Enhanced dynamic fine-grained popularity-based caching algorithm for ICN-based edge computing networks

Abstract

In this letter, we propose an Enhanced Dynamic Fine-Grained Popularity-based Caching (ED-FGPC) algorithm to efficiently cache static contents in ICN-based edge computing networks. The content popularity changes with time. Thus, the ED-FGPC algorithm considers the number of incoming interests, the practical file size, and the available cache size to adjust the content popularity threshold. This allows dynamic adjustment of the content popularity threshold. Additionally, ED-FGPC incorporates a single bit called cached bit (CB) in the header field of the content. This eliminates caching redundancy in the on-path routers. The cache eviction policy jointly considers the content popularity and the average content access timestamp for content replacement. Based on the content access pattern, this allows finer adjustment of the content eviction policy. We use analytical and mathematical modeling to derive the effectiveness and efficiency of our contribution. Results present a better hit ratio due to dynamic adjustment of the content popularity threshold and the elimination of caching redundancy from the on-path routers.