A JEE-Based Modelling and Execution Environment for Workflow Applications with Just-in-Time Service Selection

2009 ◽  
Author(s):  
Pawel Czarnul
Keyword(s):  
Service Selection ◽  
Just In Time ◽  
Time Service ◽  
Execution Environment

scholarly journals Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing ‡

2018 ◽  
Author(s):  
Luca Mazzola ◽  
Philipp Waibel ◽  
Patrick Kaphanke ◽  
Matthias Klusch
Keyword(s):  
Business Process ◽  
Process Analysis ◽  
Building Blocks ◽  
Process Models ◽  
Just In Time ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Time Service ◽  
Business Process Models ◽  
Service Oriented

A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Architectures (SOA), this requirement induces a need for agile collaboration among supply chain partners, but also between different divisions or branches of the same company. In order to address this collaboration challenge, we~propose a novel pragmatic approach for the process analysis, implementation and execution. This~is achieved through sets of semantic annotations of business process models encoded into BPMN 2.0 extensions. Building blocks for such manufacturing processes are the individual available services, which are also semantically annotated according to the Everything-as-a-Service (XaaS) principles and stored into a common marketplace. The optimization of such manufacturing processes combines pattern-based semantic composition of services with their non-functional aspects. This is achieved by means of Quality-of-Service (QoS)-based Constraint Optimization Problem (COP) solving, resulting in an automatic implementation of service-based manufacturing processes. The produced solution is mapped back to the BPMN 2.0 standard formalism by means of the introduced extension elements, fully detailing the enactable optimal process service plan produced. This approach allows enacting a process instance, using just-in-time service leasing, allocation of resources and dynamic replanning in the case of failures. This proposition provides the best compromise between external visibility, control and flexibility. In this way, it provides an optimal approach for business process models' implementation, with a full service-oriented taste, by implementing user-defined QoS metrics, just-in-time execution and basic dynamic repairing capabilities. This paper presents the described approach and the technical architecture and depicts one initial industrial application in the manufacturing domain of aluminum forging for bicycle hull body forming, where the advantages stemming from the main capabilities of this approach are sketched.

scholarly journals Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing

2018 ◽  
Author(s):  
Luca Mazzola ◽  
Philipp Waibel ◽  
Patrick Kaphanke ◽  
Matthias Klusch
Keyword(s):  
Business Process ◽  
Process Analysis ◽  
Building Blocks ◽  
Process Models ◽  
Just In Time ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Time Service ◽  
Business Process Models ◽  
Service Oriented

A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Architectures (SOA), this requirement induces a need for agile collaboration among supply chain partners, but also between different divisions or branches of the same company. In order to address this collaboration challenge, we propose a novel pragmatic approach for the process analysis, implementation and execution. This is achieved through sets of semantic annotations of business process models encoded into BPMN 2.0 extensions. Building blocks for such manufacturing processes are the individual avaialble services, which are also semantically annotated according to the Everything-as-a-Service (XaaS) principles and stored into a common marketplace. The optimization of such manufacturing processes combines pattern-based semantic composition of services with their non-functional aspects. This is achieved by means of Quality-of-Services (QoS) based constraint optimization problem (COP) solving, resulting in an automatic implementation of service-based manufacturing processes. The produced solution is mapped back to the BPMN 2.0 standard formalism by the means of introduced extension elements, fully detailing the enactable optimal process service plan produced. This approach allows enacting a process instance, using just-in-time service leasing, allocation of resources, and dynamic replanning in case of failures. This proposition provides the best compromise between external visibility, control and flexibility. In this way, it provides an optimal approach for business process models implementation, with a full service-oriented taste, by implementing user-defined QoS metrics, just-in-time execution and basic dynamic repairing capabilities. This paper presents the described approach, the technical architecture and depicts one initial industrial application in the manufacturing domains of aluminum forging for bicycle hull body forming, where the advantages stemming from the main capabilities of this approach are sketched.

Composite Service Reselection Method in Correlation Context

2015 ◽  
Vol 12 (2) ◽  
pp. 73-97 ◽  
Author(s):  
Yuesong Zhang ◽  
Bin Zhang ◽  
Changsheng Zhang
Keyword(s):  
Service Providers ◽  
Service Selection ◽  
Quality Of Services ◽  
Mining Method ◽  
Composite Service ◽  
Research Issues ◽  
Service Computing ◽  
The Core ◽  
Execution Environment

Reselection of composite service is one of the core research issues in service computing field. In practical scenarios, because of business relations between service providers or the restrictions of service physical deployment environment, there may be correlation among services. Its existence affects the quality of services used together, makes corresponding abstract services potentially correlating with each other. This leads the QoS used to determine the bindings between abstract and concrete services to be inaccurate, and the selected services would not be the optimal one in actual execution environment. In this paper, the QoS-Correlation services are extracted from the execution log through Apriori data mining method. Then, the authors capture the correlated abstract services to present such correlations in a higher level of abstraction regardless of actual services. In the final, the correlated abstract services will be regarded as a task unit, and the corresponding correlation services of each task unit as its candidate services set. They also propose a correlation-aware service selection method in the paper. The method includes runtime reselection whenever the actual QoS largely deviates from the estimates.

scholarly journals Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing ‡

Information ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 279 ◽  
Author(s):  
Luca Mazzola ◽  
Philipp Waibel ◽  
Patrick Kaphanke ◽  
Matthias Klusch
Keyword(s):  
Business Process ◽  
Process Analysis ◽  
Building Blocks ◽  
Process Models ◽  
Just In Time ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Time Service ◽  
Business Process Models ◽  
Service Oriented

A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Architectures (SOA), this requirement induces a need for agile collaboration among supply chain partners, but also between different divisions or branches of the same company. In order to address this collaboration challenge, we propose a novel pragmatic approach for the process analysis, implementation and execution. This is achieved through sets of semantic annotations of business process models encoded into BPMN 2.0 extensions. Building blocks for such manufacturing processes are the individual available services, which are also semantically annotated according to the Everything-as-a-Service (XaaS) principles and stored into a common marketplace. The optimization of such manufacturing processes combines pattern-based semantic composition of services with their non-functional aspects. This is achieved by means of Quality-of-Service (QoS)-based Constraint Optimization Problem (COP) solving, resulting in an automatic implementation of service-based manufacturing processes. The produced solution is mapped back to the BPMN 2.0 standard formalism by means of the introduced extension elements, fully detailing the enactable optimal process service plan produced. This approach allows enacting a process instance, using just-in-time service leasing, allocation of resources and dynamic replanning in the case of failures. This proposition provides the best compromise between external visibility, control and flexibility. In this way, it provides an optimal approach for business process models’ implementation, with a full service-oriented taste, by implementing user-defined QoS metrics, just-in-time execution and basic dynamic repairing capabilities. This paper presents the described approach and the technical architecture and depicts one initial industrial application in the manufacturing domain of aluminum forging for bicycle hull body forming, where the advantages stemming from the main capabilities of this approach are sketched.

Just-in-time Training for Medical Emergencies: Computer Versus Paper Checklists for a Tracheal Intubation Task

2007 ◽  
Author(s):  
F. Jacob Seagull ◽  
Danny Ho ◽  
James Radcliffe ◽  
Yan Xiao ◽  
Peter Hu ◽  
...  
Keyword(s):  
Tracheal Intubation ◽  
Just In Time ◽  
Medical Emergencies
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