Privacy-preserving wireless communications using bipartite matching in social big data

The enhanced wireless data transmissions have enabled the dramatical improvement of the service deployment, such as social networks and big data applications. The multi-channel wireless communication is one of the approaches for disseminating information when the user popularity is large in the dynamic and heterogeneous wireless networking environment. Channel Scheduling Controllers (CSCs) are vital components in data transmissions, which uses Nodes to arrange real-time task scheduling. However, a fixed communication scheduling can hardly meet the requirement of the higher-level privacy protections because of the conflict caused by the performance and security demands. To address this issue, this paper proposes a novel algorithm using communication management techniques for enhancing the security of the systems and supporting applications with real-time constraints. The experimental results depict that the proposed approach can reduce the security cost by up to 32.62% and 23.37% on average, respectively, compare to the traditional methods.