Context. Big Data and Cloud Computing nowadays require large amounts of storage that are accessible by many servers. To overcome the performance bottlenecks and single point of failure distributed storage systems came into force. So, our main aim in this thesis is evaluating the performance of these storage systems. A file coding technique is used that is the erasure coding which will help in data protection for the storage systems.

Objectives. In this study, we investigate the performance evaluation of distributed storage system and understand the effect on performance for various patterns of I/O operations that is the read and write and also different measurement approaches for storage performance.

Methods. The method is to use synthetic workload generator by streaming and transcoding video data as well as benchmark tool which generates the workload like SPECsfs2014 is used to evaluate the performance of distributed storage systems of GlusterFS and Compuverde which are file based storage.

Results. In terms of throughput results, Gluster and Compuverde perform similar for both NFS and SMB server.

The average latency results for both NFS and SMB shares indicate that Compuverde has lower latency.

When comparing results of both Compuverde and Gluster, Compuverde delivers 100% IOPS with NFS server and Gluster delivers relatively near to the requested OP rate and with SMB server Gluster delivers 100% IOPS and Compuverde delivers more than the requested OP rate.