###### Abstract  
Various techniques have been used in distributed file systems for data availability and stability. Typically, a method for storing data in a replication technique-based distributed file system is used, but due to the problem of space efficiency, an erasure-coding (EC) technique has been utilized more recently. The EC technique improves the space efficiency problem more than the replication technique does. However, the EC technique has various performance degradation factors, such as encoding and decoding and input and output (I/O) degradation. Thus, this study proposes a buffering and combining technique in which various I/O requests that occurred during encoding in an EC-based distributed file system are combined into one and processed. In addition, it proposes four recovery measures (disk input/output load distribution, random block layout, multi-thread-based parallel recovery, and matrix recycle technique) to distribute the disk input/output loads generated during decoding. distributed storage system; erasure coding; exascale; recovery; combining Article]Erasure-Coding-Based Storage and Received for Distributed Exascale Storage Systems 2021 11 3298  
The replication technique employs replicated data at the time of failure, whereas the EC technique employs decoding when recovering data. Since decoding restores data through a large number of disk I/O operations, it has more disk I/O loads than the replication technique does [26; 27; 28]. EC is a low-cost recovery technique for fault-tolerant storage that is now widely used in today's distributed storage systems (DSSs). For example, it is used by enterprise-level DSSs [5; 29; 30] and many open source DSSs [31; 32; 33; 34; 35]. Unlike replication, which simply creates identical copies of data to tolerate failure without data loss, EC has much less storage overhead by encoding/decoding data copies. In addition, it can maintain the same level of fault tolerance as the replication technique. [36]. DSS implements EC mostly based on the Reed-Solomon (RS) code [37], but some DSSs, including HDFS, Ceph [34], and Swift [32], provide various EC and EC configuration control functions. As described above, existing DSSs solved the deterioration factor of EC based on parallel processing and disabled I/O to some extent, but consider the I/O load problem between disks that occurs when EC is applied in a parallel processing method. I did not do this, which is expected to cause a large amount of I/O load between disks when recovering in parallel on an EC-based file distribution system. Therefore, this study proposes actions that reduce small amounts of disk I/Os in the EC-based HDFS, discusses issues encountered during parallel recovery, and suggests actions to address them. The main idea of our paper is the input/output buffering and combining technique that combines and processes multiple input/output requests that occur during encoding in an EC-based distributed file system. In addition, it is a disk input/output load balancing technique that is a recovery method to distribute the disk input/output load that occurs during decoding. More importantly, for file recovery, disk I/O load distribution, random block placement, and matrix recycling techniques are applied. The values and contributions of our labor profession are summarized as follows. The input/output buffering step does not wait for input/output requests for the same basic block group during input/output processing, but creates a secondary queue for the block group processing input/output and collects the waiting input/output. In the input/output buffering process, first, check if there is a secondary queue. If it does not exist, it creates a secondary queue and adds the waiting input/output to the secondary queue. If there is a secondary queue, add the requested input/output to the created secondary queue. When the addition is completed, the secondary queue setting is finally released.