In this work, we take the approach of identifying unsatisfactory performance by searching for user initiated early terminations of web transactions from passive monitoring. However, user early abortions can be caused by other factors such as loss of interests. Therefore, naively using them to represent user dissatisfaction will result in large false positives. In this paper, we propose a systematic method for inferring user dissatisfaction from the set of early abortion behaviors observed from identifying the traffic traces. We conduct a comprehensive analysis on the user acceptance of throughput and response time, and compare them with the traditional MOS metric. Then we present the characteristics of early cancelation from dimensions like the types of URLs and objects. We evaluate our approach on four data sets collected in both wireline network and a wireless cellular network.
Detecting User Dissatisfaction and Understanding the Underlying Reasons
Quantifying quality of experience for network applications is challenging as it is a subjective metric with multiple dimensions such as user expectation, satisfaction, and overall experience. Today, despite various techniques to support differentiated Quality of Service (QoS), the operators still lack of automated methods to translate QoS to QoE, especially for general web applications.