Randomized Least Frequently Used Cache Replacement Strategy for Named Data Networking

Abstract

To accommodate the rapidly changing Internet requirements, Information-Centric Networking (ICN) was recently introduced as a promising architecture for the future Internet. One of the ICN primary features is ‘in-network caching’; due to its ability to minimize network traffic and respond faster to users’ requests. Therefore, various caching algorithms have been presented that aim to enhance the network performance using different measures, such as cache hit ratio and cache hit distance. Choosing a caching strategy is critical, and an adequate replacement strategy is also required to decide which content should be dropped. Thus, in this paper, we propose a content replacement scheme for ICN, called Randomized LFU that is implemented with respect to content popularity taking the time complexity into account. We use Abilene and Tree network topologies in our simulation models. The proposed replacement achieves encouraging results in terms of the cache hit ratio, inner hit, and hit distance and it outperforms FIFO, LRU, and Random replacement strategies.