Green Computing: A Case Study of Electricity Distribution in Jordan
Nada Al Sallami *
Department of Multimedia, Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan.
Ali Al daoud
Department of Computer Science, Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan.
Sarmad Al Alossi
Computer Information Systems Department, University of Financial and Banking Sciences, Amman, Jordan.
*Author to whom correspondence should be addressed.
Abstract
This paper used a modified Neural Network algorithm for green load balancing. The algorithm applied to electricity distribution problem of Jordan. Neural network learns to predict the demand of electricity in Jordan and allocates electricity according to that prediction. Back-propagation learning algorithm is used to train neural network. Training process depends on Electricity Distribution Parameters, which are: Sector Type, and Weather Type and Daytime. These parameters are selected with respect to Jordan nature. After training, the algorithm always maintains the active servers according to current values of these parameters. As a result, energy consumption will be low and Green computing is achieved.
Keywords: Electricity distribution, green cloud computing, load balancing, artificial neural network