High-Performance General Functional Regenerating Codes with Near-Optimal Repair Bandwidth.

Erasure codes are widely used in modern distributed storage systems to prevent data loss and server failures. Regenerating codes are a class of erasure codes that trade storage efficiency and computation for repair bandwidth reduction. However, their nonunified coding parameters and huge computational overhead prohibit their applications. Hence, we first propose a family of General Functional Regenerating (GFR) codes with uncoded repair, balancing storage efficiency and repair bandwidth with general parameters. The GFR codes take advantage of a heuristic repair algorithm, which makes efforts to employ as little repair bandwidth as possible to repair a single failure. Second, we also present a scheduled shift multiplication (SSM) algorithm, which accelerates the matrix product over the Galois field by scheduling the order of coding operations, so encoding and repairing of GFR codes can be executed by fast bitwise shifting and exclusive-OR. Compared to the traditional table-lookup multiplication algorithm, our SSM algorithm gains 1.2 to 2 X speedup in our experimental evaluations, with little effect on the repair success rate.