| Title |
Developing Cloud Computing Time Slot-availability Predictions Using an Artificial Neural Network |
| Authors |
Alanazi Rayan;Muhammad Ashfaq khan;Fawaz Alhazemi;Hamoud Alshammari;Yunmook Nah |
| DOI |
https://doi.org/10.5573/IEIESPC.2020.9.1.049 |
| Keywords |
Artificial neural network; Resource management; Cloud computing; Data center |
| Abstract |
Over the last decade, cloud computing has exponentially transformed the ways of computing. In spite of its various advantages, cloud computing suffers from several challenges that affect performance. Two of the fundamental challenges are power consumption and dynamic resource scaling. An efficient resource allocation strategy could help cloud computing to improve overall performance and operational costs. In this paper, we design a novel approach to available time slot prediction in a data node, based on an artificial neural network (ANN), which predicts the time at which the required resources will be available. We conducted experiments on several nodes, obtaining up to 98%, and outperforming state-of-the-art available time slot prediction approaches. We claim that available time?slot prediction for cloud computing based on an ANN will lead to optimum resource allocation and to minimizing energy consumed while maintaining the essential performance level. |