IoT-Based Compliance Checking of Multi-party Business Processes Modeled with Commitments - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2017

IoT-Based Compliance Checking of Multi-party Business Processes Modeled with Commitments

Marco Montali
  • Function : Author
  • PersonId : 940651
Pierluigi Plebani
  • Function : Author
  • PersonId : 1007091

Abstract

In a multi-party business process, the choreography defines the conversational protocol among the parties, so that the visibility of the parties’ private processes is limited to the set of operations required to respect such a protocol. Especially in scenarios where physical resources are exchanged, knowing how a resource owned by a party is managed in the premises of another party is not possible. Thus, possible misalignments can be detected too late. At the same time, IoT is increasingly adopted to enact business processes in many domains: e.g., logistics, manufacturing, healthcare. As, with IoT, smart devices can physically flow through the different parties involved in a process, their sensing capabilities can be exploited to improve the process compliance checking. With this work we propose an approach for compliance checking that mixes commitments and smart devices. Commitments, declaratively defining mutual contractual relationships between parties, drive the configuration of smart devices that, flowing along with the process flow, check their satisfaction and, in case of misalignment, timely inform the involved parties.
Fichier principal
Vignette du fichier
449571_1_En_14_Chapter.pdf (3.12 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01677611 , version 1 (08-01-2018)

Licence

Attribution

Identifiers

Cite

Marco Montali, Pierluigi Plebani. IoT-Based Compliance Checking of Multi-party Business Processes Modeled with Commitments. 6th European Conference on Service-Oriented and Cloud Computing (ESOCC), Sep 2017, Oslo, Norway. pp.179-195, ⟨10.1007/978-3-319-67262-5_14⟩. ⟨hal-01677611⟩
50 View
77 Download

Altmetric

Share

Gmail Facebook X LinkedIn More