Runtime Performance Modeling and Measurement of Adaptive Distributed Object Applications

Distributed applications that can adapt at runtime to changing quality of service (QoS) require a model of the expected QoS and of the possible application adaptations. QoS models in turn require runtime measurements, both inband and out-of-band, from across the application’s components. As the comprehensiveness of the model increases, so does the quality of adaptation. But eventually the increasing comprehensiveness becomes too complex for the QoS Designer to deal with effectively. In addition, performance models of any complexity are expensive to create and maintain at runtime. The QoS Designer therefore needs a set of distributed-QoS tools to assist in the construction of models, the handling of quality vs. complexity tradeoffs, and the efficient maintenance of models at runtime. This paper describes the Quality Objects (QuO) middleware support that provides for developing a performance model; collecting and organizing run-time measurements of a system, both in-band and outof-band; and maintaining the model at runtime in an efficient way.