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Issue title: Special section: Recent trends, Challenges and Applications in Cognitive Computing for Intelligent Systems
Guest editors: Vijayakumar Varadarajan, Piet Kommers, Vincenzo Piuri and V. Subramaniyaswamy
Article type: Research Article
Authors: Christy, Jackson Ja; * | Rekha, Da | Vijayakumar, Vb | Carvalho, Glaucio H.S.c
Affiliations: [a] School of Computing Science and Engineering, Vellore Institute of Technology, Chennai Campus, Chennai, Tamilnadu, India | [b] School of Computer Science and Engineering, University of New South Wales, Sydney, Australia | [c] School of Applied Computing, Sheridan College, Oakville, Canada
Correspondence: [*] Corresponding author. Christy Jackson J, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai Campus, Chennai, Tamilnadu, India. E-mail: christyjackson.j@vit.ac.in.
Abstract: Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.
Keywords: VANET, evolutionary algorithm, genetic algorithm, cuckoo search, firefly algorithm, MAC protocol
DOI: 10.3233/JIFS-189134
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8125-8137, 2020
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