Maximizing Utilization in Private IaaS Clouds with Heterogenous Load through Time Series Forecasting

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00207154" target="_blank" >RIV/68407700:21230/13:00207154 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.iariajournals.org/systems_and_measurements/sysmea_v6_n12_2013_paged.pdf" target="_blank" >http://www.iariajournals.org/systems_and_measurements/sysmea_v6_n12_2013_paged.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Maximizing Utilization in Private IaaS Clouds with Heterogenous Load through Time Series Forecasting

Popis výsledku v původním jazyce

This document presents ongoing work on creating a computing system that can run two types of workloads on a private cloud computing cluster, namely web servers and batch computing jobs, in a way that would maximize utilization of the computing infrastructure. To this end, a queue engine called Cloud Gunther has been developed. This application improves upon current practices of running batch computations in the cloud by integrating control of virval machine provisioning within the job scheduler. For managing web server workloads, we present ScaleGuru, which has been modeled after Amazon Auto Scaler for easier transition from public to private cloud. Both these tools are tested to run over the Eucalyptus cloud system. Further research has been done in the area of Time Series Forecasting, which enables to predict the load of a system based on past observations. Due to the periodic nature of the interactive load, predictions can be made in the horizon of days with reasonable accuracy. Two

Název v anglickém jazyce

Maximizing Utilization in Private IaaS Clouds with Heterogenous Load through Time Series Forecasting

Popis výsledku anglicky

This document presents ongoing work on creating a computing system that can run two types of workloads on a private cloud computing cluster, namely web servers and batch computing jobs, in a way that would maximize utilization of the computing infrastructure. To this end, a queue engine called Cloud Gunther has been developed. This application improves upon current practices of running batch computations in the cloud by integrating control of virval machine provisioning within the job scheduler. For managing web server workloads, we present ScaleGuru, which has been modeled after Amazon Auto Scaler for easier transition from public to private cloud. Both these tools are tested to run over the Eucalyptus cloud system. Further research has been done in the area of Time Series Forecasting, which enables to predict the load of a system based on past observations. Due to the periodic nature of the interactive load, predictions can be made in the horizon of days with reasonable accuracy. Two

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal On Advances in Systems and Measurements

ISSN

1942-261X

e-ISSN

—

Svazek periodika

6

Číslo periodika v rámci svazku

1&2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

149-165

Kód UT WoS článku

—

EID výsledku v databázi Scopus

—