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Automating experimentation on distributed testbeds
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Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering table of contents
Long Beach, CA, USA
SESSION: Configuration management & security table of contents
Pages: 164 - 173  
Year of Publication: 2005
ISBN:1-59593-993-4
Authors
Yanyan Wang  University of Colorado, Boulder, CO
Matthew J. Rutherford  University of Colorado, Boulder, CO
Antonio Carzaniga  University of Colorado, Boulder, CO and University of Lugano, Lugano, Switzerland
Alexander L. Wolf  University of Colorado, Boulder, CO and University of Lugano, Lugano, Switzerland
Sponsors
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 37,   Citation Count: 2
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ABSTRACT

Engineering distributed systems is a challenging activity. This is partly due to the intrinsic complexity of distributed systems, and partly due to the practical obstacles that developers face when evaluating and tuning their design and implementation decisions.This paper addresses the latter aspect, providing techniques for software engineers to automate the experimentation activity. Our approach is founded on a suite of models that characterize the distributed system under experimentation, the testbeds upon which the experiments are to be carried out, and the client behaviors that drive the experiments. The models are used by generative techniques to automate construction of the workloads,as well as construction of the scripts for deploying and executing the experiments on distributed testbeds. The framework is not targeted at a specific system or application model, but rather is a generic, programmable tool. We have validated our approach by performing experiments on a variety of distributed systems. For two of these systems, the experiments were deployed and executed on the PlanetLab wide-area testbed.Our experience shows that this framework can be readily applied to different kinds of distributed system architectures,and that using it for meaningful experimentation,especially in large-scale network environments, is advantageous.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Y. Wang, M. J. Rutherford, A. Carzaniga, and A. L. Wolf. Weevil: A tool to automate experimentation with distributed systems. Technical Report CU-CS-980-04, Department of Computer Science, University of Colorado, Oct. 2004.
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Collaborative Colleagues:
Yanyan Wang: colleagues
Matthew J. Rutherford: colleagues
Antonio Carzaniga: colleagues
Alexander L. Wolf: colleagues