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Gain-based Selection of Ambient Media Services in Pervasive Environments

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Abstract

Providing ambient media services in the pervasive environments is a challenging issue. This is due to the fact that users have different satisfaction level in using different media services in varying contexts. We address this issue by proposing a gain-based media service selection mechanism. Gain refers to the extent a media service is satisfying to a user in a particular context. In our proposed mechanism, the gain is dynamically computed by adopting a user-centered approach that includes user’s context, profile, interaction history, and the reputation of a service. The dynamically computed gain is used in conjunction with the cost of using a service (e.g. media subscription and energy consumption cost) to derive our service selection mechanism. We adopt a combination of greedy and dynamic programming based solution to obtain a set of services that would maximize the user’s overall gain in the ambient environment by minimizing the cost constraint. Experimental results demonstrate the potential of this approach.

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Authors and Affiliations

  1. Multimedia Communications Research Laboratory, University of Ottawa, Ottawa, ON, Canada

    M. Anwar Hossain & Abdulmotaleb El Saddik

  2. Applied Computer Science, The University of Winnipeg, Winnipeg, MB, Canada

    Pradeep K. Atrey

Authors
  1. M. Anwar Hossain
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  2. Pradeep K. Atrey
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  3. Abdulmotaleb El Saddik
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Correspondence to M. Anwar Hossain.

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Hossain, M.A., Atrey, P.K. & El Saddik, A. Gain-based Selection of Ambient Media Services in Pervasive Environments. Mobile Netw Appl 13, 599–613 (2008). https://doi.org/10.1007/s11036-008-0092-y

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  • DOI: https://doi.org/10.1007/s11036-008-0092-y

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