Identification of Delay Thresholds Representing the Perceived Quality of Enterprise Applications

Abstract

Modern enterprise applications are often designed as distributed architectures, e.g., thin client computing and thus degradations in network related Quality of Service (QoS) parameters may also negatively impact the user-perceived Quality of Experience (QoE) of the application. In this work, we create a model to predict the perceived application quality based on measurements of objective technical parameters. For this, we gathered a data set in a cooperating enterprise over a timespan of nearly three months. As the obtained data set is subject to bias that originates from seasonal effects as well as a limited and predefined set of technical parameters, we further evaluate how to identify segments of the data that lead to misclassification. Last, we quantify the trade-off between the gain in the QoE prediction accuracy and the amount of filtered data.