Adaptability of a Deployment Decision Making System

In our living environments today, computer networks, computing devices, sensors and many other entities produce a large amount of data to be processed. This data comprise, for example, digital media content, news, computational resources like services, and much more. To be able to exploit this data, a (human or computer) user may utilize digital assistants. In this paper, we present such an assistant for deploying services and obtaining content data. We concentrate especially on how this assistant is able to adapt to changing situations, both, user-driven and in a self-adaptive manner. An experimental evaluation, based on real world digital video providers, demonstrates prerequisites, results, and potential of the various ways of adaptation within the presented approach.