Scalable Business Process Research Articles

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

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.

Measuring Scalable Business Process Model Complexity Based on Basic Control Structure

The business process model is a representation of business activities illustrated through diagram notations. This model is composed of repeated specific patterns called basic control structure. Each basic control structure has a level of complexity. The metrics for formulating existing complexity are very diverse, but can only define complexity partially and are less sensitive to small changes in the structure of the business process model. In this paper, we propose a formula of complexity metric that can indicate small changes in structure, type of branching logic, number of branches, loops, and depth. We call it the Yaqin complexity formula. To get the Yaqin complexity formula, we carried out several activities. These activities are identifying the metrics involved using the Goal-Question-Metric (GQM) method, then formulating the metric complexity, the next activity is testing the formula with several business process models and analyzing the test results, and then validating the Yaqin complexity formula using the Weyuker's properties framework. The Yaqin complexity formula, which involves seven parameters, is proven to be more comprehensive than other complexity formulas that involve less than seven parameters. The Yaqin complexity formula also proved to be more sensitive to other complexity formulas, where 7 out of 8 cases affected the Yaqin complexity metric. The validation results state that the Yaqin complexity formula meets 8 of 9 Weyuker's properties. Thus we have succeeded in formulating the Yaqin complexity, which is more comprehensive in involving parameters and more sensitive in detecting small changes in the structure of the business process model.

Performance Measurement Based on Coloured Petri Net Simulation of Scalable Business Processes

Performance Measurement Based on Coloured Petri Net Simulation of Scalable Business Processes

An Overview of Cloud Implementation in the Manufacturing Process Life Cycle

The advancement of information and communication technology (ICT) has changed the structure and functions of various sectors and it has also started to play a significant role in modern manufacturing in terms of computerized machining and cloud manufacturing. It is important for industries to keep up with the current trend of ICT for them to be able survive and be competitive. Cloud manufacturing is an approach that wanted to realize a real-world manufacturing processes that will apply the basic concept from the field of Cloud computing to the manufacturing domain called Cloud-based manufacturing (CBM) or cloud manufacturing (CM). Cloud manufacturing has been recognized as a new paradigm for manufacturing businesses. In cloud manufacturing, manufacturing companies need to support flexible and scalable business processes in the shop floor as well as the software itself. This paper provides an insight or overview on the implementation of cloud manufacturing in the modern manufacturing processes and at the same times analyses the requirements needed regarding process enactment for Cloud manufacturing and at the same time proposing a STEP-NC concept that can function as a tool to support the cloud manufacturing concept.

Evolution of distributed monitoring for scalable business process management in cloud-based databases

Embodying business process as a service (BPaaS) in cloud computing has been actively investigated by many research studies. There are many proposals to establish the scalable workflows, for instance, by adopting the multiple instances of workflow execute engine (WEE). However, it is difficult to track exactly the states of individual instances of the workflow running across multiple engines globally, by only applying the multiple WEE. It is necessary to implement an independent monitoring function from outside. This study considers making this monitoring function scalable in accordance with increasing the number of WEE. When designing the monitoring function and the maintenance protocol, the following important factors have been considered. First, to deliver the meta-data such as definitions of business processes among WEE for sharing. The second, to deliver the event instances asynchronously, by compensating inconsistent status for recoverable events. This study proposes architecture and a set of maintenance protocols to realise the scalable workflow management. It shows the critical requirements and selects a reasonable approach through qualitative evaluations.