Optimal Scheduling of Content Caching Subject to Deadline

TL;DR

This paper addresses the complex problem of optimally scheduling content caching in networks with limited cache capacity and delivery deadlines, proposing a novel solution that achieves near-optimal results through advanced algorithms.

Contribution

It introduces a new NP-hard optimization model for cache scheduling with deadlines and develops a column generation and rounding approach for near-optimal solutions.

Findings

Solution approach achieves solutions within 1% of the global optimum.

Proposed algorithms outperform existing greedy methods.

Effective in minimizing backhaul load under constraints.

Abstract

Content caching at the edge of network is a promising technique to alleviate the burden of backhaul networks. In this paper, we consider content caching along time in a base station with limited cache capacity. As the popularity of contents may vary over time, the contents of cache need to be updated accordingly. In addition, a requested content may have a delivery deadline within which the content need to be obtained. Motivated by these, we address optimal scheduling of content caching in a time-slotted system under delivery deadline and cache capacity constraints. The objective is to minimize a cost function that captures the load of backhaul links. For our optimization problem we prove its NP-hardness via a reduction from the Partition problem. For problem solving, via a mathematical reformulation, we develop a solution approach based on repeatedly applying a column generation algorithm and a problem-tailored rounding algorithm. In addition, two greedy algorithms are developed based on existing algorithms from the literature. Finally, we present extensive simulations that verify the effectiveness of our solution approach in obtaining near-to-optimal solutions in comparison to greedy algorithms. The solutions obtained from our solution approach are within 1% from the global optimum.