信息中心网络内缓存替换算法性能分析与优化

信息中心网络(information centric networking, ICN)是一类受到广泛关注的新型互联网体系结构.通过对网络内(in-network)缓存的充分利用，信息中心网络可以极大地增强内容分发效率.网络内缓存的管理机制一直是信息中心网络研究中的热点问题.分析了网络内缓存的基准缓存替换最近最少使用(least recently used, LRU)算法的性能，指出多跳LRU缓存中广泛存在的“缓存退化”问题：在首个缓存节点发生缺失的内容请求也很难被下游的缓存命中.针对这一问题，提出一种基于预过滤的O(1)复杂度的改进算法.在原有缓存前放置一个仅记录内容标识的预过滤缓存，完成对原始内容请求的整形，使得预处理后的请求流量可以更容易被后面几跳缓存命中.基于真实互联网拓扑的实验表明，在信息中心网络典型应用场景下，预过滤LRU的缓存命中率可以达到LRU的2～3倍.

Performance Analysis and Optimization for In-Network Caching Replacement in Information Centric Networking

Information centric networking (ICN) is a promising framework for evolving the current network architecture, advocating the ubiquitous in-network caching to enhance content delivery. Consequently, the cache replacement mechanism has been a hot topic in ICN research. In this paper, we first study the performance of the de facto standard cache replacement policy—least recently used (LRU). We find that if an interest for certain content is not satisfied at the first LRU cache node it hits, it is hardly satisfied in the following path. We then propose a pre-filtering based cache replacement policy to mitigate the cache degradation in multi-hop LRU cache. In the proposed policy, a pre-filtering LRU cache is settled in front of the real content store, which filters out the non-popular content and improves the hit-ratio of the real content cache. Extensive experiments based on the real-life topology show that our pre-filtering cache policy greatly improves the cache hit-ratio of cache node in typical ICN scenarios.