Web server workload characterization: the search for invariants
Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
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
Characterizing reference locality in the WWW
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Preserving QoS of e-commerce sites through self-tuning: a performance model approach
Proceedings of the 3rd ACM conference on Electronic Commerce
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
Capacity Planning for Web Services: metrics, models, and methods
Capacity Planning for Web Services: metrics, models, and methods
Microsoft SQL Server 2000 Performance Tuning Technical Reference
Microsoft SQL Server 2000 Performance Tuning Technical Reference
Summary of WWW characterizations
World Wide Web
Measuring the capacity of a Web server under realistic loads
World Wide Web
TPC-W: A Benchmark for E-Commerce
IEEE Internet Computing
Improving e-commerce system performance with dynamic system tuning
Improving e-commerce system performance with dynamic system tuning
Professional Apache Tomcat
Experiment and analysis for QoS of E-commerce systems
Journal of Theoretical and Applied Electronic Commerce Research
Self-star Properties in Complex Information Systems
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E-commerce systems are composed of many components with several configurable parameters that, if properly configured, can optimize system performance. Before upgrading existing systems to overcome performance bottlenecks, several areas of a site's architecture and its parameters may be adjusted to improve performance. This paper provides a method to rank key configurable e-commerce system parameters that significantly impact overall system performance, and the performance of the most significant Web function types. We consider both on-line and off-line parameters at each of the e-commerce system layers: Web server, application server, and database server. In order to accomplish our task, we designed a practical, ad-hoc approach that involves conducting experiments on a testbed system setup as a small e-commerce site. The configurable parameters are ranked based on their degrees of performance improvement to the system and to the most critical Web functions. The performance metrics of interest include server's response time, system throughput, and probability of rejecting a customer's request. The experiments were conducted on an e-commerce site compliant to the TPC-W benchmark.