A Novel Consistency Metric for Web Application Performance Analysis using Geographically-Distributed Traffic Data

Web applications constitute the majority of internet traffic today. These applications have been optimized for a desired level of user experience. Optimization of web application performance requires extensive testing. A reliability guarantee and associated optimization measures pose a considerable challenge in such testing approaches especially when a worldwide access is becoming a norm. Measurement of web application performance is typically conducted through models that approximate the expected user experiences, the available service architectures, and the network related impairments. In addition, the components of such a test, namely, client and server sides with the network state in the middle, each have immense amounts of configuration variations and associated requirements for performance guarantees. In this dissertation, we tackled the analysis of web application performance through a novel measure that provides a consistency indicator. We first defined measurement and metric development methodology. We conducted our research to demonstrate what constitutes consistent performance on parameters of content length and loading time, along with other parameters specific to the application. We then applied an empirical methodology to measure the consistency of web application performance through an extensive data collection tool, NetForager. We developed this tool to collect repeatable web application performance data in the form of traffic packet captures at geographically-distributed locations around the nation. The tool uses a framework with container technologies to orchestrate isolated web application data collection. The consistency metric for a representative set of web applications has been calculated along with an error margin. The content length and delay during the retrieval of the application data has been utilized for the calculations in order to achieve a holistic performance perspective. We present consistency metric analysis for 15 web applications to reason about how optimizations and acceleration methods may provide superior application performance consistency. More importantly, our metric lays a foundation on holistic external testing of application performance that can be agnostic to variations in end user clients, application service architecture and associated servers, and the network state. Furthermore, a geographically-distributed measurement of the consistency metric provided insights into how individual session count and other application characteristics can be monitored.