Efficient Prefetching and Client-Side Caching Algorithms for Improving the Performance of Read Operations in Distributed File Systems

Abstract

Modern web applications are deployed in cloud computing systems because they support unlimited storage and computing power. One of the main back-end storage components of this cloud computing system is the distributed file system which allows massive amounts of data to be stored and accessed. In most web applications deployed in such systems, read operations are performed more frequently than write operations. Consequently, increasing the efficiency of read operations in distributed file systems is a challenging and important research problem. The two main procedures used in distributed file systems to improve the performance of read operations are prefetching and caching. In this paper, we proposed novel prefetching and multi-level caching algorithms based on the Access-Frequency and Access-Recency ranking of file blocks that were previously accessed by client application programs. We also proposed new augmented ranking algorithms for prefetching file blocks by combining the Access-Frequency and Access-Recency ranking of the file blocks. We used rank-based replacement algorithms to replace file blocks in the cache. The simulation results show that, the proposed algorithms improve the performance of read operations on distributed file systems by 29% to 77% in comparison to algorithms proposed in the literature.

Keywords

• Distributed file system
• multi-level caching
• prefetching
• hadoop
• HDFS
• big data