Architectural Models to Simplify Administration of Service-Oriented Applications

Pervasive applications are often executed in fluctuating conditions and need frequent adaptations to meet requirements. Autonomic computing techniques are frequently used to automate adaptations to changing execution conditions. However, some administration tasks still have to be performed by human administrators. Such tasks are very complex because of a lack of understanding of the system evolutions. In this paper, we propose to build and link models at runtime of supervised applications in order to simplify the administrators' job. Our approach is illustrated on a health application called actimetrics, developed with the Orange Labs.