Modelling, evaluation, and adaptive control of an instrumentation system

We present results from modeling and evaluating the JEWEL instrumentation system (IS), which is being used for runtime data collection from a distributed, real-time application. Our modeling and evaluation effort addresses two objectives: (1) providing early feedback to the system developers regarding the JEWEL IS configuration options for this application; and (2) evaluation of the design alternatives for an adaptive controller to control the overhead and intrusion of the JEWEL IS to a real-time video conferencing application. For JEWEL IS design, we compare two data collection and forwarding policies (collect-and-forward and batch-and-forward). For the design of the adaptive controller, we compare two adaptation policies (static and dynamic adaptation) and two policies to schedule the implementation of the control decisions (distributed and centralized scheduling). Results reported in this paper indicate that the batch-and-forward policy for IS design static adaptation policy with distributed scheduling for the adaptive controller design meet the domain-specific requirements