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On Personalized Cloud Service Provisioning for Mobile Users Using Adaptive and Context-Aware Service Composition
United Arab Emirates University, Al-Ain, United Arab Emirates.ORCID iD: 0000-0001-9121-8766
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Distribuerade realtidssystem (DRTS), Distributed Real-Time Systems)ORCID iD: 0000-0002-7312-9089
Macquarie University, New South Wales, Australia .ORCID iD: 0000-0002-3326-4147
McGill University, Montreal, Canada.
2018 (English)In: Computing, ISSN 0010-485X, E-ISSN 1436-5057Article in journal (Refereed) Epub ahead of print
Abstract [en]

Cloud service providers typically compose their services from a number of elementary services, which are developed in- house or built by third-party providers. Personalization of composite services in mobile environments is an interesting and challenging issue to address, given the opportunity to factor-in diverse user preferences and the plethora of mobile devices at use in multiple contexts. This work proposes a framework to address personalization in mobile cloud-service provisioning. Service personalization and adaptation may be considered at different levels, including the user profile, the mobile device in use, the context of the user and the composition specification. The user’s mobile device and external services are typical sources of context information, used in our proposed algorithm to elicit context-aware services. The selection process is guided by quality-of-context (QoC) criteria that combine cloud-service provider requirements and user preferences. Hence, the paper proposes an integrated framework for enhancing personalized mobile cloud-services, based on a composition approach that adapts context information using a common model of service metadata specification.

Place, publisher, year, edition, pages
2018.
Keywords [en]
Personalization, Adaptive services, Mobile cloud computing, Composed services, Quality of context
National Category
Computer and Information Sciences
Research subject
Distributed Real-Time Systems
Identifiers
URN: urn:nbn:se:his:diva-15350DOI: 10.1007/s00607-018-0631-8OAI: oai:DiVA.org:his-15350DiVA, id: diva2:1214247
Available from: 2018-06-06 Created: 2018-06-06 Last updated: 2018-07-03

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Atif, Yacine

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CiteExportLink to record
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Output format
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