Browse wiki

From Navigators

Jump to: navigation, search
Abstract MapReduce is often used to run critical jo MapReduce is often used to run critical jobs such as scientific data analysis. However, evidence in the literature shows that arbitrary faults do occur and can probably corrupt the results of MapReduce jobs. MapReduce runtimes like Hadoop tolerate crash faults, but not arbitrary or Byzantine faults. We present a MapReduce algorithm and prototype that tolerate these faults. An experimental evaluation shows that the execution of a job with our algorithms uses twice the resources of the original Hadoop, instead of the 3 or 4 times more that would be achieved with the direct application of common Byzantine fault-tolerance paradigms. We believe this cost is acceptable for critical applications that require that level of fault tolerance. hat require that level of fault tolerance.
Address Athens, Greece  +
Author Pedro Costa + , Marcelo Pasin + , Alysson Bessani + , Miguel Correia +
Booktitle Proceedings of the 3rd IEEE International Conference on Cloud Computing and Science - CloudCom’11  +
Document CostaPBC11.pdf +
Key CostaPBC11  +
NumPubDate 2,011  +
Project Project:TCLOUDS +
ResearchLine Fault and Intrusion Tolerance in Open Distributed Systems (FIT) +
Title Byzantine Fault-Tolerant MapReduce: Faults are Not Just Crashes  +
Type inproceedings  +
Year 2011  +
Has improper value forThis property is a special property in this wiki. Month  + , Url  +
Categories Publication  +
Modification dateThis property is a special property in this wiki. 21 January 2013 15:42:49  +
redirect page Publication:CostaPBC11  +
hide properties that link here 
  No properties link to this page.


Enter the name of the page to start browsing from.
Personal tools
Navigators toolbox