Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization

TL;DR

This paper systematically reviews and characterizes web application workloads, identifying distinct daily and weekly patterns to inform workload generation and resource management strategies.

Contribution

It provides a comprehensive systematic literature review and detailed statistical characterization of web application workload patterns at daily and weekly granularities.

Findings

Identified three daily workload patterns.

Identified three weekly workload patterns.

Highlighted workload pattern uniqueness and implications.

Abstract

Web applications, accessible via web browsers over the Internet, facilitate complex functionalities without local software installation. In the context of web applications, a workload refers to the number of user requests sent by users or applications to the underlying system. Existing studies have leveraged web application workloads to achieve various objectives, such as workload prediction and auto-scaling. However, these studies are conducted in an ad hoc manner, lacking a systematic understanding of the characteristics of web application workloads. In this study, we first conduct a systematic literature review to identify and analyze existing studies leveraging web application workloads. Our analysis sheds light on their workload utilization, analysis techniques, and high-level objectives. We further systematically analyze the characteristics of the web application workloads identified in the literature review. Our analysis centers on characterizing these workloads at two distinct temporal granularities: daily and weekly. We successfully identify and categorize three daily and three weekly patterns within the workloads. By providing a statistical characterization of these workload patterns, our study highlights the uniqueness of each pattern, paving the way for the development of realistic workload generation and resource provisioning techniques that can benefit a range of applications and research areas.