An energy-efficient self-provisioning approach for cloud resources management

In recent years, energy conservation has become a major issue in information technology. Cloud computing is an emerging model for distributed utility computing and is being considered as an attractive opportunity for saving energy through central management of computational resources. Obviously, a substantial reduction in energy consumption can be made by powering down servers when they are not in use. This work presents a resources provisioning approach based on an unsupervised predictor model in the form of an unsupervised, recurrent neural network based on a self-organizing map. Another unique feature of our work is a resources administration strategy for energy saving in the cloud. Such a strategy is implemented as a selfadministration module. We show that the proposed approach gives promising results.