Gain-based selection of ambient media services in pervasive environments

  • Authors:

  • M. Anwar Hossain;Pradeep K. Atrey;Abdulmotaleb El Saddik

  • Affiliations:

  • Multimedia Communications Research Laboratory, University of Ottawa, Ottawa, ON, Canada;Applied Computer Science, The University of Winnipeg, Winnipeg, MB, Canada;Multimedia Communications Research Laboratory, University of Ottawa, Ottawa, ON, Canada

  • Venue:
  • Mobile Networks and Applications
  • Year:
  • 2008

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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.