An Energy-Efficient Controller Management Scheme for Software-Defined Vehicular Networks

The next generation of sustainable vehicular networks are expected to have a wide range of access technologies, multihoming capabilities, and traffic demand and pattern heterogeneity. In order to deliver massive data loads from various services and applications to end-users, network softwarization is a key contributor that mitigates challenges in heterogeneous networks by providing a shared interface platform. SDN-enabled vehicular network provides global snapshot of the network's status and connectivity. However, using a centralized control unit, brings many difficulties, including bottleneck problem and densification issues. A distributed control plane is an alternative, but it raises questions about where to deploy the control units and how many controllers are needed in a given network structure. In this article, we propose an energy-efficient adaptive controller management strategy for distributed software-defined vehicular networks using vehicles' mobility densities and communication latencies between switch-enabled access points. To reduce the number of controllers, the proposed method employs a split-and-merge clustering technique. The performance of the clustering solution was evaluated using realistic mobility traces and compared to several benchmark clustering solutions and variations. The results indicate the efficiency of the proposed scheme in terms of energy consumption, latency, and load on network entities.