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Title: Modelling low power compute clusters for cloud simulation
Authors: Kecskemeti, Gabor
Hajji, Wajdi
Tso, Fung Po
Keywords: Cloud computing
IaaS
Low power
Simulation
Containers
Docker
Issue Date: 2017
Publisher: © IEEE
Citation: KECSKEMETI, G., HAJJI, W. and TSO, F.P., 2017. Modelling low power compute clusters for cloud simulation. 25th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2017), St. Petersburg, Russia, 6th-8th March 2017, pp. 39-45.
Abstract: In order to minimise their energy use, data centre operators are constantly exploring new ways to construct computing infrastructures. As low power CPUs, exemplified by ARM-based devices, are becoming increasingly popular, there is a growing trend for the large scale deployment of low power servers in data centres. For example, recent research has shown promising results on constructing small scale data centres using Raspberry Pi (RPi) single-board computers as their building blocks. To enable larger scale experimentation and feasibility studies, cloud simulators could be utilised. Unfortunately, stateof-the-art simulators often need significant modification to include such low power devices as core data centre components. In this paper, we introduce models and extensions to estimate the behaviour of these new components in the DISSECT-CF cloud computing simulator. We show that how a RPi based cloud could be simulated with the use of the new models. We evaluate the precision and behaviour of the implemented models using a Hadoop-based application scenario executed both in real life and simulated clouds.
Description: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor: This work is partially supported by the UK Engineering and Physical Sciences Research Council (EPSRC) grants EP/P004407/1 and EP/P004024/1.
Version: Accepted for publication
DOI: 10.1109/PDP.2017.33
URI: https://dspace.lboro.ac.uk/2134/24644
Publisher Link: https://doi.org/10.1109/PDP.2017.33
Appears in Collections:Published Articles (Computer Science)

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