Abstract:
In vehicle to vehicle communications, there are many issues that need to be addressed. One of these issues is the frequent beaconing that causes high network congestion i...Show MoreMetadata
Abstract:
In vehicle to vehicle communications, there are many issues that need to be addressed. One of these issues is the frequent beaconing that causes high network congestion in the shared channel. Therefore, it affects other applications and protocols especially the safety-related ones. This situation becomes even worse in high densities where the number of vehicles becomes larger. Thus, scalable protocols are required in dense conditions in order to increase cooperative awareness between vehicles and reduce network congestion to keep network resources free as much as possible for other applications and protocols. In this paper, we propose a VANET scalable scheme that uses fuzzy logic system to adapt the beacon generation rate. This fuzzy logic system uses five inputs, channel busy time (CBT), signal to interference-noise ratio (SINR), packet delivery ratio (PDR), number of neighbors and mobility. Then, it generates a congestion rank as an output which will help determine the next beacon frequency. NS-3 simulations have been conducted to investigate the effectiveness of our proposed protocol in terms of average waiting time, total delay and average number of neighbors. The proposed protocol performed well in sparse scenarios and consistently achieved the highest level of scalability compared to fixed rate of 10 beacons per second, JSRC and BRAIN-F in both highway and urban environments.
Date of Conference: 27 November 2017 - 01 December 2017
Date Added to IEEE Xplore: 08 February 2018
ISBN Information: