EEOMA: End-to-end oriented management architecture for 6G-enabled drone communications

We are witnessing a new era in autonomous systems with unprecedented user experiences, excessively recovered road safety and air quality, a wide range of transportation conditions and utilization cases, as well as a plethora of advanced time-sensitive applications. To realise this ambitious vision, Vehicular Ad-hoc Networks (VANET) and drones must have significantly improved communication. They must be remarkably intelligent and capable of simultaneously supporting hyper-fast, ultra-reliable, uninterrupted service, as well as low-latency massive information exchange. Although the Sixth Generation (6G) is successful in providing a seamless integration of heterogeneous elements as well as offering high coverage area with maximizing resource utilization; however, the accomplishment of faster computation, reducing bandwidth usage, low power consumption, and high throughput is remaining critical more than other purposes. This study introduces an End-To-End Oriented Management Architecture (EEOMA) based on fog computing and software-defined network (SDN) technologies for boosting the performance in hybrid networks of Vehicular Ad hoc Network (VANET) and Drone. Two techniques are proposed through EEOMA to manage the data transmission on both the SDN and the drones and meet network constraints: (i) a transport service aggregation approach for simplifying the amount of traffic data traveling across the network bandwidth and (ii) a normalized throughput of a channel with adjusting the interference ratio that indicates medium access control (MAC) layer overhead. The experimental results show that there is 1.2% to 6.1% enhancement of packet delivery and packet loss ratios. More trustworthiness in performance measurement is reached by the proposed EEOMA in terms of total throughput, response time, and power consumption.