During ISIT 2014, the IEEE International Symposium on Information Theory awarded its top prize to Erasure Coding in Windows Azure Storage—an associated systems paper written by Microsoft’s Cheng Huang, Huseyin Simitci, Yikang Xu, Aaron Ogus, Brad Calder, Parikshit Gopalan, Jin Li, and Sergey Yekhanin—which pointed the way to a new method for achieving more efficient storage in the cloud.

Erasure coding, a powerful math tool that reduces the space required to store data, relies on shortened descriptions of data for reassembly and delivery to users. Local Reconstruction Codes (LRC) enable quicker data reconstructions, and the result is reduced time and costs for data retrieval. Together, they developed an abstract mathematical framework that captures the requirements for codes that arise in distributed storage systems. The research was such a success that its practical applications have been adopted throughout all Microsoft storage production lines, from the cloud to enterprise and the desktop, including Windows Server and Windows 8.1.

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