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Authors: Aymen Jlassi 1 ; Patrick Martineau 2 and Vincent Tkindt 2

Affiliations: 1 Cyres Group and University François-Rabelais of Tours, France ; 2 University François-Rabelais of Tours, France

ISBN: 978-989-758-104-5

Keyword(s): Big Data, MapReduce Model, Hadoop Scheduling Problem, Time Indexed Formulation.

Related Ontology Subjects/Areas/Topics: Cloud Computing ; Cloud Computing Architecture ; Cloud Computing Enabling Technology ; Fundamentals ; Monitoring of Services, Quality of Service, Service Level Agreements ; Performance Development and Management

Abstract: MapReduce is a model to manage quantities massive of data. It is based on the distributed and parallel execution of tasks over the cluster of machines. Hadoop is an implementation of MapReduce model, it is used to offer BigData services on the cloud. In this paper, we expose the scheduling problem on Hadoop systems. We focus on the offline-scheduling, expose the problem in a mathematic model and use the timeindexed formulation. We aim consider the maximum of constraints of the MapReduce environment. Solutions for the presented model would be a reference for the on-line Schedules in the case of low and medium instances. Our work is useful in term of the problem definition: constraints are based on observations and take into account resources consumption, data locality, heterogeneous machines and workflow management; this paper defines boundaries references to evaluate the online model.

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Paper citation in several formats:
Jlassi, Aymen; Martineau, P. and Tkindt, V. (2015). Offline Scheduling of Map and Reduce Tasks on Hadoop Systems.In Proceedings of the 5th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-104-5, pages 178-185. DOI: 10.5220/0005483601780185

@conference{closer15,
author={Jlassi, Aymen and Patrick Martineau. and Vincent Tkindt.},
title={Offline Scheduling of Map and Reduce Tasks on Hadoop Systems},
booktitle={Proceedings of the 5th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2015},
pages={178-185},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005483601780185},
isbn={978-989-758-104-5},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Offline Scheduling of Map and Reduce Tasks on Hadoop Systems
SN - 978-989-758-104-5
AU - Jlassi, Aymen
AU - Martineau, P.
AU - Tkindt, V.
PY - 2015
SP - 178
EP - 185
DO - 10.5220/0005483601780185

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