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

Hamza Ouarnoughi 1 Jalil Boukhobza 1 Frank Singhoff 1 Stéphane Rubini 1
1 Lab-STICC_UBO_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance, UBO - Université de Brest
Abstract : 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, monitoring 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.
Type de document :
Communication dans un congrès
3rd IEEE Real-Time and Distributed Computing in Emerging Applications (REACTION ), Dec 2014, Rome, Italy
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http://hal.univ-brest.fr/hal-01097125
Contributeur : Jalil Boukhobza <>
Soumis le : jeudi 18 décembre 2014 - 22:23:30
Dernière modification le : mardi 16 janvier 2018 - 15:54:23

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  • HAL Id : hal-01097125, version 1

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Hamza Ouarnoughi, Jalil Boukhobza, Frank Singhoff, Stéphane Rubini. A Multilevel I/O Tracer for Timing and Performance Analysis of Storage Systems in IaaS Cloud. 3rd IEEE Real-Time and Distributed Computing in Emerging Applications (REACTION ), Dec 2014, Rome, Italy. 〈hal-01097125〉

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