Abstract
IoV is the latest application of VANET and is the alliance of Internet and IoT. With the rapid progress in technology, people are searching for a traffic environment where they would have maximum collaboration with their surroundings which comprise other vehicles. It has become a necessity to find such a traffic environment where we have less traffic congestion, minimum chances of a vehicular collision, minimum communication delay, fewer communication errors, and a greater message delivery ratio. For this purpose, a vehicular ad hoc network (VANET) was devised where vehicles were communicating with each other in an infrastructureless environment. In VANET, vehicles communicate in an ad hoc manner and communicate with each other to deliver messages, for infotainment purposes or for warning other vehicles about emergency scenarios. Unmanned aerial vehicle- (UAV-) assisted VANET is one of the emerging fields nowadays. For VANET’s routing efficiency, several routing protocols are being used like optimized link state routing (OLSR) protocol, ad hoc on-demand distance vector (AODV) routing protocol, and destination-sequenced distance vector (DSDV) protocol. To meet the need of the upcoming era of artificial intelligence, researchers are working to improve the route optimization problems in VANETs by employing UAVs. The proposed system is based on a model of VANET involving interaction with aerial nodes (UAVs) for efficient data delivery and better performance. Comparisons of traditional routing protocols with UAV-based protocols have been made in the scenario of vehicle-to-vehicle (V2V) communication. Later on, communication of vehicles via aerial nodes has been studied for the same purpose. The results have been generated through various simulations. After performing extensive simulations by varying different parameters over grid sizes of 300 × 1500 m to 300 × 6000 m, it is evident that although the traditional DSDV routing protocol performs 14% better than drone-assisted destination-sequenced distance vector (DA-DSDV) when we have number of sinks equal to 25, the performance of drone-assisted optimized link state routing (DA-OLSR) protocol is 0.5% better than that of traditional OLSR, whereas drone-assisted ad hoc on-demand distance vector (DA-AODV) performs 22% better than traditional AODV. Moreover, if we increase the number of sinks up to 50, it can be clearly seen that the DA-AODV outperforms the rest of the routing protocols by up to 60% (either traditional routing protocol or drone-assisted routing protocol). In addition, for parameters like MAC/PHY overhead and packet delivery ratio, the performance of our proposed drone-assisted variants of protocols is also better than that of the traditional routing protocols. These results show that our proposed strategy performs better than the traditional VANET protocols and plays important role in minimizing the MAC/PHY and enhancing the average throughput along with average packet delivery ratio.
Highlights
Internet of Vehicles (IoV) is the new form of vehicular ad hoc network (VANET) and is the alliance of Internet and IoT
IoV is the new form of VANET and is the alliance of Internet and IoT
We considered optimized link state routing (OLSR), ad hoc on-demand distance vector (AODV), and destination-sequenced distance vector (DSDV) protocol to check their efficiency in our first scenario
Summary
IoV is the new form of VANET and is the alliance of Internet and IoT. VANET is a type of wireless network where vehicles interact with each other as well as with roadside units within a short distance [1]. We have devised an optimized solution for enhancing the network efficiency in terms of better throughput, average packet delivery ratio, and less MAC/PHY overhead. Such proposed scheme will help in having better network experience in traffic, and enhance the medicine and healthcare, agriculture, disaster, and emergency scenarios and provide environmental and surrounding information and a better solution for communication over a congested road. E end results of simulations show that our proposed strategy have better performance in terms of average packet delivery ratio, MAC/PHY overhead, and average throughput for larger grid size involving a greater number of vehicular as well as sink nodes
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