A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach

Youcef Azzoug, Abdelmadjid Boukra and Vasco N. G. J. Soares
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Youcef Azzoug: Department of Informatics, University of Science and Technology Houari Boumediene, 16111 Algiers, Algeria
Abdelmadjid Boukra: Department of Informatics, University of Science and Technology Houari Boumediene, 16111 Algiers, Algeria
Vasco N. G. J. Soares: Instituto de Telecomunicações, 6201-001 Covilhã, Portugal

Future Internet, 2020, vol. 12, issue 11, 1-18

Abstract: The probabilistic Delay Tolerant Network (DTN) routing has been adjusted for vehicular network (VANET) routing through numerous works exploiting the historic routing profile of nodes to forward bundles through better Store-Carry-and-Forward (SCF) relay nodes. In this paper, we propose a new hybrid swarm-inspired probabilistic Vehicular DTN (VDTN) router to optimize the next-SCF vehicle selection using the combination of two bio-metaheuristic techniques called the Firefly Algorithm (FA) and the Glowworm Swarm Optimization (GSO). The FA-based strategy exploits the stochastic intelligence of fireflies in moving toward better individuals, while the GSO-based strategy mimics the movement of glowworm towards better area for displacing and food foraging. Both FA and GSO are executed simultaneously on each node to track better SCF vehicles towards each bundle’s destination. A geography-based recovery method is performed in case no better SCF vehicles are found using the hybrid FA–GSO approach. The proposed FA–GSO VDTN scheme is compared to ProPHET and GeoSpray routers. The simulation results indicated optimized bundles flooding levels and higher profitability of combined delivery delay and delivery probability.

Keywords: VDTNs; next-SCF vehicle selection; ProPHET; probabilistic DTN routing; Glowworm Swarm Optimization; Firefly Algorithm; swarm-based approaches (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2020
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