Coding for Caches in the Plane

TL;DR

This paper analyzes wireless cache placement strategies in the plane, demonstrating that coded data allocation generally reduces retrieval costs compared to uncoded methods, especially under distance-dependent cost measures.

Contribution

It introduces a framework for comparing coded and uncoded data placement in wireless caches modeled by point processes, quantifying the benefits of coding.

Findings

Coded allocation outperforms uncoded for increasing cost functions.

Quantified benefits of coding for specific cost measures.

Validated results with real-world mobile base station data.

Abstract

We consider wireless caches located in the plane according to general point process and specialize the results for the homogeneous Poisson process. A large data file is stored at the caches, which have limited storage capabilities. Hence, they can only store parts of the data. Clients can contact the caches to retrieve the data. We compare the expected cost of obtaining the complete data under uncoded as well as coded data allocation strategies. It is shown that for the general class of cost measures where the cost of retrieving data is increasing with the distance between client and caches, coded allocation outperforms uncoded allocation. The improvement offered by coding is quantified for two more specific classes of performance measures. Finally, our results are validated by computing the costs of the allocation strategies for the case that caches coincide with currently deployed mobile base stations.