Abstract: Distributed systems and grid environments grew up rapidly in the past few years due to increasing number of users and applicability. In the past, performance of grid based system is evaluated by using Quality of Service (QoS). The information of customers experience with a service is being considered nowadays. QoS does not focus on the preferences of end-users of a service. To evade this issue, Quality of Experience (QoE) based on various assessment methods is used. QoE is a promising multifaceted field which is based on cognitive science, engineering science and economics, focused on the understanding of overall human quality requirements. QoE is a way of quantifying a customes experiences with a service. This study discusses about the novel approach for QoE prediction in a grid based environment. Experimental results show that the probability based machine learning approach outperforms compared to other Machine Learning (ML) approaches.
R. Rajeswari and N. Kasthuri, 2016. QOE Prediction in Grid Based Environment. Asian Journal of Information Technology, 15: 4567-4570.