Social Context-Aware Mobile Data Offloading Algorithm via Small Cell Backhaul Networks

Abstract

In recent years, total mobile traffic has increased explosively, and this has led to severe traffic load on the mobile network operator (MNO)'s core network. Mobile data offloading is a promising solution to alleviate the core network's load. Through such mobile data offloading, MNO can reroute the mobile traffic to other access networks using various radio access technologies, such as WiFi, opportunistic communications, and so on. In addition, social networking traffic has risen sharply due to the popularity of online social networking services, such as Facebook and Twitter. Thus, we need to consider a social context for effective mobile data offloading. In this paper, in order to apply the social context to mobile data offloading, we model the social context in terms of two aspects: the user's social relationships and application's popularity. In addition, we propose a social context-aware mobile data offloading algorithm to maximize the quality of service (QoS) of users in a small cell backhaul offloading environment. The performance evaluation results demonstrate that the proposed algorithm outperforms the other algorithms that do not consider the social context.