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Professor Alexander Barg (ECE/ISR) is the recipient of a three-year, $250K National Science Foundation Computing and Communication Foundations grant for "Coding and Information: Theoretic Aspects of Local Data Recovery."
Barg will study fundamental problems in data coding that can improve the efficiency of distributed storage systems by increasing data reliability and availability while reducing storage overhead compared to existing industry standards. This research will benefit storage applications ranging from financial, scientific monitoring, and signal processing to social networks and sharing platforms.
Data coding with locality is a rapidly developing area of coding theory initially motivated by applications in distributed storage. It has links to many areas of network science (e.g., index coding and network coding) as well as to computer science. Barg's project advances the theory and practice of data coding with local recovery by investigating broad implications of the locality constraint in coding problems. These include studying new error-correcting code families and their decoding, fundamental limitations on the code parameters and capacity bounds under the requirements of local data recovery. The newly designed coding schemes developed in this project will be validated through implementation and evaluation in simulated computer environment, aiming at enhanced performance of data coding in current industry solutions.
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July 7, 2016
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