A Probabilistic Framework for Automatic and Dependable Adaptation in Dynamic Environments

Distributed protocols executing in uncertain environments, like the Internet, had better adapt dynamically to environment changes in order to preserve QoS. In earlier work, it was shown that QoS adaptation should be dependable, if correctness of protocol properties is to be maintained. More recently, some ideas concerning specific strategies and methodologies for improving QoS adaptation have been proposed. In this paper we describe a complete framework for dependable QoS adaptation. We assume that during its lifetime, a system alternates periods where its temporal behavior is well characterized, with transition periods during which a variation of the environment conditions occurs. Our method is based on the following: if the environment is generically characterized in analytical terms, and we can detect the alternation of these stable and transient phases, we can improve the effectiveness and dependability of QoS adaptation. To prove our point we provide detailed evaluation results of the proposed solutions. Our evaluation is based on synthetic data flows generated from probabilistic distributions, as well as on real data traces collected in various Internet-based environments. Our results show that the proposed strategies can indeed be effective, allowing protocols to adapt to the available QoS in a dependable way.