Modeling Data Transformations in Data-Aware Service Choreographies

Hahn, Michael; Breitenbücher, Uwe; Leymann, Frank; Wurster, Michael; Yussupov, Vladimir

doi:10.1109/edoc.2018.00014

Cited by 4 publications

(7 citation statements)

References 12 publications

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“…To decouple data flow and control flow modeling, TraDE [ 29 ] is a middleware which supports cross-partners data flows by using data objects and intermediate storage. The choreography model applies TraDE modeling extensions to replace the traditional message-based data exchange by a data-aware choreography [ 30 ]. Previous works of TraDe authors include the ChorSystem platform [ 23 ].…”

Section: Methodsmentioning

confidence: 99%

“…In recent years, service composition modeling under choreography paradigm has been addressed in several platforms such as CHOReOS [19,20] and its evolution into CHOReV-OLUTION [21]; ActnConnect [22]; ChorSystem [23]; and research works such as [24][25][26][27][28]. Extensions integrated within choreography add functionality oriented to different scenarios [29][30][31][32].…”

Section: Methodsmentioning

confidence: 99%

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A Service Discovery Solution for Edge Choreography-Based Distributed Embedded Systems

Clavero

Montón

Palanca-Barrio

et al. 2021

Sensors

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This paper presents a solution to support service discovery for edge choreography based distributed embedded systems. The Internet of Things (IoT) edge architectural layer is composed of Raspberry Pi machines. Each machine hosts different services organized based on the choreography collaborative paradigm. The solution adds to the choreography middleware three messages passing models to be coherent and compatible with current IoT messaging protocols. It is aimed to support blind hot plugging of new machines and help with service load balance. The discovery mechanism is implemented as a broker service and supports regular expressions (Regex) in message scope to discern both publishing patterns offered by data providers and client services necessities. Results compare Control Process Unit (CPU) usage in a request–response and datacentric configuration and analyze both regex interpreter latency times compared with a traditional message structure as well as its impact on CPU and memory consumption.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

A Service Discovery Solution for Edge Choreography-Based Distributed Embedded Systems

Clavero

Montón

Palanca-Barrio

et al. 2021

Sensors

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“…3represents data that need to be exchanged between processes. It indicates a common, consolidated and agreed set of data items representing a data contract between participating processes [11,12].…”

Section: Definition 4 (Business Process Collaboration Bpc)mentioning

confidence: 99%

“…The authors of [19] emphasize automating data exchange between processes use messages. Furthermore, Hahn et al [11] introduce TraDE to improve the flexibility of data modeling, supporting data exchange and runtime data change across processes. All cross process data items are exposed by participants in a web accessible way (e.g., through a REST API) [12].…”

Section: B Detecting Data Flow Errors In Bpcmentioning

confidence: 99%

“…In this paper, we propose a formal method based on BPMN to detect data flow errors across processes in BPC. Our method draws on the ideas from both detecting data flow errors within a single process [8] and TraDE [11,12]. The former describes the data dependencies among nodes within a single process based on operational data specification (read and write operations), which inspires us to further analyze data dependencies across processes and formalize data flow error patterns across processes.…”

Section: Introductionmentioning

confidence: 99%

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Detecting Data Flow Errors Across Processes in Business Process Collaboration

Xiong

Pan

et al. 2020

IEEE Access

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In business process collaboration (BPC), especially when it comes to message communication and data exchange, there are complex data dependencies among sender process, receiver process and messages. However, each participant of the overall BPC develops its part independently as a service, including its own communication part and data flow. As a result, data flow errors across processes may occur easily. In this paper, we propose a method based on BPMN to detect these errors caused by data dependency violations. Our method is inspired by the study of detecting data flow errors within a single process and focuses on a subset of the elements of the BPC model, without having to consider the complete set. In particular, we define a set of data flow error patterns by analyzing and formalizing data dependencies in order to clearly clarify and identify errors. Then we give the corresponding automatic detection algorithm. Finally, through two evaluations, we demonstrate the effectiveness of our proposal. INDEX TERMS Business process management, business process collaboration, data flow error across processes, data dependency.

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