LAUSR

Based on IEEE 802.11p and IEEE 1609.4 protocols, vehicular ad hoc network (VANETs) transmit safety and non-safety packets through multichannel. Due to the increase in usage of various infotainment applications, the quality-of-service (QoS) is not met in VANETs resulting in high congestion over transmission. To ensure QoS in safety, transport efficiency and infotainment applications, we proposed a multichannel approach with optimal minimum contention window (CW) technique named as reinforcement learning and multichannel MAC protocol (RL- M -MAC). In this paper, an algorithm is proposed to select the channel for transmission. Proposed RL-M-MAC protocol uses conditional Markov chain technique to identify the optimal CW value. Theoretical performance analysis and extensive simulation results shows that RL-M-MAC protocol can support QoS services with lower collision probability, higher throughput, and high fairness.