A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach
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 s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Future Internet |
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| Online Access: | https://www.mdpi.com/1999-5903/12/11/192 |
| _version_ | 1827702693142986752 |
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| author | Youcef Azzoug Abdelmadjid Boukra Vasco N. G. J. Soares |
| author_facet | Youcef Azzoug Abdelmadjid Boukra Vasco N. G. J. Soares |
| author_sort | Youcef Azzoug |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T15:02:08Z |
| format | Article |
| id | doaj.art-6c28c767f3414fdc93ef075f616feb87 |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-10T15:02:08Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-6c28c767f3414fdc93ef075f616feb872023-11-20T20:05:52ZengMDPI AGFuture Internet1999-59032020-11-01121119210.3390/fi12110192A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based ApproachYoucef Azzoug0Abdelmadjid Boukra1Vasco N. G. J. Soares2Department of Informatics, University of Science and Technology Houari Boumediene, 16111 Algiers, AlgeriaDepartment of Informatics, University of Science and Technology Houari Boumediene, 16111 Algiers, AlgeriaInstituto de Telecomunicações, 6201-001 Covilhã, PortugalThe 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.https://www.mdpi.com/1999-5903/12/11/192VDTNsnext-SCF vehicle selectionProPHETprobabilistic DTN routingGlowworm Swarm OptimizationFirefly Algorithm |
| spellingShingle | Youcef Azzoug Abdelmadjid Boukra Vasco N. G. J. Soares A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach Future Internet VDTNs next-SCF vehicle selection ProPHET probabilistic DTN routing Glowworm Swarm Optimization Firefly Algorithm |
| title | A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach |
| title_full | A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach |
| title_fullStr | A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach |
| title_full_unstemmed | A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach |
| title_short | A Probabilistic VDTN Routing Scheme Based on Hybrid Swarm-Based Approach |
| title_sort | probabilistic vdtn routing scheme based on hybrid swarm based approach |
| topic | VDTNs next-SCF vehicle selection ProPHET probabilistic DTN routing Glowworm Swarm Optimization Firefly Algorithm |
| url | https://www.mdpi.com/1999-5903/12/11/192 |
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