A Performance Model of Zoned Disk Drives with I/O Request Reordering

Abstract

Abstract-Disk drives are a common performance bottleneck in modern storage systems. To alleviate this, disk manufacturers employ a variety of I/O request scheduling strategies which aim to reduce disk head positioning time by dynamically reordering queueing requests. An analytical model of this phenomenon is best represented by an M/G/1 queue with queue length dependent service times. However, there is no general exact result for the response time distribution of this variety of queue with generalised service time distributions. In this paper, we present a novel approximation for the response time distribution of such a queue. We then apply this method to the specific case of a zoned disk drive which implements I/O request reordering. A key contribution is the derivation of realistic service time distributions with minimised positioning time. We derive analytical results for calculating not only the mean but also higher moments and the full distribution of I/O request response time. We validate our model against measurements from a real disk to demonstrate the accuracy of our approximation.

Fourier-assisted machine learning of hard disk drive access time models

“…Many analytic models exist, including work by Lebrecht, Dingle, and Knottenbelt [21]. Analytic models are relatively easy to understand and extremely fast due to their compact formulae.…”

Hybrid system analysis and design for scale-out storage environments

“…In order to build an analytical model to study the SMR drive performance, it is better to know the analytical approach for conventional storage devices. Historically, the performance of HDD device is studied by lots of researchers[147] [148] [149][150]. Due to the different data recording properties and request processing method of SMR drive, such as the batch write and garbage collection method, etc., these models can not be directly applied to the modern SMR drive design.…”