Performance Evaluation of Distributed Storage Systems

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 work 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.In this study we investigate the performance evaluation of distributed storage system and understand the effect on performance for various patters of I/O operations that is the read and write and also different measurement approaches for storage performance. The method is to use synthetic workload generator by streaming and transcoding video data as well as benchmark tool which generate the workload like SPECsfs2014 is used to evaluate the performance of distributed storage systems of GlusterFS and Compuverde which are file based storage. We concluded that Compuverde performs better when compared to gluster even though a low performance hardware is used. We recommend to use cache drive in the Gluster storage nodes for the better performance to avoid bottlenecks.