Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Wireless Personal Communications
Erschienen in: Wireless Personal Communications 1/2021

27.08.2020

Optimal Multipath Routing for Video Transmission in VANETs

verfasst von: Shivaprasad More, Udaykumar Naik

Erschienen in: Wireless Personal Communications | Ausgabe 1/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The communication among the vehicles in Vehicular Ad Hoc Network (VANET) plays a major role in the improvement of safety in critical situations of road scenario. With the implementation of VANET, the transmission of videos to other vehicles is done in an improved way. A new algorithm, known as Moth Whale Optimization Algorithm (MWOA) is proposed in this paper to determine the optimal multipath for the transmission of the videos from one vehicle to other in the VANET network. The proposed algorithm is developed with the integration of Moth Search (MS) algorithm and Whale Optimization Algorithm (WOA). Initially, the VANET is simulated and the optimal selection of the multipath is done using adaptive geographic routing scheme based on the fitness measure. The performance of the proposed Moth Whale Optimization Algorithm is estimated with the metrics, such as Packet delivery Ratio (PDR), Packet end-to-end delay, and the throughput. The Moth-Whale Optimization Algorithm produces the minimum end-to-end delay of 4.4427, and maximum Packet delivery ratio and throughput of 96.5135 and 94.2429, respectively, which shows the superiority of the method in effective video transmission.
Vorheriger Artikel Asymmetric Coplanar Strip-Fed with Hilbert Curve Fractal Antenna for Multiband Operations
Nächster Artikel A Competent Ad-hoc Sensor Routing Protocol for Energy Efficiency in Mobile Wireless Sensor Networks

