Learning automata-based virtual backoff algorithm for efficient medium access in vehicular ad hoc networks

In vehicular ad hoc networks (VANETs), the effect of signal distortions due to the existence of adjoining vehicles and the high degrees of mobility of the nodes affect the reliability of transmission. This paper presents a learning automata (LA)-based solution, named LAVBA, for reliable and efficient medium access control, based on virtual backoff algorithm (VBA), in VANETs. In VBA, a counter is used at each node for fair distributed channel access. The performance of VBA medium access depends on the selection of the sequence number. We use an LA-based approach for obtaining an optimal sequence number. It is observed that the performance of the proposed scheme is improved, when compared to the legacy schemes such as distributed coordination function (DCF) and VBA.