Characterizing Interest Aggregation in Content-Centric Networks

TL;DR

This paper analyzes Interest aggregation in Content-Centric Networks, revealing that under realistic conditions, it benefits only a small fraction of Interests, questioning the effectiveness of PITs in these networks.

Contribution

It provides a novel analytical framework and simulation results to evaluate Interest aggregation, highlighting its limited benefits in practical scenarios.

Findings

Interest aggregation benefits a small fraction of Interests

PIT size growth may negate its intended advantages

Analytical model helps assess cache network performance

Abstract

The Named Data Networking (NDN) and Content-Centric Networking (CCN) architectures advocate Interest aggregation as a means to reduce end-to-end latency and bandwidth consumption. To enable these benefits, Interest aggregation must be realized through Pending Interest Tables (PIT) that grow in size at the rate of incoming Interests to an extent that may eventually defeat their original purpose. A thorough analysis is provided of the Interest aggregation mechanism using mathematical arguments backed by extensive discrete-event simulation results. We present a simple yet accurate analytical framework for characterizing Interest aggregation in an LRU cache, and use our model to develop an iterative algorithm to analyze the benefits of Interest aggregation in a network of interconnected caches. Our findings reveal that, under realistic assumptions, an insignificant fraction of Interests in the system benefit from aggregation, compromising the effectiveness of using PITs as an integral component of Content-Centric Networks.