TY  - JOUR
T1  - QOE Prediction in Grid Based Environment
AU - Rajeswari, R. AU - Kasthuri, N. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 22
SP  - 4567
EP  - 4570
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.4567.4570
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.4567.4570
KW  - Grid computing
KW  -load balancing
KW  -data mining
KW  -prediction
KW  -QoE
AB  - 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 customer’s 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 custome’s 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.
ER  -