Understanding I/O Performance Behaviors of Cloud Storage from a Client’s Perspective

Abstract

Cloud storage has gained increasing popularity in the past few years. In cloud storage, data is stored in the service provider’s data centers, and users access data via the network. For such a new storage model, our prior wisdom about conventional storage may not remain valid nor applicable to the emerging cloud storage. In this article, we present a comprehensive study to gain insight into the unique characteristics of cloud storage and optimize user experiences with cloud storage from a client’s perspective. Unlike prior measurement work that mostly aims to characterize cloud storage providers or specific client applications, we focus on analyzing the effects of various client-side factors on the user-experienced performance. Through extensive experiments and quantitative analysis, we have obtained several important findings. For example, we find that (1) a proper combination of parallelism and request size can achieve optimized bandwidths, (2) a client’s capabilities and geographical location play an important role in determining the end-to-end user-perceivable performance, and (3) the interference among mixed cloud storage requests may cause performance degradation. Based on our findings, we showcase a sampling- and inference-based method to determine a proper combination for different optimization goals. We further present a set of case studies on client-side chunking and parallelization for typical cloud-based applications. Our studies show that specific attention should be paid to fully exploiting the capabilities of clients and the great potential of cloud storage services.