EnosLib: A Library for Experiment-Driven Research in Distributed Computing
Despite the importance of experiment-driven research in the distributed computing community, there has been little progress in helping researchers conduct their experiments. In most cases, they have to achieve tedious and time-consuming development and instrumentation activities to deal with the spe...
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| Published in: | IEEE transactions on parallel and distributed systems Vol. 33; no. 6; pp. 1464 - 1477 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
IEEE
01.06.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers |
| Subjects: | |
| ISSN: | 1045-9219, 1558-2183 |
| Online Access: | Get full text |
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| Abstract | Despite the importance of experiment-driven research in the distributed computing community, there has been little progress in helping researchers conduct their experiments. In most cases, they have to achieve tedious and time-consuming development and instrumentation activities to deal with the specifics of testbeds and the system under study. In order to relieve researchers of the burden of those efforts, we have developed EnosLib : a Python library that takes into account best experimentation practices and leverages modern toolkits on automatic deployment and configuration systems. EnosLib helps researchers not only in the process of developing their experimental artifacts, but also in running them over different infrastructures. To demonstrate the relevance of our library, we discuss three experimental engines built on top of EnosLib , and used to conduct empirical studies on complex software stacks between 2016 and 2019 (database systems, communication buses and OpenStack). By introducing EnosLib , our goal is to gather academic and industrial actors of our community around a library that aggregates everyday experiment-driven research operations. A library that has been already adopted by open-source projects and members of the scientific community thanks to its ease of use and extension. |
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| AbstractList | Despite the importance of experiment-driven research in the distributed computing community, there has been little progress in helping researchers conduct their experiments. In most cases, they have to achieve tedious and time-consuming development and instrumentation activities to deal with the specifics of testbeds and the system under study. In order to relieve researchers of the burden of those efforts, we have developed ENOSLIB: a Python library that takes into account best experimentation practices and leverages modern toolkits on automatic deployment and configuration systems. ENOSLIB helps researchers not only in the process of developing their experimental artifacts, but also in running them over different infrastructures. To demonstrate the relevance of our library, we discuss three experimental engines built on top of ENOSLIB, and used to conduct empirical studies on complex software stacks between 2016 and 2019 (database systems, communication buses and OpenStack). By introducing ENOSLIB, our goal is to gather academic and industrial actors of our community around a library that aggregates everyday experiment-driven research operations. A library that has been already adopted by open-source projects and members of the scientific community thanks to its ease of use and extension. |
| Author | Simonin, Matthieu Balderrama, Javier Rojas Simonet, Anthony van Kempen, Alexandre Cherrueau, Ronan-Alexandre Lebre, Adrien Delavergne, Marie Pertin, Dimitri |
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| SubjectTerms | Benchmark testing Codes Computer networks Computer Science distributed computing experimentation library Distributed processing Distributed, Parallel, and Cluster Computing Experiment-driven research Experimentation Experiments Libraries Networking and Internet Architecture Other performance evaluation Protocols Software Source code Task analysis |
| Title | EnosLib: A Library for Experiment-Driven Research in Distributed Computing |
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