A modeling approach for estimating performance and energy consumption of storage systems

Abstract

Improvements in data storage may be constrained by the lower performance of hard disk drives (HDD) and the higher cost per gigabyte of solid-state drives (SSD). To mitigate these issues, hybrid storage architectures have been conceived. Some works evaluate the performance of storage architectures, but energy consumption is usually neglected and not simultaneously evaluated with performance. This paper presents an approach based on generalized stochastic Petri nets (GSPN) for performance and energy consumption evaluation of individual and hybrid storage systems. The proposed models can represent distinct workloads and also estimate throughput, response time and energy consumption of storage systems. Experiments based on industry-standard benchmarks are adopted to demonstrate the feasibility of the proposed approach.