Open AccessA Novel Collision Supervision and Avoidance Algorithm for Scalable MAC of Vehicular Networks
Author(s) -
Shuai WANG,
Yan LU,
Jie ZHU,
Ping WANG
Publication year - 2021
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2020.12.001
Subject(s) - computer science , exponential backoff , scalability , computer network , throughput , network packet , markov chain , collision avoidance , collision , latency (audio) , low latency (capital markets) , markov process , real time computing , wireless , computer security , telecommunications , database , statistics , mathematics , machine learning
In order to meet low‐latency and ultrareliable requirements on safety services in vehicular networks, this paper proposes a novel Collision supervision and avoidance (CSA) algorithm for the contention based scalable media access control protocol. The two‐dimensional Markov chain model of adaptive backoff state transition criterion in CSA has been built, which could efficiently match the backoff states of nodes to the dynamic changes of vehicular networks. The scalable transmissions can be achieved through supervised trend and matching backoff mechanisms with three adaptive backoff modes. The packet transmit probabilities for the backoff modes have been derived with the theoretical result of the enhanced throughput. The simulation results show the remarkable scalability performance such as normalized throughput > 0.92, PDR > 86% and delay < 6.5ms even in the high‐density and high‐mobility environment.