Universiti Teknologi Malaysia Institutional Repository

A reliable merging link scheme using weighted Markov Chain Model in vehicular Ad Hoc networks

Emmanuel, Siman and Isnin, Ismail Fauzi and Mohamad, Mohd. Murtadha (2022) A reliable merging link scheme using weighted Markov Chain Model in vehicular Ad Hoc networks. Sensors, 22 (13). pp. 1-17. ISSN 1424-8220

[img] PDF
773kB

Official URL: http://dx.doi.org/10.3390/s22134861

Abstract

The vehicular ad hoc network (VANET) is a potential technology for intelligent transportation systems (ITS) that aims to improve safety by allowing vehicles to communicate quickly and reliably. The rates of merging collision and hidden terminal problems, as well as the problems of picking the best match cluster head (CH) in a merged cluster, may emerge when two or more clusters are merged in the design of a clustering and cluster management scheme. In this paper, we propose an enhanced cluster‐based multi‐access channel protocol (ECMA) for high‐throughput and effective access channel transmissions while minimizing access delay and preventing collisions during cluster merging. We devised an aperiodic and acceptable merge cluster head selection (MCHS) algorithm for selecting the optimal merge cluster head (MCH) in centralized clusters where all nodes are one‐hop nodes during the merging window. We also applied a weighted Markov chain mathematical model to improve accuracy while lowering ECMA channel data access transmission delay during the cluster merger window. We presented extensive simulation data to demonstrate the superiority of the suggested approach over existing state‐of‐the‐arts. The implementation of a MCHS algorithm and a weight chain Markov model reveal that ECMA is distinct and more efficient by 64.20–69.49% in terms of average network throughput, end‐to‐end delay, and access transmission probability.

Item Type:Article
Uncontrolled Keywords:clustering, merge collision, merge window, merging link, predicting probability, weight value, weighted Markov chain
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:104021
Deposited By: Yanti Mohd Shah
Deposited On:14 Jan 2024 00:42
Last Modified:14 Jan 2024 00:42

Repository Staff Only: item control page