Soft Cache Hits and the Impact of Alternative Content Recommendations on Mobile Edge Caching

TL;DR

This paper explores how recommending related content can improve mobile edge caching efficiency by reducing hard cache misses, using a new soft cache hit model and analyzing its benefits with real datasets.

Contribution

It introduces the concept of soft cache hits in edge caching, departing from traditional hard miss assumptions, and formulates an optimal caching strategy considering delayed access and related content recommendations.

Findings

Significant caching gains with related content recommendations.

Effective in both synthetic and real datasets.

Potential to reduce backhaul load and improve user satisfaction.

Abstract

Caching popular content at the edge of future mobile networks has been widely considered in order to alleviate the impact of the data tsunami on both the access and backhaul networks. A number of interesting techniques have been proposed, including femto-caching and "delayed" or opportunistic cache access. Nevertheless, the majority of these approaches suffer from the rather limited storage capacity of the edge caches, compared to the tremendous and rapidly increasing size of the Internet content catalog. We propose to depart from the assumption of hard cache misses, common in most existing works, and consider "soft" cache misses, where if the original content is not available, an alternative content that is locally cached can be recommended. Given that Internet content consumption is increasingly entertainment-oriented, we believe that a related content could often lead to complete or at least partial user satisfaction, without the need to retrieve the original content over expensive links. In this paper, we formulate the problem of optimal edge caching with soft cache hits, in the context of delayed access, and analyze the expected gains. We then show using synthetic and real datasets of related video contents that promising caching gains could be achieved in practice.