Abstract
In the past two decades, the automotive industry has undergone tremendous changes, as this field has become one of the fastest developing and growing fields, especially with the progress of global digitization and massive research related to networks. So, it comes as no surprise that self-driving vehicles are ubiquitous mainly relying on Vehicular ad-hoc networks (VANETs). This transformation ensures improved road navigation and traffic congestion avoidance by relying on Rapid Data Deployment (DD). On the other hand, although DD achieves high connection reliability, it may affect network bandwidth and performance. In addition, excessive DD causes frequent link outages resulting in reduced data delivery, massive packet loss, and premature end of network life. This paper presents an integrated architecture proposal for a vehicle dynamic assistance architecture, based on reliable methods to ensure steering accuracy while minimizing the energy expended for controlling the DD rate via VANETs. The proposed architecture integrates between Software-Defined Networks (SDN) and fog computing based on dealing with the mobility factors that exploit vehicle communication behaviors. Such integration will aid in improving network performance in terms of packet delivery and DD. The study also discusses how to take into consideration the Euclidean distance, geographical routing information, residual power ratio, and latency time to maximize network stability and avoid possible link disruption. The simulation results prove that there is a 62% to 70% enhancement of the whole power consumption and network throughput, depending on the implementation of the proposed position-based routing approach. Interestingly, the proposed routing protocol is a dual-phase routing protocol with a 90% of SDN data packet delivery ratio and an 82% of SDN data loss reduction. So, when the SDN fails to deliver packets, the proposed position-based routing handles them as a parallel mechanism of SDN.
Published Version
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