Dynamic Workload Management using SLAs and an e-Business Performance Prediction Framework

Distributed e-business application platforms such as the web services framework will require sophisticated workload management infrastructures for the matching of client requests to the most appropriate resources. This paper introduces a novel dynamic predictive framework that uses both historical data and analytical performance modelling to extrapolate a request’s predicted performance under varying workloads and conditions on different systems. Such a framework can facilitate a workload manager in maximising the extent to which service level agreements can be met. An e-business benchmark is used to demonstrate how predictions can be used to efficiently distribute clients across heterogeneous servers whilst meeting response time goals.