The purpose of this paper is to introduce a new data dissemination model in order to improve the performance of transmission in VANET. It proposes a protocol named Epidemic and Transmission-Segment-based Geographic Routing (ETSGR) and outlining the issues due to high mobility of nodes and uncertain physical topologies in the network. The proposed ETSGR is mainly used to analyze the vehicle state, direction, distance, traffic density and link quality of the network.
This research work based on ETSGR protocol mainly uses epidemic algorithm in order to find the vehicle state based on susceptible, infected and recovered (SIR) model. Furthermore, the vehicle position and finding the head node in the network is utilized using the transmission segment protocol based on geographic routing and analyses each node to form the segments and find the destination to transmit the data in timely manner.
The paper provides the enhancement of the performance based on some metrics such as end-to-end delay that obtained 0.62%, data throughput as 32.3%, packet delivery ratio as 67% and one-hop communication as 13%. The proposed ETSGR protocol analyzes the state of the vehicle correctly and each node segmented to transmit the data with the timely manner and obtaining reliable performance even with high mobility of nodes in the network.
The proposed ETSGR protocol may have some limitation when considering the timing which should improve even in increasing many number of vehicles and different road segments.
This paper includes some suggestions for the practical deployment of the approach in which a real-time traffic analysis can be evaluated for taking prior actions during an emergency situation and proper dissemination of data in timely manner can help utilize the guidance of proper planning of roads.
This research fulfills an enhanced protocol to improve the performance of data dissemination.
D.N.S., R.K. and S., B. (2021), "Data dissemination model using Epidemic and Transmission-Segment-based Geographic Routing protocol: a new perspective in vehicular ad hoc networks", International Journal of Intelligent Computing and Cybernetics, Vol. 14 No. 2, pp. 287-301. https://doi.org/10.1108/IJICC-12-2020-0210
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