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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 11/2018

31.10.2016 | Original Article

Simulation, modeling and analysis of master node election algorithm based on signal strength for VANETs through Colored Petri nets

verfasst von: Syed Asad Hussain, Naeem Akhtar Khan, Ayesha Sadiq, Farooq Ahmad

Erschienen in: Neural Computing and Applications | Ausgabe 11/2018

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Abstract

The broadcast storm problem causes redundancy, contention and collision of messages in a network, particularly in vehicular ad hoc networks (VANETs) where number of participants can grow arbitrarily. This paper presents a solution to this problem in which a node is designated as a master through an election process. Moreover, an algorithm is proposed for asynchronous VANETs to select a master node, where the participants (i.e., vehicles) can communicate with each other directly (single-hop). The proposed algorithm is extrema-finding in a way that a node having maximum signal strength is elected as a master node and each vehicle continues communication with the master until the master node keeps its signal strength at the highest level and remains operational too. This paper further presents the Petri net-based modeling of the proposed algorithm for evaluation which is going to be presented for the first time in leader election algorithm in VANETs. Verification of the proposed algorithm is carried out through state space analysis technique.
Vorheriger Artikel An evolutionary framework in modelling of multi-output characteristics of the bone drilling process
Nächster Artikel Dynamic multi-objective optimization control for wastewater treatment process

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Metadaten
Titel
Simulation, modeling and analysis of master node election algorithm based on signal strength for VANETs through Colored Petri nets
verfasst von
Syed Asad Hussain
Naeem Akhtar Khan
Ayesha Sadiq
Farooq Ahmad
Publikationsdatum
31.10.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 11/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2622-z

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