Social-aware mobile data offloading algorithm through small cell backhaul network: Direct and indirect user influence perspectives

Abstract

Mobile data offloading is a promising solution to mitigate the explosive increasing traffic load in a mobile network operator (MNO)’s core network, where the MNO can deliver the mobile traffic without traversing the core network. Most of all, the social networking traffic has increased sharply due to the proliferation of online social networking services (SNSs), such as Facebook and Instagram. Thus, an effective mobile data offloading algorithm that considers the social context needs to be developed. In this paper, exploiting the social context from two perspectives, we propose the model to estimate the application selection probability considering a direct influence by each user and indirect influence by other users. Based on this, we propose the mobile data offloading algorithm considering the social context via small cell backhaul network, in order to maximize the quality of service (QoS) of a user and reduce the core network load of an MNO to the maximum. The results of the performance evaluation show that the proposed algorithm considering the social context can enhance the QoS of users and alleviate the core network load better than the other algorithm that does not exploit the social context.