| Large scale content distribution over the internet has been the focus of numerous studies in recent years. In the traditional server-client model, the server may suffer from overload when a popular file stored at the server is frequently requested. In order to reduce the cost at servers and decrease the retrieval time for clients, distributed storage solutions that operate by dividing the file into pieces and placing copies of the pieces (replication) or coded versions of the pieces (coding) at multiple source nodes have been proposed.Distributed storage systems provide reliable access to data through redundancy spread over individually unreliable nodes. Application scenarios include data centers, peer-to-peer storage systems, and storage in wireless networks. Storing data using an erasure code, in fragments spread across nodes, requires less redundancy than simple replication for the same level of reliability. However, since fragments must be periodically replaced as nodes fail, a key question is how to generate encoded fragments in a distributed way while transferring as little data as possible across the network.For an erasure coded system, a common practice to repair from a node failure is for a new node to download subsets of data stored at a number of surviving nodes, reconstruct a lost coded block using the downloaded data, and store it at the new node. It has been shown that this procedure is sub-optimal. The notion of regenerating codes was introduced, which allow a new node to download functions of the stored data from the surviving nodes. It has also been shown that regenerating codes can significantly reduce the repair bandwidth. Further, the fundamental tradeoff between storage and repair bandwidth which we theoretically characterize using flow arguments on an appropriately constructed graph was introduced. By invoking constructive results in network coding, we introduce regenerating codes that can achieve any point in this optimal tradeoff. |
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