IEEE Project Abstract

In recent years, total mobile traffic has increased explosively, and this has led to severetraffic load on the mobile network operator (MNO)'s core network. Mobile data ofoading is a promising solution to alleviate the core network's load. Through such mobile data ofoading, MNO can reroute themobile trafc 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 ofoading. In this paper, in order to apply the social context to mobile data ofoading, 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 ofoading algorithm to maximize the quality of service (QoS) of users in a small cell backhaul ofoading environment. The performance evaluation results demonstrate that the proposed algorithm outperforms the other algorithms that do not consider the social context.