Graph-Based Edge-User Collaborative Caching with Social Attributes

Abstract

Collaborative caching in edge-user architecture has been regarded as one of the most promising technologies to release the pressure of core networks and reduce the content download delay. However, the caching resources at edge servers and devices are limited, so how to utilize their cache space efficiently has become a significant issue. This paper introduces a three-tier caching framework consisting of a macro-cell base station (MBS), multiple small-cell base stations (SBSs), and user equipments (UEs). In this framework, by combining physical and social attributes, we propose a directed graph-based edge-user collaborative caching (DG-EUCC) strategy to minimize the content download delay. Specifically, the wireless communication networks between the different types of nodes at the SBSs tier and the UEs tier are simplified to a one-tier directed graph (DG) with social attributes, to realize the simplification of the system model. Further, we design a DG-based collaborative caching strategy to minimize the content download delay, where each node caches the most popular contents according to the weighted content popularity set. Simulation results show that, compared with the benchmark strategies, the proposed DG-EUCC strategy can effectively reduce average download delay.