Using Quantitative Analysis to Implement Autonomic IT Systems

The software underpinning today's IT systems needs to adapt dynamically and predictably to rapid changes in system workload, environment and objectives. The authors describe a software framework that achieves such adaptiveness for IT systems whose components can be modeled as Markov chains. The framework comprises an autonomic architecture that uses Markov-chain quantitative analysis to dynamically adjust the parameters of an IT system in line with its state, environment and objectives; and a method for developing instances of this architecture for real-world systems.