Multi-criteria content adaptation service selection broker

In this paper, we propose a service-oriented content adaptation framework and an approach to the Content Adaptation Service Selection (CASS) problem. In particular, the problem is how to assign adaptation tasks (e.g., transcoding, video summarization, etc) together with respective content segments to appropriate adaptation services. Current systems tend to be mostly centralized suffering from single point failures. The proposed algorithm consists of a greedy and single objective assignment function that is constructed on top of an adaptation path tree. The performance of the proposed service selection framework is studied in terms of efficiency of service selection execution under various conditions. The results indicate that the proposed policy performs substantially better than the baseline approach.