Exploring the impact of iaccuracy and imprecision of QoS assumptions on proactive constraint-based QoS prediction for service orchestrations

Constraint-based Quality of Service (QoS) prediction is a method for predicting violations of Service Level Agreements (SLAs) in an executing instance of a service orchestration. It uses assumptions about the ranges of QoS values for component services in the orchestration. Experiments suggest that the method, when given correct component QoS assumptions, produces highly accurate predictions according to a series of quality-of-prediction metrics, and that it does so well ahead of the time when the prediction is to happen. We study the behavior of this method when the component QoS assumptions become incorrect or too vague. We conclude that the effect is a graceful deterioration in prediction quality, unless gross (order-of-magnitude) imprecisions are introduced. However, the method is very sensitive to the loss of information on the lower bounds for component QoS values, since the knowledge of the upper bounds is not sufficient for failure predictio