Abstract

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.

中文翻译：

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基于云的内容分发网络上优化成本和QoS的进化算法

摘要

内容分发网络（CDN）是向最终用户提供全球服务和内容的关键。在这项工作中，我们提出了三种多目标进化算法来解决设计和优化基于云的CDN的问题。我们考虑的目标是最大程度地降低基础架构（包括虚拟机，网络和存储）的总成本，并最大程度地提高提供给最终用户的服务质量。提出的模型考虑了多租户方法，其中单个基于云的CDN能够使用资源共享策略托管多个内容提供商。所提出的进化算法解决了提供基础设施资源的离线问题，而提出了一种贪婪启发式方法来解决路由内容的在线问题。对提出的方法的实验评估是在一组现实的问题实例上进行的。结果表明，所提出的方法对于设计和优化基于云的CDN是有效的，可将总成本降低多达10.3％，同时保持适当的服务质量。