of a change done by one microservice to be integrated into both the BPMN fragments of the rest of the microservices and the global BPMN model. This protocol also supports the negotiation among participants and the automatic suggestion of model adaptations to maintain the functional integrity of the composition. These suggestions are supported by a catalogue of adaptation rules that precisely characterize every possible change and propose actions to be considered by the affected microservices. All the evolution process is done at the modelling level, without managing hard-coded implementations. We have developed specific tools to facilitate the practical adoption of this protocol, and we have validated our work in an experiment with users. We can conclude that the proposed approach is effective to evolve microservice compositions implemented as event-based choreography of BPMN fragments from the local perspective of one partner.

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Configurable Batch-Processing Discovery from Event Logs

Pika

Ouyang

Hofstede

2022

ACM Trans. Manage. Inf. Syst.

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Batch processing is used in many production and service processes and can help achieve efficiencies of scale; however, it can also increase inventories and introduce process delays. Before organizations can develop good understanding about the effects of batch processing on process performance, they should be able to identify potential batch-processing behavior in business processes. However, in many cases such behavior may not be known; for example, batch processing may be occasionally performed during certain time frames, by specific employees, and/or for particular customers. This article presents a novel approach for the identification of batching behavior from process execution data recorded in event logs. The approach can discover different types of batch-processing behaviors and allows users to configure batch-processing characteristics they are interested in. The approach is implemented and evaluated through experiments with synthetic event logs and case studies with real-life event logs. The evaluation demonstrates that the approach can identify various batch-processing behaviors in the context of business processes.

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Enhancing Business Process Flexibility by Flexible Batch Processing

Cited by 3 publications

References 27 publications

Autonomic Process Performance Improvement

Autonomic Process Performance Improvement

Microservice compositions based on the choreography of BPMN fragments: facing evolution issues

Configurable Batch-Processing Discovery from Event Logs

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