Prediction Strategies for Proactive Management in Dynamic Distributed Systems

Abstract

In real-life distributed systems, dynamic changes are unavoidable properties because of the degeneration or improvement in system performance. Hence to understand the dynamic changes and to "catch the trend" of the changes in distributed systems will be very important for distributed systems management. In order to model the dynamic changes in distributed systems, temporal extensions of Bayesian networks are employed to address the temporal factors and to model the dynamic changes of managed entities and the dependencies between them. Furthermore, the prediction capabilities are investigated by means of the relevant inference techniques when the imprecise and dynamic management information occurs in the distributed system.