Content Distribution Networks (CDN) are key for providing worldwide services and content to end-users. In this work, we propose three multiobjective evolutionary algorithms for solving the problem of designing and optimizing cloud-based CDNs. We consider the objectives of minimizing the total cost of the infrastructure (including virtual machines, network, and storage) and the maximization of the quality-of-service provided to end-users. The proposed model considers a multi-tenant approach where a single cloud-based CDN is able to host multiple content providers using a resource sharing strategy. The proposed evolutionary algorithms address the offline problem of provisioning infrastructure resources while a greedy heuristic method is proposed for addressing the online problem of routing contents. The experimental evaluation of the proposed methods is performed over a set of realistic problem instances. Results indicate that the proposed approach is effective for designing and optimizing cloud-based CDNs reducing total costs by up to 10.3% while maintaining an adequate quality of service.
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The work of S. Iturriaga and S. Nesmachnow is partially supported by ANII and PEDECIBA, Uruguay. The work of B. Dorronsoro is partially supported by the Ministry of Science, Innovation and Universities and ERDF with the fundings of the project RTI2018-100754-B-I00 (iSUN).
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Iturriaga, S., Nesmachnow, S., Goñi, G. et al. Evolutionary Algorithms for Optimizing Cost and QoS on Cloud-based Content Distribution Networks. Program Comput Soft 45, 544–556 (2019) doi:10.1134/S0361768819080127