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JOURNALS // Proceedings of the Institute for System Programming of the RAS // Archive

Proceedings of ISP RAS, 2019 Volume 31, Issue 2, Pages 15–20 (Mi tisp405)

This article is cited in 2 papers

Design and optimization of Content Distribution Networks

S. D. Iturriaga Fabraa, S. E. Nesmachnow Cánovasa, G. Goñi Bofriscoa, B. Dorronsoro Díazb, A. N. Tchernykhcde

a Universidad de la República
b Universidad de Cádiz
c Ivannikov Institute for System Programming of the Russian Academy of Sciences
d South Ural State University
e Centro de Investigación Científica y Educación Superior de Ensenada

Abstract: This article presents the application of soft computing methods for solving the problem of designing and optimizing cloud-based Content Distribution Networks (CDN). A multi-objective approach is applied to solve the resource provisioning problem for building the infrastructure for the network, considering the objectives of minimizing the cost of the virtual machines, network, and storage, and the maximization of the quality-of-service provided to end-users. A specific brokering model is proposed to allow a single cloud-based CDN to be able to host multiple content providers applying a resource sharing strategy. Following the proposed brokering model, three multiobjective evolutionary approaches are studied for the offline optimization of resource provisioning and a greedy heuristic method is proposed for addressing the online routing of contents. The experimental evaluation of the proposed approach is performed over a set of realistic problem instances. The obtained experimental results indicate that the proposed approach is effective for designing and optimizing cloud-based Content Distribution Networks: total costs are reduced by up to 10.34% while maintaining high quality-of-service values.

Keywords: cloud computing, optimization, evolutionary algorithms, content distribution networks.

DOI: 10.15514/ISPRAS-2019-31(2)-1



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