Two Efficient Partial-Updating Schemes for Erasure-Coded Storage Clusters

Nowadays, erasure codes have been widely used in data storage to achieve high fault-tolerance. However, compared with replica-based storage, erasure-coded system may suffer significant performance overhead in encoding, decoding and updating. Traditional updating schemes(e.g. DUM and PUM) use an individual manager node to accomplish the updating. In this paper, we propose two partial-updating schemes (i.e. PUM-P and PDN-P) to improve the small update in erasure coded storage clusters, where both schemes only read a portion of data, including the data blocks to be updated and the parity blocks, and utilize the calculation capacity of the storage nodes. We implement four updating algorithms (DUM, PUM, PUM-P and PDN-P) upon an erasure-coded storage cluster platform, and conduct a set of comparative tests under two real-world workloads with different fault-tolerance parameters. The experimental results shows that PUM-P and PDN-P can speed up the small updating by a factor of up to 1.62 and 2.72 compared with DUM under small update, respectively; and by a factor of up to 1.42 and 2.23 relative to PUM, respectively. We also validate that DUM scheme can achieve better updating performance than the other schemes within the large update scenario.