| Abstract
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MapReduce is often used for critical data … MapReduce is often used for critical data processing, e.g., in the context of scientific or financial simulation. However, there is evidence in the literature that there are arbitrary (or Byzantine) faults that may corrupt the results of MapReduce without being detected. We present a Byzantine fault-tolerant MapReduce framework that can run in two modes: non-speculative and speculative.
We thoroughly evaluate experimentally the performance of these two versions of the framework, showing that they use around twice more resources than Hadoop MapReduce, instead of the three times more of alternative solutions. We believe this cost is acceptable for many critical applications. acceptable for many critical applications.
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| Author
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Pedro Costa +
, Marcelo Pasin +
, Alysson Bessani +
, Miguel Correia +
|
| Document
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Document for Publication-PedroCosta 2013.pdf +
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| Journal
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IEEE Transactions on Dependable and Secure Computing +
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| Key
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PedroCosta 2013 +
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| NumPubDate
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2,013 +
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| Project
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Project:TCLOUDS +
, Project:RC-Clouds +
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| ResearchLine
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Fault and Intrusion Tolerance in Open Distributed Systems (FIT) +
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| Title
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On the Performance of Byzantine Fault-Tolerant MapReduce +
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| Type
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article +
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| Year
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2013 +
|
| Has improper value forThis property is a special property in this wiki.
|
Month +
, Url +
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| Categories |
Publication +
|
| Modification dateThis property is a special property in this wiki.
|
31 January 2013 18:33:03 +
|
