Introducing the Vienna Platform for Elastic Processes

Schulte, Stefan; Hoenisch, Philipp; Venugopal, Srikumar; Dustdar, Schahram

doi:10.1007/978-3-642-37804-1_19

Cited by 19 publications

(12 citation statements)

References 27 publications

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“…These problems have to be addressed by an intermediary middleware delivered by the Cloud Manufacturing Platform [19], [20]. The according research question is: "What are the needed methodologies and instruments to establish the Cloud Manufacturing Platform, and how can we implement them?…”

Section: Methodology and Research Agendamentioning

confidence: 99%

Towards a methodology and instrumentation toolset for cloud manufacturing

Skarlat

Borkowski

Schulte

2016

2016 1st International Workshop on Cyber-Physical Production Systems (CPPS)

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Cloud Manufacturing is a recent concept to realize real-world manufacturing processes by applying a combination of well-known principles from the fields of Cloud Computing, Business Process Management (BPM), and Internet of Things (IoT) to the manufacturing domain. Cloud Manufacturing assumes using crowdsourcing and outsourcing types of business mobilization to transform local production-oriented manufacturing into global service-oriented manufacturing networks.While there have been a number of conceptual frameworks for Cloud Manufacturing, there is still a lack of concrete methodologies and instrumentation. Especially, the integration of generic Cyber-Physical Systems (CPS) shop floors and the support of manufacturing business processes in the Cloud have not been given full consideration yet. Within this paper, we intend to define a research agenda and according missing methodologies and instrumentation to ground a platform for Cloud Manufacturing.

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Section: Methodology and Research Agendamentioning

confidence: 99%

Towards a methodology and instrumentation toolset for cloud manufacturing

Skarlat

Borkowski

Schulte

2016

2016 1st International Workshop on Cyber-Physical Production Systems (CPPS)

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“…The service objectives are defined by a client in regard to cost and quality. Schulte et al take on this concept and suggest an advanced BPMS that incorporates these properties [13]. Dörnemann proposes a workflow system in which a process engine and a load balancer are enhanced to provide automatic and dynamic resource provisioning [14].…”

Section: B Related Workmentioning

confidence: 99%

Scalable Business Process Execution in the Cloud

Euting

Janiesch

Fischer

et al. 2014

2014 IEEE International Conference on Cloud Engineering

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Business processes orchestrate service requests in a structured fashion. Process knowledge, however, has rarely been used to predict and decide about cloud infrastructure resource usage. In this paper, we present an approach for BPM-aware cloud computing that builds on process knowledge to improve the timeliness and quality of resource scaling decisions. We introduce an IaaS resource controller based on fuzzy theory that monitors process execution and that is used to predict and control resource requirements for subsequent process tasks. In a laboratory experiment, we evaluate the controller design against a commercially available state-of-the-art auto scaler. Based on the results, we discuss improvements and limitations, and suggest directions for further research.

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“…2 presents the high-level architecture of ViePEP-C. The architecture of ViePEP-C is based on our former work, called ViePEP [7], [33], [34]. Since ViePEP is not able to utilize containers to enact business processes, ViePEP-C constitutes a complete revision of the software.…”

Section: General Approachmentioning

confidence: 99%

“…In our former work [7], [33], [34], we presented an eBPMS called ViePEP. ViePEP uses VMs for the execution of process activities on cloud resources.…”

Section: Related Workmentioning

confidence: 99%

ViePEP-C: A Container-Based Elastic Process Platform

Waibel

Hochreiner

Schulte

et al. 2021

IEEE Trans. Cloud Comput.

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Business Process Management Systems (BPMS) need to be able to take into account the fluctuating demand for computational resources during the execution of business process activities. Today, BPMS rely on the leasing and releasing of virtual machines (VMs) on cloud resources, which leads to a rather coarse-grained allocation of computational resources. This may result in an increase in the execution cost, flexibility restrictions, and a negative impact on the Quality of Service. In order to overcome these drawbacks, we introduce the Vienna Platform for Elastic Processes on Containers (ViePEP-C). ViePEP-C is an elastic BPMS that uses containers instead of VMs for the execution of business process activities on cloud resources, leading to a more fine-grained execution environment. To achieve this, ViePEP-C offers cloud controller, monitoring and business process execution functionalities and provides a platform for different resource and task scheduling algorithms. To evaluate the benefits of ViePEP-C, we further present a resource and task scheduling algorithm and show that, by using containers as execution environment, the execution cost can be decreased by over 20% (compared to a state-of-the-art VM-based scheduling algorithm) while considering a high service level.

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Introducing the Vienna Platform for Elastic Processes

Cited by 19 publications

References 27 publications

Towards a methodology and instrumentation toolset for cloud manufacturing

Towards a methodology and instrumentation toolset for cloud manufacturing

Scalable Business Process Execution in the Cloud

ViePEP-C: A Container-Based Elastic Process Platform

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