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Karagiannis, G., Altintas, O., Ekici, E., Heijenk, G., Jarupan, B., Lin, K., et al. (2011). Vehicular networking: A survey and tutorial on requirements, architectures, challenges, standards and solutions. IEEE Communications Surveys & Tutorials, 13(4), 584–616.CrossRef
2.
Kumar, D. A., & Bansal, M. (2017). A review on VANET security attacks and their countermeasure. In Proceedings of 4th international conference on signal processing, computing and control (ISPCC), Solan (pp. 580–585).
3.
Rakhshan, A., & Pishro-Nik, H. (2017). Improving Safety on Highways by Customizing Vehicular Ad Hoc Networks. IEEE Transactions on Wireless Communications, 16(3), 2026.CrossRef
4.
Lo, C. C., & Kuo, Y. H. (2017). Traffic-aware routing protocol with cooperative coverage-oriented information collection method for VANET. IET Communications, 11(3), 444–450.CrossRef
5.
Petruccelli, U., & Antonello, R. (2019). Assessment of the drivers number as a tool for improving efficiency of public transport services. Ingegneria Ferroviaria, 4(4), 295–315.
6.
Xie, H., Boukerche, A., & Loureiro, A. A. F. (2015). MERVS: a novel multi-channel error recovery video streaming protocol for vehicle ad-hoc networks. IEEE Transactions on Vehicular Technology, pp–14.
7.
Salkuyeh, M. A., & Abolhassani, B. (2016). An adaptive multipath geographic routing for video transmission in Urban VANETs. IEEE Transactions on Intelligent Transportation Systems, pp. 1–10.
8.
Dharani, P., Chakkaravarthy, S. S., Kamalanaban, M. G. E., Pravin, P. V., Patil, R., & Mahesh, C. (2015). An unidentified location-based routing protocol in VANET. Artificial Intelligence and Evolutionary Algorithms in Engineering Systems, 324, 415–421.CrossRef
9.
Gomathi, N., & Karlekar, N. P. (2019). Ontology and hybrid optimization based SVNN for privacy preserved medical data classification in cloud. International Journal on Artificial Intelligence Tools, 28(3), 1950009.CrossRef
10.
Arul, V. H., Sivakumar, V. G., Marimuthu, R., & Chakraborty, B. (2019). An approach for speech enhancement using deep convolutional neural network. Multimedia Research (MR), 2(1), 37–44.
11.
Mane, A. A., Waykar, B. S., & Narvekar, S. D. (2011). Multimedia resource library using video streaming. In Proceedings of the International Conference & Workshop on Emerging Trends in Technology (pp. 1378–1379).
12.
Zaidi, S., Bitam, S., & Mellouk, A. (2017). Enhanced user datagram protocol for video streaming in VANET. In Proceedings of IEEE international conference on communications (pp. 1–6). IEEE.
13.
Dua, A., Kumar, N., & Bawa, S. (2016). ReIDD: Reliability-aware intelligent data dissemination protocol for broadcast storm problem in vehicular ad hoc networks. Telecommunication System, 64(3), 439–458.CrossRef
14.
Gaikwad, D. S., & Zaveri, M. (2011). VANET Routing Protocols and Mobility Models: A Survey. Trends in Network and Communications, 197, 334–342.CrossRef
15.
Mchergui, A., Moulahi, T., Alaya, B., & Nasri, S. (2017). A survey and comparative study of QoS aware broadcasting techniques in VANET. Telecommunication Systems, 66(2), 253–281.CrossRef
16.
Chang, S.-W., & Lee, S.-S. (2016). A Routing Protocol for Urban Vehicular Multi-hop Data Delivery. Chinese Journal of Electronics, 25(2), 348–356.CrossRef
17.
Agrawal, S., Tyagi, N., Misra, A. K., Shukla, R. S., & Gupta, A. (2016). Position Based Seamless Connectivity for Vehicular Ad Hoc Networks. Proceedings of the National Academy of Sciences, India, Section A: Physical Sciences, 87(1), 73–81.MathSciNetCrossRef
18.
Singh, H. K., Raw, R. S., Kumar, S., Singh, A. K., & Soni, S. K. (2016). Analysis of Angle Based Opportunistic Routing Protocol for Vehicular Ad-Hoc Networks. In Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies.
19.
Kumar, N., & Dave, M. (2016). BIIR: A Beacon Information Independent VANET Routing Algorithm with Low Broadcast Overhead. Wireless Personal Communications, 87(3), 869–895.CrossRef
20.
Lee, S.-H., & Seok, S.-J. (2014). A Two-Tier Routing Algorithm Based on Geographical Zone in VANET. Frontier and Innovation in Future Computing and Communications, 301, 751–761.CrossRef
21.
Zaidi, S., Bitam, S., & Mellouk, A. (2016). Enhanced adaptive sub-packet forward error correction mechanism for video streaming in VANET. In 2016 IEEE Global Communications Conference (GLOBECOM) (pp. 1-6).
22.
Hu, Z., & Zhang, Q. (2018). A new approach for packet loss measurement of video streaming and its application. Multimedia Tools and Applications, 1–20.
23.
Immich, R., Cerqueira, E., & Curado, M. (2016). Shielding video streaming against packet losses over VANETs. Wireless Networks, 22(8), 2563–2577.CrossRef
24.
Smida, E. B., Fantar, S. G., & Youssef, H. (2017). Video streaming challenges over vehicular ad-hoc networks in smart cities. In Proceedings of International Conference on Smart, Monitored and Controlled Cities (pp. 12–16).
25.
Sullivan, G. J., Ohm, J.-R., Han, W.-J., & Wiegand, T. (2012). Overview of the high efficiency video coding (HEVC) standard. IEEE Transactions on Circuits and Systems for Video Technology, 22(12), 1649–1668.CrossRef
26.
Mirjalili, S., & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51–67.CrossRef
27.
Wang, G.-G. (2016). Moth search algorithm: a bio-inspired metaheuristic algorithm for global optimization problems.
28.
Sarubbi, J. F. M., Martins, F. V. C, & Silva, C. M. (2016). A genetic algorithm for deploying roadside units in vanets. In IEEE Congress on Evolutionary Computation (CEC).
29.
Arzil, S. A., Aghdam, M. H., & Jamali, M. A. J. (2010). Adaptive routing protocol for VANETs in city environments using real-time traffic information. In Proceedings on international conference on information, networking and automation (ICINA).
Metadaten
Titel
Optimal Multipath Routing for Video Transmission in VANETs
verfasst von
Shivaprasad More
Udaykumar Naik
Publikationsdatum
27.08.2020
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 1/2021
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07740-1

Weitere Artikel der Ausgabe 1/2021

Wireless Personal Communications 1/2021 Zur Ausgabe

OriginalPaper

Eagle Eye CBVR Based on Unique Key Frame Extraction and Deep Belief Neural Network

OriginalPaper

Energy Efficient Location Error Resilient Connectivity in Wireless Sensor Networks

OriginalPaper

VDCC Based Sinusoidal Oscillators Using All Grounded Capacitors: A Series of Realization

OriginalPaper

Exploring New Vista of Secured and Optimized Data Slicing for Big Data: An IOT Paradigm

OriginalPaper

Study on the Spatial Layout Features of Linpan in Western Sichuan with the Aid of GIS: A Case Study in Deyuan Town

OriginalPaper

Investigations of Free Space Optical Communications Under Real-World Atmospheric Conditions

Neuer Inhalt

    Bildnachweise