Performance Evaluation of Rate Adaptation Algorithms in IEEE802.11p Heterogeneous Vehicular Networks

Abstract

VANET is emerging as a new landscape of mobile ad-hoc networks to make the connected vehicles' projects a reality. The continuous connectivity in VANET is a huge challenge caused by the extremely dynamic network topology and the highly variable number of mobile nodes. Moreover, this specific network faces many challenges to define reliable protocols and mechanisms like rate adaptation schemes. The performance of different VANET applications like traffic management and multimedia delivery depends on the network throughput and the success ratio these networks can provide. Rate adaptation is the key method to maximize the throughput and to avoid performance network degradation by estimating the current channel qualities and deciding the best bitrate for the next frames. Although numerous data rate adaptation mechanisms are available for 802.11 WLANs standards, there is little work dedicated to the IEEE 802.11p rate adaptation in vehicular networks. In this paper, we evaluate and compare the available 802.11 wireless networks rate adaptation mechanisms in various vehicular scenarios to analyze their performance and understand their behavior under different conditions. Five mechanisms were selected to be compared using NS-3 simulations: Minstrel, AARF-CD, CARA, Onoe, and Ideal algorithm. The performance results show that Minstrel is the most stable algorithm since it performs better in dynamic and dense environments when compared with the other algorithms.