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 paper, we present a comprehensive study and attempt to gain insight into the unique characteristics of cloud storage, primarily from the client's perspective. Through extensive experiments and quantitative analysis, we have acquired several interesting, and in some cases unexpected, findings. (1) Parallelizing I/Os and increasing request sizes are keys to improving the performance, but optimal bandwidth may only be achieved with a proper combination of parallelism and request size. (2) Client capabilities, including CPU, memory, and storage, play an unexpectedly important role in determining the achievable performance. (3) A geographically long distance affects client-perceived performance but does not always result in lower bandwidth and longer latency. Based on our experimental studies, we further present a case study on appropriate chunking and parallelization in a cloud storage client. Our studies show that specific attention should be paid to fully exploiting the capabilities of clients and the great potential of cloud storage services.