A location‐aware network virtualization and reconfiguration for 5G core network based on SDN and NFV. (11th February 2020) - Kim, Yong‐hwan; Gil, Joon‐Min; Kim, Dongkyun
Summary: In 5G networks, mobile network and service functions run as software on general‐purpose servers that are distributed across remote sites. Dedicated networks, such as Internet of Things (IoT) network, disaster network, and immersive media network, are virtualized as software solutions on common hardware equipment. This means a new network can be easily provisioned by modifying the configurations of the network based on software‐defined networking (SDN) and network functions virtualization (NFV). Furthermore, the 5G core network architecture toward flat architecture with distributed cloud is a key solution for providing service flexibility and scalability in order to handle an explosive increase in mobile data traffic. To create heterogeneous networks and services on 5G networks, we propose a location‐aware network virtualization method that aims at minimizing the network load and resource cost by appropriately selecting the relevant cloud (including Virtual Machines (VMs), virtual network function [VNF] nodes, applications, and resources) and mobile core entities to provide the required virtual networking services that facilitate secure isolation of the virtual networks with automated resource convergence. In addition, we propose a selective mobility management scheme for service continuity in cases of user equipment (UE) handover. The numerical results show the trade‐off between the different cost factors, ie, network cost and service resources cost in terms of the number of deployed clouds on 5G core networks. Abstract : This paper proposes a location‐aware network virtualization method on the software‐defined networking (SDN)/network functions virtualization (NFV)Űbased 5G mobile network architecture with the distributed cloud environments. For this, we propose a cloud selection model to provide the required virtual networking services with edge cloud resources based on the location and the resource utilization properties. Additionally, we propose a network virtualization method for data transmission between the user, the selected edge cloud for the required user service, and the network entities including the AP and the SDN switches.