Proactive Caching at the Edge Leveraging Influential User Detection in Cellular D2D Networks

Abstract

Caching close to users in a radio access network (RAN) has been identified as a promising method to reduce a backhaul traffic load and minimize latency in 5G and beyond. In this paper, we investigate a novel community detection inspired by a proactive caching scheme for device-to-device (D2D) enabled networks. The proposed scheme builds on the idea that content generated/accessed by influential users is more probable to become popular and thus can be exploited for pro-caching. We use a Clustering Coefficient based Genetic Algorithm (CC-GA) for community detection to discover a group of cellular users present in close vicinity. We then use an Eigenvector Centrality measure to identify the influential users with respect to the community structure, and the content associated to it is then used for pro-active caching using D2D communications. The numerical results show that, compared to reactive caching, where historically popular content is cached, depending on cache size, load and number of requests, up to 30% more users can be satisfied using a proposed scheme while achieving significant reduction in backhaul traffic load.

Cognitive Caching at the Edges for Mobile Social Community Networks: A Multi-Agent Deep Reinforcement Learning Approach

“…CafRepCache is built on multilayer predictive analytics and heuristics to capture and predict content interests coming from dynamic changing clusters [1,2,3,14,31,39] of subscribers in both random and scale-free network, and thus reduce content retrieval delay, improve cache efficiency and reduce resource consumption while enabling responsiveness to heterogeneous dynamically changing network topology, congestion avoidance and varying patterns of content publishers/subscribers. Authors in [30] present InfluentialCache, a proactive caching approach in small cellular device-to-device communication networks. InfluentialCache models D2D cellular network as a social graph in order to utilize its spatial structure.…”

“…To enable fully local network, interest and privacy awareness self-organised multi-layer cognitive edge clouds have been proposed in [32,34] to host various services. Edge and fog computing [3,41,50] integration with various technologies including device-to-device (D2D) communication [30,43], contentcentric architecture [1,11], small cells [48], caching [1,2,3,8] are proposed to support complex networking data services. Intelligent caching services at the edges are envisaged to be important solution providing more localised and more responsive content services to mobile users compared to the traditional CDN approaches.…”

Leveraging mobility and content caching for proactive load balancing in heterogeneous cellular networks

“…Recently, many attempts have been made to incorporate users' mobility for load balancing . Similarly, edge caching has gained popularity in the last decade . Thus far, these works utilized either content caching or mobility; however, no work has explored a framework for joint consideration of both factors for proactive load balancing.…”

“…21,22 Similarly, edge caching has gained popularity in the last decade. 23,24 Thus far, these works utilized either content caching or mobility; however, no work has explored a framework for joint consideration of both factors for proactive load balancing. Next, we present the details of some eminent reactive and proactive LB schemes.…”

Sharing Content at the Edge of the Network Using Game Theoretic Centrality

“…In [6] the authors also proposed a caching scheme based on betweenness centrality and showed that their solution can achieve better gain both in synthetic and real topologies. In [11] the authors proposed a new community detection inspired proactive caching scheme for device-to-device (D2D) enabled networks and used Eigenvector Centrality measure to locate the influential users in the community structure. But in none of the works user preference was taken into account.…”