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.
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Danehchin, R. Enhancing fault tolerance in vehicular ad-hoc networks using artificial bee colony algorithm-based spanning trees. Int J Syst Assur Eng Manag 13, 1722–1732 (2022). https://doi.org/10.1007/s13198-021-01530-z
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DOI: https://doi.org/10.1007/s13198-021-01530-z