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Compound Codes for Optimal Repair in Distributed Storage

This article explores compound codes for optimal repair within distributed storage systems, particularly in RAID-type environments and peer-to-peer architectures. It highlights the efficiency of Maximum Distance Separable (MDS) codes, such as Reed-Solomon codes, in addressing redundancy and repair complexity. The discussion encompasses recent advancements in repair efficiency, network bandwidth considerations, and disk access redundancy. Various coding schemes, including EVENODD, STAR, RDP, Liberation, and X codes, are analyzed for their performance in practical reliability contexts.

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Compound Codes for Optimal Repair in Distributed Storage

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  1. Compound Codes for Optimal Repair in Distributed Storage Viveck R. Cadambe

  2. Data Centers Servers (RAID-type systems) Peer-to-Peer Storage

  3. Distributed Storage Data Centers Servers (RAID-type systems) Peer-to-Peer Storage

  4. Redundancyfor a fixed amount storage • Maximum Distance Separable Codes (MDS Codes); For example,Reed-Solomon Codes • Complexity (Encoding and Update) • EVENODD, STAR, RDP, Liberation, X Codes etc. • (Recent) Repair Efficiency • Network bandwidth • Disk access

  5. Redundancyfor a fixed amount storage • Maximum Distance Separable Codes (MDS Codes); For example,Reed-Solomon Codes • Complexity (Encoding and Update) • EVENODD, STAR, RDP, Liberation, X Codes etc. • (Recent) Repair Efficiency • Network bandwidth • Disk access

  6. Redundancyfor a fixed amount storage • Maximum Distance Separable Codes (MDS Codes); For example,Reed-Solomon Codes • Complexity (Encoding and Update) • EVENODD, STAR, RDP, Liberation, X Codes etc. • (Recent) Repair Efficiency • Network bandwidth • Disk access

  7. Redundancyfor a fixed amount storage • Maximum Distance Separable Codes (MDS Codes); For example, Reed Solomon Codes • Complexity(Encoding and Update) • EVENODD, STAR, RDP, Liberation, X Codes etc. • (Recent) Repair Efficiency • Network bandwidth • Disk access

  8. Practical reasons (Reliability, Network Bandwidth usage) *non-multicast -> Destinations do not intend to decode all the sources in the network.

  9. Practical reasons (Reliability, Network Bandwidth usage) • Multi-Source (non-multicast*) Network Capacity Problem • Interference Alignment *non-multicast -> Destinations do not intend to decode all the sources in the network.

  10. [Wu-Dimakis 09] Trivial Repair : 4 linear combinations

  11. [Wu-Dimakis 09] Interference Alignment!

  12. Interference Alignment!

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