A fragmented data-declustering strategy for high skew tolerance and efficient failure recovery

Data declustering is a common technique to improve data I/O performance by retrieving data in parallel from multiple storage nodes. Data-declustering methods with replicated data also increase system availability, reliability and skew tolerance. Current replicated declustering schemes fall into two types. In the first, each storage node has its data fully replicated on one other storage node. In the second, each storage node has its replica data fragmented and distributed over several storage nodes. The different schemes have different trade-offs between skew tolerance and data reliability. In this paper, we introduce Fragmented Chained Declustering (FCD) to provide better load balancing and efficient failed-data restoration, with the same or lower data loss rates than previous solutions. Experimental results show the load-balancing and failure recovery efficiency of FCD.