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A Multilevel I/O Tracer for Timing and Performance Analysis of Storage Systems in IaaS Cloud

By Hamza Ouarnough, Jalil Boukhobza and Frank Singhoff


REACTION 2014. 3rd International Workshop on Real-time and Distributed Computing in Emerging Applications. Rome, Italy. December 2nd, 2014.Data centers are more and more relying on hybrid storage systems consisting of flash memory based storage devices and traditional hard disk drives. Optimal data placement in such hybrid storage systems is a very important issue in the domain of cloud computing and virtualization. This is specially the case when users need that storage systems enforce Quality of Service requirements on I/Os performed, for example for multimedia applications. To characterize Virtual Machine (VM) I/O workload properties such as timing predictability or throughput, monitor-ing services are necessary on such new architectures. This article presents a multilevel I/O tracer for virtual machines that relies on and complement different state-of-the-art tools. It produces I/O traces at different levels of the Linux I/O software stack. The I/O tracer gives an exhaustive information that allows administrators to precisely characterize virtual machine I/O behavior in terms of percentage of read/write I/Os, percentage of random/sequential, I/O request inter-arrival time, etc. This tool is the first piece towards a middleware whose purpose is to meet user QoS requirements thanks to optimal data placement and migration policies in a hybrid storage system in the context of an IaaS Cloud.This work has been funded by the French government through the National Research Agency (ANR) Investment referenced ANR-A0-AIRT-07Publicad

Topics: Sistemas en tiempo real, Sistemas distribuidos, cloud computing, distributed systems, Real-time computing, Telecomunicaciones
Publisher: 'Universidad Carlos III de Madrid'
Year: 2011
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