The Interplay between QoE, User Behavior and System Blocking in QoE Management

In this position paper we highlight a shortcoming of current QoE management approaches that typically do not take into due account the resulting user behavior. As a result, a divergence is introduced between the predicted and the actual QoE, the later being affected by the reaction of the user to resource assignments. We believe the following two factors to be among those having the highest impact in this respect: the user (im)patience, and tolerance to low quality. To illustrate our claims, we model an example scenario where a user requests an online service, such as an online authentication service. The request is processed by a system with limited resources, which may also cause the request to be blocked or buffered, with a consequent impact on the QoE. Some aspects of aborting users, blocked users, and QoE of served users are investigated by means of a simple queueing system, M/M/s/n + M which takes impatience into account. Insights from this theoretical study show that an increase in the user patience results in a decrease of the average QoE in the system, as the user may consume system resources without waiting to be finally served. Based on these findings, we argue the importance of incorporating these aspects of quality, often ignored in both QoE modeling and management, into any QoE management system that is expected to improve the provider's bottom line.