SDN Enabled Dual Cluster Head Selection and Adaptive Clustering in 5G-VANET

Nowadays, self-driving vehicles which would shoulder the burden of driving and set free human on board are gradually becoming a reality. Consequently, the supporting of growing in-vehicle data traffic will be challenging in future 5G and vehicular networks, due to the high mobility nature of vehicles and the densified irregular distribution on road especially during rush time. Therefore in this paper, a Software-Defined Networking (SDN) enabled integrated 5G-VANET architecture is proposed to improve heterogeneous network (HetNet) management and aggregate vehicle traffic through IEEE 802.11p; a novel vehicle clustering method and dual cluster head design are then introduced to reduce signaling overhead and enhance the overall communication quality in 5G-VANET HetNet under the coordination of SDN. It is also proved by simulation that the proposed design reduced 5G users' blocking probability to the operators services with a back-up cluster head (CH) in each cluster, and also realized adaptive clustering without excessive SDN's processing delay.