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Authors: Fereydoun Farrahi Moghaddam ; Reza Farrahi Moghaddam and Mohamed Cheriet

Affiliation: École de Technologie Supérieure, Canada

ISBN: 978-989-8565-05-1

Keyword(s): Cloud Computing, Virtual Private Cloud, Green IT, Carbon Footprint, Genetic Algorithm, Multi-level Grouping.

Related Ontology Subjects/Areas/Topics: Cloud Applications Performance and Monitoring ; Cloud Computing ; Cloud Computing Enabling Technology ; Cloud Middleware Frameworks ; e-Business ; e-Governance ; Energy and Economy ; Enterprise Information Systems ; Load Balancing in Smart Grids ; Mobility ; Performance Development and Management ; Platforms and Applications ; Smart Grids

Abstract: Optimization problem of physical servers consolidation is very important for energy efficiency and cost reduction of data centers. For this type of problems, which can be considered as bin-packing problems, traditional heuristic algorithms such as Genetic Algorithm (GA) are not suitable. Therefore, other heuristic algorithms are proposed instead, such as Grouping Genetic Algorithm (GGA), which are able to preserve the group features of the problem. Although GGA have achieved good results on server consolidation in a given data center, they are weak in optimization of a network of data centers. In this paper, a new grouping genetic algorithm is introduced which is called Multi-Level Grouping Genetic Algorithm (MLGGA), and is designed for multi-level bin packing problems such as optimization of a network of data centers for carbon footprint reduction, energy efficiency, and operation cost reduction. The new MLGGA algorithm is tested on a real world problem in a simulation platform, and its results are compared with the GGA results. The comparison shows a significant increase in the performance achieved by the proposed MLGGA algorithm. (More)

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Paper citation in several formats:
Farrahi Moghaddam, F.; Farrahi Moghaddam, R. and Cheriet, M. (2012). MULTI-LEVEL GROUPING GENETIC ALGORITHM FOR LOW CARBON VIRTUAL PRIVATE CLOUDS.In Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-8565-05-1, pages 315-324. DOI: 10.5220/0003903303150324

@conference{closer12,
author={Fereydoun Farrahi Moghaddam. and Reza Farrahi Moghaddam. and Mohamed Cheriet.},
title={MULTI-LEVEL GROUPING GENETIC ALGORITHM FOR LOW CARBON VIRTUAL PRIVATE CLOUDS},
booktitle={Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2012},
pages={315-324},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003903303150324},
isbn={978-989-8565-05-1},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - MULTI-LEVEL GROUPING GENETIC ALGORITHM FOR LOW CARBON VIRTUAL PRIVATE CLOUDS
SN - 978-989-8565-05-1
AU - Farrahi Moghaddam, F.
AU - Farrahi Moghaddam, R.
AU - Cheriet, M.
PY - 2012
SP - 315
EP - 324
DO - 10.5220/0003903303150324

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