Optimal Geographic Caching in Finite Wireless Networks

TL;DR

This paper develops a framework to optimize content caching in finite D2D networks by modeling device locations as a binomial point process, aiming to maximize hit probability based on device proximity and activity.

Contribution

It introduces a generic analysis framework for coverage probability in finite regions and derives optimal caching probabilities considering device activity levels.

Findings

Optimal caching probability depends on the number of active devices.

Coverage probability analysis tailored for finite regions.

Framework applicable to various finite-area D2D scenarios.

Abstract

Cache-enabled device-to-device (D2D) networks turn memory of the devices at the network edge, such as smart phones and tablets, into bandwidth by enabling asynchronous content sharing directly between proximate devices. Limited storage capacity of the mobile devices necessitates the determination of optimal set of contents to be cached on each device. In order to study the problem of optimal cache placement, we model the locations of devices in a finite region (e.g., coffee shop, sports bar, library) as a uniform binomial point process (BPP). For this setup, we first develop a generic framework to analyze the coverage probability of the target receiver (target-Rx) when the requested content is available at the $k^{th}$ closest device to it. Using this coverage probability result, we evaluate optimal caching probability of the popular content to maximize the total hit probability. Our analysis concretely demonstrates that optimal caching probability strongly depends on the number of simultaneously active devices in the network.