Content adaptor selection models in Adaptation Management Framework

Abstract

Pervasive devices possess restricted capabilities in terms of processing, information display and network data rates due to their mobile nature. Therefore in order to provide content to users with pervasive devices, the quality of the media presentation often needs to be adjusted according the different characteristics of those devices, and it is not efficient for content and service providers to provide all sort of contents in advanced. That indicates the great importance of adaptation in pervasive computing environment. Adaptation Management Framework (AMF) has been proposed to provide an environment in which the content/services are personalized to the user's preferences automatically. In this paper, we look into one major complication in the design of the AMF, that is to select and combine appropriate adaptation operations as well as their concrete implementations which is called Adaptation Mechanisms. We proposed the use of two selection algorithm methods to fulfill the tasks. Their performances are evaluated and compared with respect to effectiveness and efficiency.