Eventually Byzantine Agreement on CDS-based mobile ad hoc network

Chiang, Mao-Lun

doi:10.1016/j.adhoc.2011.07.005

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…Hence, in sparse and dense networks, the minimum calculated desired time (MCDT) technique is suggested, and data dissemination is performed using a context-aware congestion resolution protocol. MCDT determines the node connectivity through a peak-stable link [25,26]. Modified lion algorithm (LA) is also used to compare with GA, and performance analysis was done for cost, complexity, and convergence.…”

Section: Overview Of Previous Workmentioning

confidence: 99%

A Novel Routing Protocol for Realistic Traffic Network Scenarios in VANET

Singh

Kumar

Alshazly

et al. 2021

Wireless Communications and Mobile Computing

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The vehicular ad hoc network (VANET) has traditional routing protocols that evolved from mobile ad hoc networks (MANET). The standard routing protocols of VANET are geocast, topology, broadcast, geographic, and cluster-based routing protocols. They have their limitations and are not suitable for all types of VANET traffic scenarios. Hence, metaheuristics algorithms like evolutionary, trajectory, nature-inspired, and ancient-inspired algorithms can be integrated with standard routing algorithms of VANET to achieve optimized routing performance results in desired VANET traffic scenarios. This paper proposes integrating genetic algorithm (GA) in ant colony optimization (ACO) technique (GAACO) for an optimized routing algorithm in three different realistic VANET network traffic scenarios. The paper compares the traditional VANET routing algorithm along with the metaheuristics approaches and also discusses the VANET simulation scenario for experimental purposes. The implementation of the proposed approach is tested on the open-source network and traffic simulation tools to verify the results. The three different traffic scenarios were deployed on Simulation of Urban Mobility (SUMO) and tested using NS3.2. After comparing them, the results were satisfactory and it is found that the GAACO algorithm has performed better in all three different traffic scenarios. The realistic traffic network scenarios are taken from Dehradun City with four performance metric parameters including the average throughput, packet delivery ratio, end-to-end delay, and packet loss in a network. The experimental results conclude that the proposed GAACO algorithm outperforms particle swarm intelligence (PSO), ACO, and Ad-hoc on Demand Distance Vector Routing (AODV) routing protocols with an average significant value of 1.55%, 1.45%, and 1.23% in three different VANET network scenarios.

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Section: Overview Of Previous Workmentioning

confidence: 99%