Information-Centric Virtualization for Software-Defined Statistical QoS Provisioning Over 5G Multimedia Big Data Wireless Networks

The multimedia transmission represents a typical big data application in the fifth-generation (5G) wireless networks. However, supporting multimedia big data transmission over 5G wireless networks imposes many new and open challenges because multimedia big data services are both time-sensitive and bandwidth-intensive over time-varying wireless channels with constrained wireless resources. To overcome these difficulties, in this paper we propose the information-centric virtualization architectures for software-defined statistical delay-bounded quality of service (QoS) provisioning over 5G multimedia big data wireless networks. In particular, our proposed schemes integrate the three 5G-promising candidate techniques to guarantee the statistical delay-bounded QoS for multimedia big data transmissions: 1) information-centric network (ICN), to derive the optimal in-network caching locations for multimedia big data; 2) network functions virtualization (NFV), to abstract the PHY-layer infrastructures into several virtualized networks to derive the optimal multimedia data contents delivery paths; and 3) software-defined networks (SDNs), to dynamically reconfigure wireless resources allocation architectures through the SDN-control plane. Under our proposed architectures, to jointly optimize the implementations of NFV and SDN techniques under ICN architectures, we develop the three virtual network selection and transmit-power allocation schemes to: 1) maximize single user’s effective capacity; 2) jointly optimize the aggregate effective capacity and allocation fairness over all users; and 3) coordinate non-cooperative gaming among all users, respectively. By simulations and numerical analyses, we show that our proposed architectures and schemes significantly outperform the other existing schemes in supporting the statistical delay-bounded QoS provisioning over the 5G multimedia big data wireless networks.