Using AI Planning and Late Binding for Managing Service Workflows in Intelligent Environments

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dc.contributor.authorBidot, Julien
dc.contributor.authorGoumopoulos, Christos
dc.contributor.authorCalemis, Ioannis
dc.date.accessioned2019-10-27T21:26:30Z
dc.date.available2019-10-27T21:26:30Z
dc.date.issued2011
dc.departmentEge Üniversitesien_US
dc.descriptionIEEE International Conference on Pervasive Computing and Communications (PerCom) -- MAR 21-25, 2011 -- Seattle, WAen_US
dc.description.abstractIn this paper, we present an approach to aggregating and using devices that support the everyday life of human users in ambient intelligence environments. These execution environments are complex and changing over time, since the devices of the environments are numerous and heterogeneous, and they may appear or disappear at any time. In order to appropriately adapt the ambient system to a user's needs, we adopt a service-oriented approach; i.e., devices provide services that reflect their capabilities. The orchestration of the devices is actually realized with the help of Artificial Intelligence planning techniques and dynamic service binding. At design time, (i) a planning problem is created that consists of the user's goal to be achieved and the services currently offered by the intelligent environment, (ii) the planning problem is then solved using Hierarchical Task Network and Partial-Order Causal-Link planning techniques, (iii) and from the planning decisions taken to find solution plans, abstract service workflows are automatically generated. At run time, the abstract services are dynamically bound to devices that are actually present in the environment. Adaptation of the workflow instantiation is possible due to the late binding mechanism employed. The paper depicts the architecture of our system. It also describes the modeling and the life cycle of the workflows. We discuss the advantages and the limit of our approach with respect to related work and give specific details about implementation. We present some experimental results that validate our system in a real-world application scenario.en_US
dc.description.sponsorshipIEEE, Natl Sci Fdn (NSF), Microsoft Res, IBM, QUALCOMMen_US
dc.description.sponsorshipEC's 7th FP [216837]; Transregional Collaborative Research CentreMinistry of Education and Science, Spain [SFB/TRR 62]; German Research Foundation (DFG)German Research Foundation (DFG)en_US
dc.description.sponsorshipThe research leading to these results has received funding from the ECs 7th FP under grant agreement no 216837 and from the Transregional Collaborative Research Centre SFB/TRR 62 Companion-Technology for Cognitive Technical Systems funded by the German Research Foundation (DFG).en_US
dc.identifier.endpage163en_US
dc.identifier.isbn978-1-4244-9529-0
dc.identifier.issn2474-2503
dc.identifier.startpage156en_US
dc.identifier.urihttps://hdl.handle.net/11454/44972
dc.identifier.wosWOS:000299123100018en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2011 Ieee International Conference on Pervasive Computing and Communications (Percom 2011)en_US
dc.relation.ispartofseriesInternational Conference on Pervasive Computing and Communications
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHierarchical Task Network planningen_US
dc.subjectPartial-Order Causal-Link planningen_US
dc.subjectadaptive workflowsen_US
dc.subjectdynamic service bindingen_US
dc.subjectambient intelligenceen_US
dc.subjectontologyen_US
dc.subjectservices composition frameworken_US
dc.titleUsing AI Planning and Late Binding for Managing Service Workflows in Intelligent Environmentsen_US
dc.typeConference Objecten_US

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