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Emergence of Composite Services in Smart Environments

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HAL Id: hal-02280356

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Submitted on 17 Sep 2019

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Emergence of Composite Services in Smart

Environments

Maroun Koussaifi, Walid Younes, Françoise Adreit, Jean-Paul Arcangeli,

Jean-Michel Bruel, Sylvie Trouilhet

To cite this version:

Maroun Koussaifi, Walid Younes, Françoise Adreit, Jean-Paul Arcangeli, Jean-Michel Bruel, et al..

Emergence of Composite Services in Smart Environments. 8th EuroScience Open Forum (ESOF

2018), Jul 2018, Toulouse, France. pp.0, 2018. �hal-02280356�

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This is an author’s version published in:

http://oatao.univ-toulouse.fr/22488

Official URL

DOI :

https://doi.org/10.13140/RG.2.2.21832.42248

Open Archive Toulouse Archive Ouverte

OATAO is an open access repository that collects the work of Toulouse

researchers and makes it freely available over the web where possible

To cite this version:

Koussaifi, Maroun and Younes, Walid

and Adreit, Françoise and Arcangeli, Jean-Paul and Bruel,

Jean-Michel and Trouilhet, Sylvie Emergence of Composite

Services in Smart Environments. (2018) In: 8th EuroScience

Open Forum (ESOF 2018), 9 July 2018 - 14 July 2018

(Toulouse, France).

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Emergence of Composite Services in Smart Environments

Maroun KOUSSAIFI, Walid YOUNES

Françoise ADREIT, Jean-Paul ARCANGELI, Jean-Michel BRUEL and Sylvie TROUILHET

University of Toulouse, France - Toulouse Institute of Computer Science Research firstname.lastname@irit.fr

Opportunistic Composition Engine “OCE”

Artificial Intelligence & Learning

Decentralized and automatic decision

Emergence of new composite services adapted to the context and the user

Connected objects in an ambient environment

Physical / software components Emergent service User Constant mobility Unpredictable needs Services Unpredictable availability Environment Uncertain Highly unstable

How to provide a working and relevant composite service?

Opportunistic Software Composition

How to let the user manipulate an emergent service?

Interactive Control Environment “ICE”

Current status

Future Work

Feedback generation by ICE

Full integration of OCEand ICE Methods and Tools

Announcement-based interaction protocol

Feedback exploitation byOCE Multi-Agent System

Environment-directed service composition

Dynamic and continuous adaptation Learning by reinforcement

Integration of new appearing services

Principles

Binding decision and feedback to the agent

Interface adaptation to the user

Consolidation of the learning mechanism in OCE

Scalability assessment Operational prototypes of

OCEandICE

Demonstration of simple use cases with real connected objects

Arduino, Android, Node.js, WComp…

Interactive Control Environment “ICE”

Model-Driven Engineering (MDE) Domain Specific Languages (DSL)

Eclipse Modeling Framework, GEMOC Model transformations

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