增强以信息为中心的网络中的缓存鲁棒性:逐面流行方法

Network Pub Date : 2023-11-01 DOI:10.3390/network3040022
John Baugh, Jinhua Guo
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引用次数: 0

摘要

信息中心网络(Information-Centric Networking, ICN)是一种新的网络架构范式,它关注的是内容,而不是作为网络一等公民的主机。作为这些体系结构的一部分,网络内存储设备对于为最终用户提供流行内容的紧密副本、减少延迟和改善用户的整体体验以及减少网络拥塞和内容生产者的负载至关重要。为了提高效率,网络内存储设备(如内容存储路由器)应该维护最流行的内容对象的副本。希望降低这种有效性的攻击者可以发起缓存污染攻击,以消除网络内存储设备缓存的好处。因此,保护这些设备并确保尽可能高的命中率至关重要。本文演示了逐面流行度方法,通过规范化内容存储路由器所有面评估的流行度来减少缓存污染的影响并提高命中率。所开发的机制可防止消费者(无论是合法的还是恶意的)在任何单一或少数面孔上对保留在缓存中的内容对象产生压倒性影响。结果表明,与目前使用的缓存替换技术相比,逐面方法通常具有更好的命中率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Cache Robustness in Information-Centric Networks: Per-Face Popularity Approaches
Information-Centric Networking (ICN) is a new paradigm of network architecture that focuses on content rather than hosts as first-class citizens of the network. As part of these architectures, in-network storage devices are essential to provide end users with close copies of popular content, to reduce latency and improve the overall experience for the user but also to reduce network congestion and load on the content producers. To be effective, in-network storage devices, such as content storage routers, should maintain copies of the most popular content objects. Adversaries that wish to reduce this effectiveness can launch cache pollution attacks to eliminate the benefit of the in-network storage device caches. Therefore, it is crucial to protect these devices and ensure the highest hit rate possible. This paper demonstrates Per-Face Popularity approaches to reducing the effects of cache pollution and improving hit rates by normalizing assessed popularity across all faces of content storage routers. The mechanisms that were developed prevent consumers, whether legitimate or malicious, on any single face or small number of faces from overwhelmingly influencing the content objects that remain in the cache. The results demonstrate that per-face approaches generally have much better hit rates than currently used cache replacement techniques.
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