Joint Caching and Pricing Strategies for Popular Content in Information Centric Networks

TL;DR

This paper presents a game-theoretic framework for joint caching and pricing strategies in Information Centric Networks, revealing that optimal caching is a threshold-based all-or-nothing policy driven by content popularity.

Contribution

It introduces a novel analytical model combining caching and pricing in ICNs, demonstrating that Nash caching strategies are binary and depend on content popularity thresholds.

Findings

Nash caching strategies are 0-1 (all or nothing).

Optimal caching thresholds depend on content popularity.

Pricing and caching decisions can be decoupled into separate problems.

Abstract

We develop an analytical framework for distribution of popular content in an Information Centric Network (ICN) that comprises of Access ICNs, a Transit ICN and a Content Provider. Using a generalized Zipf distribution to model content popularity, we devise a game theoretic approach to jointly determine caching and pricing strategies in such an ICN. Under the assumption that the caching cost of the access and transit ICNs is inversely proportional to popularity, we show that the Nash caching strategies in the ICN are 0-1 (all or nothing) strategies. Further, for the case of symmetric Access ICNs, we show that the Nash equilibrium is unique and the caching policy (0 or 1) is determined by a threshold on the popularity of the content (reflected by the Zipf probability metric), i.e., all content more popular than the threshold value is cached. We also show that the resulting threshold of the Access and Transit ICNs, as well as all prices can be obtained by a decomposition of the joint caching and pricing problem into two independent caching only and pricing only problems.