Search results for "WEB SERVER"

Web Traffic Modeling for E-Commerce Web Server System

2009

The paper concerns a problem of the e-commerce Web server system performance evaluation through simulation experiments, especially a problem of modeling a representative stream of user requests at the input of such system. Motivated by a need of a benchmarking tool for the Business-to-Consumer (B2C) environment we discuss a workload model typical of such Web sites and also a model of a multi-tiered e-commerce Web server system. A simulation tool in which the proposed models have been implemented is briefly talked over and some experimental results on the Web system performance in terms of traditional and business performance measures are presented.

Modeling a session-based bots' arrival process at a Web server

2017

Characterizing Web sessions of e-customers interested in traditional and innovative products

2016

Web traffic characterization and modelling is currently a hot research issue. Low-level analysis of HTTP traffic on the server allows one to build adequate traffic models to be used in server benchmarking. High-level analysis of Web user behavior allows one to optimize website structure and develop personalized service strategies. In this paper, analysis of customer sessions in an online store is performed using Web server log data. The goal is to explore possible differences between sessions of customers viewing and purchasing innovative products, and customers only interested in traditional products.

Investigating Long-Range Dependence in E-Commerce Web Traffic

2016

This paper addresses the problem of investigating long-range dependence (LRD) and self-similarity in Web traffic. Popular techniques for estimating the intensity of LRD via the Hurst parameter are presented. Using a set of traces of a popular e-commerce site, the presence and the nature of LRD in Web traffic is examined. Our results confirm the self-similar nature of traffic at a Web server input, however the resulting estimates of the Hurst parameter vary depending on the trace and the technique used.

Online anomaly detection using dimensionality reduction techniques for HTTP log analysis

2015

Modern web services face an increasing number of new threats. Logs are collected from almost all web servers, and for this reason analyzing them is beneficial when trying to prevent intrusions. Intrusive behavior often differs from the normal web traffic. This paper proposes a framework to find abnormal behavior from these logs. We compare random projection, principal component analysis and diffusion map for anomaly detection. In addition, the framework has online capabilities. The first two methods have intuitive extensions while diffusion map uses the Nyström extension. This fast out-of-sample extension enables real-time analysis of web server traffic. The framework is demonstrated using …