Adaptive Parameter Tuning for Constructing Storage Tiers in an Autonomous Distributed Storage System

Abstract

We are developing an autonomous distributed storage system to make effective use of networked heterogeneous storage devices. It dynamically configures the storage tiers using effective performance values measured during operation, rather than static performance indicators of the storage device. Data blocks are transferred to a more appropriate storage tier according to their read/write tendencies. In the previous paper, the storage tiers were set using statically defined thresholds, but in this paper, we propose a method to set the thresholds adaptively. This method eliminates the need to adjust the runtime parameters for threshold setting according to the runtime environment. It has also been improved so that appropriate parameter values can be set for individual storage, rather than applying a single parameter value to the entire system. In the previous system, the administrator had to readjust the parameter values periodically to match the usage status of the storage device and the behavior of the process. However, in the proposed method, the parameter values are fine-tuned during operation to reduce the workload of the administrator. The simulation results show that the proposed method can reduce the execution time by up to about 30% compared to the previous method with optimum parameters configured statically.