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 needs 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 the greedy algorithms. The solutions obtained from our solution approach are within 1.6% from global optimality.

中文翻译：

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截止日期的内容缓存优化调度

网络边缘的内容缓存是减轻回程网络负担的一种很有前途的技术。在本文中，我们考虑在具有有限缓存容量的基站中随时间进行内容缓存。由于内容的流行程度可能会随时间变化，因此需要相应地更新缓存的内容。另外，所请求的内容可以具有递送截止期限，在该期限内需要获得该内容。基于这些动机，我们解决了在交付期限和缓存容量约束下的时隙系统中内容缓存的最佳调度。目的是最小化捕获回程链路负载的成本函数。对于我们的优化问题，我们通过减少分区问题来证明其NP硬度。为了解决问题，通过数学重新公式化，我们基于反复应用列生成算法和按问题定制的舍入算法，开发了一种解决方案方法。另外，基于文献中的现有算法开发了两种贪婪算法。最后，我们提供了广泛的仿真，与贪婪算法相比，这些仿真验证了我们的解决方案方法在获得接近最佳解决方案方面的有效性。通过我们的解决方案方法获得的解决方案与全局最优值相比，误差在1.6％以内。