Abstract: This paper discusses a proposed load balance technique based on artificial neural network. It distributes workload equally across all the nodes by using back propagation learning algorithm to train feed forward Artificial Neural Network (ANN). The proposed technique is simple and it can work efficiently when effective training sets are used. ANN predicts the demand and thus allocates resources according to that demand. Thus, it always maintains the active servers according to current demand, which results in low energy consumption than the conservative approach of over-provisioning. Furthermore, high utilization of server results in more power consumption, server running at higher utilization can process more workload with similar power usage. Finally the existing load balancing techniques in cloud computing are discussed and compared with the proposed technique based on various parameters like performance, scalability, associated overhead... etc. In addition energy consumption and carbon emission perspective are also considered to satisfy green computing.

Nada M. Al Sallami, Ali Al daoud and Sarmad A. Al Alousi, “Load Balancing with Neural Network” International Journal of Advanced Computer Science and Applications(IJACSA), 4(10), 2013. http://dx.doi.org/10.14569/IJACSA.2013.041021

@article{Sallami2013,
title = {Load Balancing with Neural Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.041021},
url = {http://dx.doi.org/10.14569/IJACSA.2013.041021},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {10},
author = {Nada M. Al Sallami and Ali Al daoud and Sarmad A. Al Alousi}
}