Fundamental Limits on Throughput Capacity in Information-Centric Network

TL;DR

This paper analyzes the fundamental throughput and latency limits in information-centric wireless networks with cache expiration, showing how caching impacts network performance as it scales.

Contribution

It provides the first theoretical analysis of throughput and latency limits in cache-enabled information-centric networks with limited cache lifetime.

Findings

Throughput remains constant with network growth under certain conditions.

Caching significantly improves asymptotic network performance.

Simple path search mechanisms retain most benefits of caching.

Abstract

Wireless information-centric networks consider storage as one of the network primitives, and propose to cache data within the network in order to improve latency and reduce bandwidth consumption. We study the throughput capacity and latency in an information-centric network when the data cached in each node has a limited lifetime. The results show that with some fixed request and cache expiration rates, the order of the data access time does not change with network growth, and the maximum throughput order is not changing with the network growth in grid networks, and is inversely proportional to the number of nodes in one cell in random networks. Comparing these values with the corresponding throughput and latency with no cache capability (throughput inversely proportional to the network size, and latency of order $\sqrt{n}$ and the inverse of the transmission range in grid and random networks, respectively), we can actually quantify the asymptotic advantage of caching. Moreover, we compare these scaling laws for different content discovery mechanisms and illustrate that not much gain is lost when a simple path search is used.