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Generating representative Web workloads for network and server performance evaluation
Abstract
One role for workload generation is as a means for understanding how servers and networks respond to variation in load. This enables management and capacity planning based on current and projected usage. This paper applies a number of observations of Web server usage to create a realistic Web workload generation tool which mimics a set of real users accessing a server. The tool, called Surge (Scalable URL Reference Generator) generates references matching empirical measurements of 1) server file size distribution; 2) request size distribution; 3) relative file popularity; 4) embedded file references; 5) temporal locality of reference; and 6) idle periods of individual users. This paper reviews the essential elements required in the generation of a representative Web workload. It also addresses the technical challenges to satisfying this large set of simultaneous constraints on the properties of the reference stream, the solutions we adopted, and their associated accuracy. Finally, we present evidence that Surge exercises servers in a manner significantly different from other Web server benchmarks.
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Cited by
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A Brief History of Generative Models for Power Law and Lognormal Distributions
Mitzenmacher, M. (2004) · Internet Mathematics · doi:10.1080/15427951.2004.10129088 · Cited by 1,188
Roughan, M., Sen, S., Spatscheck, O., & Duffield, N. (2004) · Proceedings of the 4th ACM SIGCOMM conference on Internet measurement · doi:10.1145/1028788.1028805 · Cited by 494
Analysis of SRPT scheduling: investigating unfairness
Bansal, N., & Harchol-Balter, M. (2001) · Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems · doi:10.1145/378420.378792 · Cited by 312
An energy-efficient VM placement method for cloud data centers using a hybrid genetic algorithm
Kaaouache, M. A., & Bouamama, S. (2018) · Journal of Systems and Information Technology · doi:10.1108/jsit-10-2017-0089 · Cited by 18
Metadata
- Authors
- Barford, P., & Crovella, M.
- Venue
- Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
- Publisher
- ACM
- Published
- 1998-06
- Pages
- 151-160
- OpenAlex
- W2133985894
- Cited by
- 1,431
- References
- 0
- FWCI
- 53.72
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Barford, P., & Crovella, M. (1998). Generating representative Web workloads for network and server performance evaluation. Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems. https://doi.org/10.1145/277851.277897
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.