Analyzing Request Volatility of I/O Temporal Behaviors in Mobile Storage Workloads

The design and performance optimization of flash-based storage subsystems are crucial for improving the system performance of Android-based smartphones. However, it highly relies on wisdom derived from mobile storage workload studies of smartphone applications. From the temporal perspective, our burstiness diagnosis reveals that the arrival processes of I/O requests in 33 smartphone applications, are significantly bursty, especially for read requests. This article studies the correlation of inter-arrival times of read and write requests, and compares the correlations for read and write requests in the four same types of mobile applications. We first observe that read requests of 85% of applications and write requests of 88% of applications present a certain degree of correlation over a longer time range. Then, we further conduct Hurst parameter estimation for these mobile applications with mature statistical tools. All estimated Hurst parameters are larger than 0.5, confirming the existence of self-similarity in a majority of mobile application workloads. Finally, we deploy a flexible I/O request generator for smartphone applications based on the parameters measured from actual traces. Experimental results show that the proposed generator can accurately generate request sequences for various mobile applications and more faithfully characterize the heavy-tail properties of I/O activities in mobile storage workloads than traditional models.