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A value-based cache replacement approach for Information-Centric Networks

机译:以信息为中心的网络的基于值的缓存替换方法

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Information-Centric Networks (ICNs) represent a content-based model which addresses user's requests regardless of the content's location or the nature of its original publisher. The performance of an ICN is highly dependent on replicating the content across the caches of a multitude of nodes in the network. Given the high data turnover rates of contemporary applications and the finite nature of caching space, efficient caching algorithms play a crucial role in determining which data item can be safely dropped in order to accommodate for more important items. In this paper, we present a value-based cache replacement approach that executes a Least Valuable First (LVF) policy. Our approach employs a utility function that uses delay, popularity and age parameters to determine which item to drop from the cache. We present simulation results comparing our approach to other dominant cache replacement policies under varying conditions such as data popularity, in-network cache ratio and connectivity degree. Results show that our approach outperforms in terms of time-to-hit, hit rate, in-network delay and data publisher load.
机译:以信息为中心的网络(ICN)代表一种基于内容的模型,该模型可满足用户的请求,而与内容的位置或其原始发布者的性质无关。 ICN的性能高度依赖于在网络中多个节点的缓存之间复制内容。鉴于现代应用程序的高数据周转率以及缓存空间的有限性,有效的缓存算法在确定可以安全删除哪些数据项以容纳更重要的项方面起着至关重要的作用。在本文中,我们提出了一种基于值的缓存替换方法,该方法执行了最低优先级(LVF)策略。我们的方法采用了一个实用程序函数,该函数使用延迟,流行度和年龄参数来确定要从缓存中删除的项目。我们提供了仿真结果,将我们的方法与在各种情况下(例如数据受欢迎程度,网络内缓存比率和连接度)的其他主要缓存替换策略进行了比较。结果表明,我们的方法在命中时间,命中率,网络内延迟和数据发布者负载方面均优于。

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