Adaptive scheduled partitioning technique for reliable emergency message broadcasting in VANET for intelligent transportation systems

Lokesh, S (2023) Adaptive scheduled partitioning technique for reliable emergency message broadcasting in VANET for intelligent transportation systems. Automatika, 64 (2). pp. 341-354. ISSN 0005-1144

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Abstract

This paper aims to enable accurate and reliable emergency message broadcast in Vehicular Ad hoc Network (VANET). The VANET is the most common topology used in Intelligent Transportation Systems (ITS), where changes in standard topology due to the mobility of nodes create challenges in broadcasting the emergency message and efficient data delivery in both highway and urban scenarios. The main problems in urban scenarios are channel contention, message redundancy and road structure. To obtain information, broadcast protocols for VANET typically use beacon messages, which are distributed among the vehicles. When multiple vehicles transmit messages at the same time, a broadcast storm occurs and vehicles experience message delivery failure. To address this problem, Adaptive Scheduled Partitioning and Broadcasting Technique (ASPBT) for emergency message broadcast and beacon retransmissions for message reliability were proposed. This protocol dynamically modifies several partitions and beacon periodicity to reduce the number of retransmissions. Later, the partition size is determined by estimating the network transmission density of each partition schedule via the Black Widow Optimization (BWO) algorithm is proposed. The simulation is carried out with different network densities at the vehicle speed of 110 km/h, a direct path length of 12 km under a four-way direction path and performance analysis was performed.

Item Type: Article
Subjects: C Computer Science and Engineering > Optimization Techniques
C Computer Science and Engineering > Adhoc Networks
Divisions: Computer Science and Engineering
Depositing User: Users 5 not found.
Date Deposited: 26 Jul 2024 09:07
Last Modified: 26 Jul 2024 09:07
URI: https://ir.psgitech.ac.in/id/eprint/826

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