Abstract: In distributed storage systems, replication and erasure code (EC) are common methods for data redundancy. Compared with replication, EC has better storage efficiency, but suffers higher overhead in update. Moreover, consistency and reliability problems caused by concurrent updates bring new challenges to applications of EC. Many works focus on optimizing the EC solution, including algorithm optimization, novel data update method, and so on, but lack the solutions for consistency and reliability problems. In this paper, we introduce a storage system that decouples data updating and EC encoding, namely, decoupled data updating and coding (DDUC), and propose a data placement policy that combines replication and parity blocks. For the (N,M) EC system, the data are placed as N groups of M+1 replicas, and redundant data blocks of the same stripe are placed in the parity nodes, so that the parity nodes can autonomously perform local EC encoding. Based on the above policy, a two-phase data update method is implemented in which data are updated in replica mode in phase 1, and the EC encoding is done independently by parity nodes in phase 2. This solves the problem of data reliability degradation caused by concurrent updates while ensuring high concurrency performance. It also uses persistent memory (PMem) hardware features of the byte addressing and eight-byte atomic write to implement a lightweight logging mechanism that improves performance while ensuring data consistency. Experimental results show that the concurrent access performance of the proposed storage system is 1.70–3.73 times that of the state-of-the-art storage system Ceph, and the latency is only 3.4%–5.9% that of Ceph.

Key words: Concurrent update; High reliability; Erasure code; Consistency; Distributed storage system

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