A New Storage Workload Management Model for High-Performance I/O Systems
Huang Huang, Sheng You, Yu Tong Lu · 2019
Data-intensive applications involve with massive data, ranging from terabytes to petabytes, which is a critical bottleneck in the next generation systems. In this article, we mainly focus on system I/O competition caused by the data-intensive applications and unbalanced storage capacity, and attempt to develop effective solutions to alleviate this issue. To this end, we develop an I/O middleware based method. The core of our middleware is the storage workload management model (SWMM), which allows us to adjust and optimize the I/O access process efficiently and flexibly. We have implemented our solution and conducted extensive tests based on a petascale system. The experimental results demonstrate the effectiveness and efficiency of our solution.