PePC: popularity based early predictive caching in named data networks

Abstract

Caching technique used in Information Centric/Named Data Networks (ICN/NDN) governs the response time. Cache capacity constraints at routers have led to investigations on different caching mechanisms to improve effective caching and performance in terms of improved cache hits and response time for requested contents. However, most caching methods remain oblivious to the dynamics of cache occupancy. In this paper, we describe a new caching technique which predicts whether a new content has to be cached or not considering the current occupancy level of the cache. Our prediction based approach is inspired by the Random Early Detection (RED) method used for queue management. Similar to RED, our predictive caching algorithm bases its decision to cache a content using the average cache occupancy and also takes into account the content popularity. When the cache occupancy is low, we cache every possible content, and with the increasing cache occupancy, the decision to cache the content is decided based on the content popularity and the occupancy threshold parameters. We perform simulation based studies using discrete event simulator to assess its performance. We also compare the performance of our predictive caching method with five different popular caching methods used in Named Data Networks to show its superiority over others.