Enhancing fault tolerance in vehicular ad-hoc networks using artificial bee colony algorithm-based spanning trees

Ramin Danehchin ()
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Ramin Danehchin: University of Tabriz

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 4, No 15, 1722-1732

Abstract: Abstract Providing efficient unicast communication is a crucial challenge in Vehicular Ad-hoc Networks (VANETs). Road-Side Unit (RSU) guarantees unicast communication by constructing the spanning tree among vehicles. Recent papers proposed artificial intelligence-based algorithms for constructing a group of spanning trees in VANETs to deal with the failure of nodes and fast-moving vehicles. The algorithms consider the Euclidean distance between vehicles as a weight function. In such approaches, it is possible for a common non-leaf vehicle in all obtained spanning trees to become unavailable; the spanning trees of the VANETs become paralyzed. To address this challenge, in this paper, a two-phase near-optimal spanning tree contraction in the RSU that is named Fault Tolerance near-optimal Spanning Trees (FTST) is proposed. In the FTST, first, the Multi-objective Artificial Bee Colony (MABC) algorithm is used to construct a spanning tree for the input VANET’s graph with the near-minimum weight and the maximum number of leaves. Then, the second phase of the FTST tries to construct a near-minimum spanning tree with the maximum number of leaves so that the first step spanning tree’s non-leaves can leave off. Implementation results demonstrate the FTST will be suitable for VANET’s applications by improving the fault tolerance of the network and reducing the injected traffic into it.

Keywords: Fault tolerance; Multi-objective artificial bee colony (MABC) algorithm; Near-optimal spanning trees; Vehicular ad-hoc networks (VANETs) (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-021-01530-z

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