Characterizing and Modeling the Dropbox Workload

This paper presents a characterization and modeling of the workload of the currently most popular cloud storage system, Drop box. The workload is analyzed from two complementary perspectives. On one side, characteristics of the Drop box folders of a set of 333 volunteers, including number, type and sizes of files, replication level, and file update dynamics are analyzed. On the other side, the client behavior patterns are modeled based on the analysis of Drop box traffic collected from 3 universities. Our results can be explored to design realistic synthetic workloads, which in turn can support the design and evaluation of more cost-effective cloud storage services.