Title: Cloud provider profit-aware and triadic concept analysis-based data replication strategy for tenant performance improvement

Authors: Amel Khelifa; Tarek Hamrouni; Riad Mokadem; Faouzi Ben Charrada

Addresses: LIPAH, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia ' LIPAH, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia ' Institut de Recherche en Informatique de Toulouse (IRIT), Paul Sabatier University, Toulouse, France ' LIMTIC, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia

Abstract: Effective data management is very challenging to cloud providers, whose business model relies on maintaining an economic profit while satisfying the tenants' performance requirements. To address these challenges, many data replication strategies have been proposed. In this paper, we propose a new dynamic data replication strategy for cloud systems called RCPP¹. In order to satisfy performance requirements, the proposed strategy exploits the valuable knowledge extracted from the tenants' past access history. Therefore, it uses the mathematical triadic concept analysis approach to determine correlated data to be replicated. Furthermore, the cloud provider's profit is taken into account. Hence, an economic model is proposed to estimate the revenues and expenditures of the provider. Experimental studies show the efficiency and effectiveness of RCPP compared to state-of-the-art strategies. RCPP is indeed proven able to reduce the total expenditures of the cloud provider significantly while achieving better performances.

Keywords: replication; cloud provider; data correlation; profit; economic model; triadic concept.

DOI: 10.1504/IJHPCN.2020.112678

International Journal of High Performance Computing and Networking, 2020 Vol.16 No.2/3, pp.67 - 86

Received: 10 Jan 2020
Accepted: 14 Apr 2020
Published online: 28 Jan 2021 *

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