Time series: theory and methods
Time series: theory and methods
Characterizing browsing strategies in the World-Wide Web
Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
Internet Web servers: workload characterization and performance implications
IEEE/ACM Transactions on Networking (TON)
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
Generating representative Web workloads for network and server performance evaluation
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Workload characterization of a Web proxy in a cable modem environment
ACM SIGMETRICS Performance Evaluation Review
Automatic personalization based on Web usage mining
Communications of the ACM
Evidence for long-tailed distributions in the internet
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Session-Based Admission Control: A Mechanism for Peak Load Management of Commercial Web Sites
IEEE Transactions on Computers
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
A Comparative Transaction Log Analysis of Two Computing Collections
ECDL '00 Proceedings of the 4th European Conference on Research and Advanced Technology for Digital Libraries
The Structural Cause of File Size Distributions
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis
INFORMS Journal on Computing
Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs
IEEE Transactions on Software Engineering
Empirical Study of Session-Based Workload and Reliability for Web Servers
ISSRE '04 Proceedings of the 15th International Symposium on Software Reliability Engineering
Variable heavy tails in internet traffic
Performance Evaluation - Special issue: Distributed systems performance
Associating search and navigation behavior through log analysis: Research Articles
Journal of the American Society for Information Science and Technology
On TCP and self-similar traffic
Performance Evaluation - Long range dependence and heavy tail distributions
Empirical Characterization of Session---Based Workload and Reliability for Web Servers
Empirical Software Engineering
A Contribution Towards Solving the Web Workload Puzzle
DSN '06 Proceedings of the International Conference on Dependable Systems and Networks
The information seeking behaviour of the users of digital scholarly journals
Information Processing and Management: an International Journal
Website usage metrics: A re-assessment of session data
Information Processing and Management: an International Journal
Empirical observations on the session timeout threshold
Information Processing and Management: an International Journal
Lognormal and Pareto distributions in the Internet
Computer Communications
A workload characterization study of the 1998 World Cup Web site
IEEE Network: The Magazine of Global Internetworking
Information Processing and Management: an International Journal
| Hi-index | 0.00 |
Companies now rely on the World Wide Web for communication with their customers. As reliance on web servers grows, the need for companies to better understand the workload placed upon these servers also increases. The session workload unit is a popular unit of measurement used to analyze recorded information from server logs. In fact, many web applications, from shopping carts to online banking systems, require session information to function correctly. Web data mining is also dependent on session workload information. However, the distributional properties of this session workload are not understood. Whether the session workload can be described as a short-tailed or heavy-tailed distribution is a fundamental question for the investigation of the session workload unit. This paper empirically explores claims that the session workload can be described using a heavytailed distribution. The paper concludes that, for the samples used in this paper, a method to accurately determine whether the session workload is drawn from a heavy-tailed distribution does not exist. Hence, the conclusion that they are drawn from such a distribution cannot be made.