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Cost-aware caching: Optimizing cache provisioning and object placement in ICN

机译：成本感知缓存：在ICN中优化缓存配置和对象放置

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摘要

Caching is frequently used by Internet Service Providers as a viable technique to reduce the latency perceived by end users, while jointly offloading network traffic. While the cache hit-ratio is generally considered in the literature as the dominant performance metric for such type of systems, in this paper we argue that a critical missing piece has so far been neglected. Adopting a radically different perspective, in this paper we explicitly account for the cost of content retrieval, i.e. the cost associated to the external bandwidth needed by an ISP to retrieve the contents requested by its customers. Interestingly, we discover that classical cache provisioning techniques that maximize cache efficiency (i.e., the hit-ratio), lead to suboptimal solutions with higher overall cost. To show this mismatch, we propose two optimization models that either minimize the overall costs or maximize the hit-ratio, jointly providing cache sizing, object placement and path selection. We formulate a polynomial-time greedy algorithm to solve the two problems and analytically prove its optimality. We provide numerical results and show that significant cost savings are attainable via a cost-aware design.
机译：缓存是Internet服务提供商经常使用的一种可行技术，它可以减少最终用户感知的延迟，同时减轻网络流量的负担。尽管在文献中通常将高速缓存命中率视为此类系统的主要性能指标，但在本文中，我们认为到目前为止，关键的缺失部分已被忽略。本文采用截然不同的观点，在本文中，我们明确说明了内容检索的成本，即与ISP检索其客户请求的内容所需的外部带宽相关的成本。有趣的是，我们发现最大程度地提高缓存效率（即命中率）的经典缓存置备技术会导致总成本较高的次优解决方案。为了显示这种不匹配，我们提出了两个优化模型，它们可以最小化总体成本或最大化命中率，共同提供缓存大小，对象放置和路径选择。我们提出了多项式时间贪婪算法来解决这两个问题，并分析证明了其最优性。我们提供了数值结果，并表明通过成本意识设计可以实现显着的成本节省。

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