Back to Search Start Over

A new popularity-based data replication strategy in cloud systems

Authors :
Riad Mokadem
Abdenour Lazeb
Ghalem Belalem
Université d'Oran 1 Ahmed Ben Bella [Oran]
Optimisation Dynamique de Requêtes Réparties à grande échelle (IRIT-PYRAMIDE)
Institut de recherche en informatique de Toulouse (IRIT)
Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3)
Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP)
Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées
Source :
Multiagent and Grid Systems-An International Journal of Cloud Computing, Multiagent and Grid Systems-An International Journal of Cloud Computing, IOS Press, 2021, 17 (2), pp.159-177. ⟨10.3233/MGS-210348⟩
Publication Year :
2021
Publisher :
IOS Press, 2021.

Abstract

International audience; Data-intensive cloud computing systems are growing year by year due to the increasing volume of data. In this context, data replication technique is frequently used to ensure a Quality of service, e.g., performance. However, most of the existing data replication strategies just reproduce the same number of replicas on some nodes, which is certainly not enough for more accurate results. To solve these problems, we propose a new data Replication and Placement strategy based on popularity of User Requests Group (RPURG). It aims to reduce the tenant response time and maximize benefit for the cloud provider while satisfying the Service Level Agreement (SLA). We demonstrate the validity of our strategy in a performance evaluation study. The result of experimentation shown robustness of RPURG.

Details

ISSN :
18759076 and 15741702
Volume :
17
Database :
OpenAIRE
Journal :
Multiagent and Grid Systems
Accession number :
edsair.doi.dedup.....96049c3e995b34728915588390a0216f