A provably efficient online collaborative caching algorithm for multicell-coordinated systems

TL;DR

This paper introduces a provably efficient online collaborative caching algorithm for multicell systems, minimizing costs without prior knowledge of content popularity, and demonstrates its near-optimal performance through theoretical analysis and simulations.

Contribution

The paper presents the first online collaborative caching algorithm with a proven competitive ratio for multicell systems, without needing content popularity estimates.

Findings

Achieves a competitive ratio of O(log n)

Proves the optimal competitive ratio is Ω(log n / log log n)

Performs close to optimal offline schemes in simulations

Abstract

Caching at the base stations brings the contents closer to the users, reduces the traffic through the backhaul links, and reduces the delay experienced by the cellular users. The cellular network operator may charge the content providers for caching their contents. Moreover, content providers may lose their users if the users are not getting their desired quality of service, such as maximum tolerable delay in Video on Demand services. In this paper, we study the collaborative caching problem for a multicell-coordinated system from the point of view of minimizing the total cost paid by the content providers. We formulate the problem as an Integer Linear Program and prove its NP-completeness. We also provide an online caching algorithm that does not require any knowledge about the contents popularities. We prove that the online algorithm achieves a competitive ratio of $\mathcal{O}(\log(n))$, and we show that the best competitive ratio that any online algorithm can achieve is $\Omega(\frac{\log(n)}{\log\log(n)})$. Therefore, our proposed caching algorithm is provably efficient. Through simulations, we show that our online algorithm performs very close to the optimal offline collaborative scheme, and can outperform it when contents popularities are not properly estimated.