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.
Highlights
We address optimal scheduling of cache updates taking into account the downloading cost subject to delivery deadline and cache capacity constraints
We investigate joint impact of deadline constraint and cache updates in content caching and show how much gain can be achieved
OUR CONTRIBUTIONS We investigate scheduling of content caching in a base station (BS) with limited caching capacity in a time-slotted system under delivery deadline and cache capacity constraints
Summary
W HEREAS the amount of data traffic is exponentially growing, it has been realized that the major portion of the data traffic originates from duplicated downloads of a few popular contents [1]. We investigate joint impact of deadline constraint and cache updates in content caching and show how much gain can be achieved As another contribution, we provide a systematic optimization approach for solving the problem via applying column generation. Our objective is to optimally schedule the updates across the time slots so as to minimize the total cost of obtaining the requested contents by users. The problem is formulated as an integer linear program (ILP), taking into account the size of contents, capacity of the cache, deadlines of requests, and costs of content downloading and cache updating. The problem is how to optimally Schedule Content Caching subject to Deadline (SCCD) with the objective of minimizing the total cost of content downloading. When content scheduling is optimized from an application viewpoint (see, e.g., [16], [20], [24]), system modeling typically does not go down to physical-layer details
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