An analysis of data corruption in the storage stack
By Lakshmi N. Bairavasundaram, Garth R. Goodson, Bianca Schroeder, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau. TOS, 2008
329 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/2a9ff343e70eca6156e80f6efbbe9f0b9c55f9f0
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In Artificial Intelligence
- Sean Quinlan
- Parikshit Gopalan
- Sergey Yekhanin
- Srikanth Kandula
- Jin Li
- Ion Stoica
- Carrie Grimes
- Ganesh Ananthanarayanan
In Computer Networks and Communications
- Ion Stoica
- Srikanth Kandula
- Ganesh Ananthanarayanan
- Randy Howard Katz
- Jin Li
- Albert G. Greenberg
- Luiz André Barroso
- Sean Quinlan
Citations in the corpus
- Reining in the Outliers in Map-Reduce Clusters using Mantri (2010, background): “The subset of machines that triggers most of the recomputes is steady over days but varies over weeks, likely indicative of changing hotspots in data popularity or corruption in disks [6].”
- Erasure Coding in Windows Azure Storage (2012, background): “Data corruption can happen throughout the storage stack for numerous reasons [36].”
- Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads (2012, background): “We expect small variation between different use cases, and the representative features are already captured in publications on the web indexing use case and existing microbenchmarks.”
- Availability in Globally Distributed Storage Systems (2010, methodology): “We demonstrate this method by validating physical racks as an important failure domain.”