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Professor Alexander Barg (ECE/ISR) is the principal investigator for a new NSF Communication and Information Foundations grant, ?Efficient Codes and their Performance Limits for Distributed Storage Systems.? The three-year, $300K grant addresses the efficient means of storing the huge amount of data being generated and collected. This research will develop more efficient data management procedures for large-scale distributed storage systems.

Large data centers and distributed storage systems have become more widespread, playing an ever-increasing role in everyday computational tasks. While a data center should never lose data, industry statistics confirm that disk failures occur on a daily basis. Barg will develop methods and ideas about error correcting codes that will enable systems to provide better guarantees against data loss and reduce the amount of data that needs to be moved to enable recovery of information lost due to disk failures.

Barg also will use algebraic methods of constructing data encoding procedures as well as novel algorithms of data exchange and recovery to reduce the storage overhead needed to support the recovery procedures. This will enable tradeoffs between overhead and repair bandwidth, based on the concept of local recovery. Barg will study both the case of recovering from a single disk loss, which is the most frequent problem in systems, as well as failure of multiple disks. This will address the problem of correcting one erasure as well as multiple erasures in data encoding. New bounds on the distance of codes with the locality requirement derived in this research will be developed, as well as new constructions of optimal locally recoverable codes equipped with simple recovery procedures.

The project also addresses the problem of simultaneous recovery of data from multiple locations, enhancing data availability in the large-scale distributed storage systems that are a key backbone component of the 21st century economy.



Related Articles:
New data coding methods for large data centers
Barg is principal investigator for new NSF information recovery award
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Ye, Barg win IEEE Data Storage Best Paper Award
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Alexander Barg receives NSF grant for polar code research
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Arya Mazumdar wins information theory student paper prize
Alexander Barg receives NSF grant for improving error-correcting coding

September 5, 2014


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