Wrekavoc: a tool for emulating heterogeneity

Canon, Louis-Claude; Jeannot, Emmanuel

doi:10.1109/ipdps.2006.1639386

Cited by 13 publications

(7 citation statements)

References 11 publications

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“…Our previous work [8] mainly aimed at showing the feasibility of building a BitDew based MapReduce runtime for large scale and loosely connected Internet Desktop Grid. We rewrite the upper layer MapReduce API to allow users to isolate their application-specified map and reduce functions with the data management code.…”

Section: B the Bitdew-mapreduce Runtimementioning

confidence: 99%

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Assessing MapReduce for Internet Computing: A Comparison of Hadoop and BitDew-MapReduce

Jin

Shi

et al. 2012

2012 ACM/IEEE 13th International Conference on Grid Computing

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Section: B the Bitdew-mapreduce Runtimementioning

confidence: 99%

“…We use the same methodology to evaluate the scalability of BitDew services using one hundred nodes to simulate a huge number of concurrent clients. Wrekavoc [8] is a heterogeneity emulator that controls environment by degrading the nodes' performance that is similar to our approach, which is used in the heterogeneity scenarios.…”

Section: Related Workmentioning

confidence: 99%

Assessing MapReduce for Internet Computing: A Comparison of Hadoop and BitDew-MapReduce

Jin

Shi

et al. 2012

2012 ACM/IEEE 13th International Conference on Grid Computing

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“…In this case, the control of the environment (CPU or network speed) is done by degrading the performance. This is the approach taken by Wrekavoc [22]. Both approaches will be discussed in Section 4.2.…”

Section: Emulationmentioning

confidence: 99%

Experimental Methodologies for Large-Scale Systems: A Survey

Gustedt

Jeannot

Quinson

2009

Parallel Process. Lett.

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The increasing complexity of available infrastructures with specific features (caches, hyperthreading, dual core, etc.) or with complex architectures (hierarchical, parallel, distributed, etc.) makes it extremely difficult to build analytical models that allow for a satisfying prediction. Hence, it raises the question on how to validate algorithms if a realistic analytic analysis is not possible any longer. As for some many other sciences, the one answer is experimental validation. Nevertheless, experimentation in Computer Science is a difficult subject that today still opens more questions than it solves: What may an experiment validate? What is a "good experiment"? How to build an experimental environment that allows for "good experiments"? etc. In this paper we will provide some hints on this subject and show how some tools can help in performing "good experiments", mainly in the context of parallel and distributed computing. More precisely we will focus on four main experimental methodologies, namely in-situ (real-scale) experiments (with an emphasis on PlanetLab and Grid'5000), Emulation (with an emphasis on Wrekavoc) benchmarking and simulation (with an emphasis on SimGRID and GridSim). We will provide a comparison of these tools and methodologies from a quantitative but also qualitative point of view.

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“…In this case, the control of the environment (CPU or network speed) is done by degrading the performance. This is the approach taken by Wrekavoc [4] and will be discussed in the next section.…”

Section: Emulationmentioning

confidence: 99%

“…We have designed a tool called Wrekavoc 5 [4] to tackle the problem of emulating a heterogeneous environment. Wrekavoc addresses the problem of controlling the heterogeneity of a cluster.…”

Section: Emulatorsmentioning

confidence: 99%

Experimental validation of grid algorithms: A comparison of methodologies

Jeannot¹

2008

2008 IEEE International Symposium on Parallel and Distributed Processing

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The increasing complexity of available infrastructures with specific features (caches, hyperthreading, dual core, etc.) or with complex architectures (hierarchical, parallel, distributed, etc.) makes models either extremely difficult to build or intractable. Hence, it raises the question: how to validate algorithms if a realistic analytic analysis is not possible any longer? As for some other sciences (physics, chemistry, biology, etc.), the answer partly falls in experimental validation. Nevertheless, experiment in computer science is a difficult subject that opens many questions: what an experiment is able to validate? What is a "good experiments"? How to build an experimental environment that allows for "good experiments"? etc. In this paper we will provide some hints on this subject and show how some tools can help in performing "good experiments". More precisely we will focus on three main experimental methodologies, namely real-scale experiments (with an emphasis on PlanetLab and Grid'5000), Emulation (with an emphasis on Wrekavoc: http://wrekavoc.gforge.inria.fr) and simulation (with an emphasis on SimGRID and GridSim). We will provide a comparison of these tools and methodologies from a quantitative but also qualitative point of view.

show abstract

Wrekavoc: a tool for emulating heterogeneity

Cited by 13 publications

References 11 publications

Assessing MapReduce for Internet Computing: A Comparison of Hadoop and BitDew-MapReduce

Assessing MapReduce for Internet Computing: A Comparison of Hadoop and BitDew-MapReduce

Experimental Methodologies for Large-Scale Systems: A Survey

Experimental validation of grid algorithms: A comparison of methodologies

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