Abstract
Due to the rapid growth in wireless communications, vehicular ad-hoc networks (VANETs) face many challenges over wireless communication networks. Nowadays VANETs have become a major research and they have incredible resources to improve road traffic efficiency, safety, convenience and comfort to both drivers and passengers etc. Congestion occurs when the vehicles are in the dense part while the network node is carrying more data than it can handle. The proposed DBDC: density based dynamic clustering devices determine node density of the precise location in a lane and provide a proactive solution for congestion. To trigger the congestion control process in the cluster, we use average vehicle density threshold which is calculated using trained dataset. If the node density is greater than the threshold value, the dynamic clustering process is triggered. Our simulation result indicates that the overall performance of our scheme is better than multi agent dynamic clustering and vehicular weighted clustering algorithm in terms of average cluster number, cluster head duration and average cluster member duration.
Similar content being viewed by others
References
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, 584–616.
Zeadally, S., Hunt, R., Chen, Y.-S., Irwin, A., & Hassan, A. (2012). Vehicular ad hoc networks (VANETS): Status, results, and challenges. Telecommunication Systems, 50, 217–241.
Stanica, R., Chaput, E., & Beylot, A. (2011). Local density estimation for contention window adaptation in vehicular networks. In IEEE 22nd international symposium on personal indoor and mobile radio communications (PIMRC), Sept. 2011 (pp. 730–734).
Sanguesa, J. A., Fogue, M., Garrido, P., Martinez, F. J., Cano, J.-C., Calafate, C. T., et al. (2013). An infrastructureless approach to estimate vehicular density in urban environments. Sensors, 13, 2399–2406.
Dimitrakopoulos, G., & Demestichas, P. (2010). Intelligent transportation systems. Vehicular Technology Magazine, IEEE, 5(1), 77–84.
Barrachina, J., Garrido, P., Fogue, M., Martinez, F. J., Cano, J.-C., Calafate, C. T., et al. (2013). Road side unit deployment: A density-based approach. IEEE Intelligent Transportation Systems Magazine, 5(3), 30–39.
Kumar, V., Mishra, S., & Chand, N. (2013). Applications of VANETs: Present and future. Communications and Network, 5, 12–15.
Yair, A., & Segal, M. (2011). Near-optimal, reliable and self-organizing hierarchical topology in VANET. In: Eighth ACM international workshop on vehicular internetworking (pp. 79–80).
Song, T., Xia, W., Song, T., & Shen, L. (2010). A cluster-based directional routing protocol in VANET. In 12th IEEE international conference on communication technology (ICCT) (pp. 1172–1175).
Wiegel, B., Gunter, Y., & Grossmann, H. (2007). Cross-layer design for packet routing in vehicular ad hoc networks. In IEEE 66th vehicular technology conference VTC Fall (pp. 2169–2173).
Zhang, Z., Boukerche, A., & Pazzi, R. (2011). A novel multi-hop clustering scheme for vehicular ad-hoc networks. In Proceedings of the 9th ACM international symposium on mobility management and wireless access (pp. 19–26).
Su, H., & Zhang, X. (2007). Clustering-based multichannel MAC protocols for QoS provisionings over vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 56(6), 3309–3323.
Daeinabi, A., Pour Rahbar, A. G., & Khademzadeh, A. (2011). VWCA: An efficient clustering algorithm in vehicular ad hoc networks. Journal of Network and Computer Applications, 34(1), 207–222.
Wolny, G. (2008). Modified DMAC clustering algorithm for VANETs. In Systems and networks communications, ICSNC (pp. 268–273).
Hassanabadi, B., Shea, C., Zhang, L., & Valaee, S. (2014). Clustering in vehicular ad hoc networks using affinity propagation. Ad Hoc Networks, 13, 535–548.
Souza, E., Nikolaidis, I., & Gburzynski, P. (2010). A new aggregate local mobility ALM; Clustering algorithm for VANETs. In IEEE International conference on communications (ICC) (pp. 1–5).
Rawashdeh, Z. Y., & Mahmud, S. (2012). A novel algorithm to form stable clusters in vehicular ad hoc networks on highways. In EURASIP journal on wireless communications and networking (p. 15).
Wang, Z., Liu, L., Zhou, M., & Ansari, N. (2008). A position-based clustering technique for ad hoc intervehicle communication. In IEEE transactions on systems, man, and cybernetics, part C: applications and reviews.
Basagni, S. (1999). Distributed clustering for ad hoc networks. In Proceedings of the fourth international symposium on parallel architectures, algorithms, and networks (I-SPAN’99), Perth/Fremantle, Australia (pp. 310–315).
Basu, P., Khan, N., & Little, T. (2001). A mobility based metric for clustering in mobile ad hoc networks. In Proceedings of distributed computing systems workshop, Vol. 2001, Phoenix/Mesa, Arizona (pp. 413–418).
McDonald, A., & Znati, T. (1999). A mobility-based framework for adaptive clustering in wireless adhoc networks. IEEE Journal on Selected Areas in Communications, 17(8), 1466–1487.
Kuklinski, S., & Wolny, G. (2009). Density based clustering algorithm for VANETs. International Journal of Internet Protocol Technology, 4, 149–157.
Bakhoya, M., Gaber, J., & Lorenz, P. (2011). An adaptive approach for information dissemination in vehicular ad hoc networks. Journal of Network and Computer Applications, 34, 1971–1978.
Darwish, T., & Bakar, K. A. (2015). Traffic density estimation in vehicular ad hoc networks: A review. Pervasive Computing Research Group, Faculty of Computing, Universiti Teknologi Malaysia (UTM), 81310.
Kakkasageri, M. S., & Manvi, S. S. (2012). Multiagent driven dynamic clustering of vehicles in VANETs. Journal of Network and Computer Applications, 35, 1771–1780.
Daeinabi, A., Rahbar, A. G. P., & Khademzadeh, A. (2011). VWCA: An efficient clustering algorithm in vehicular ad hoc networks. Journal of Network and Computer Applications, 34, 207–222.
Liu, X., Fan, Z., & Shi, L. (2007). Securing vehicular ad hoc networks. In Second conference on international pervasive computing and applications, Amsterdam, The Netherlands (pp. 424–432).
Beckmann, M., McGuire, C. B., & Winsten, C. B. (1955). Studies in the economics of transportation. Number RM-1488. Yale University Press.
Bertini, R. L. (2003). Toward the systematic diagnosis of freeway bottleneck activation. In Proceedings of the IEEE 6th annual conference on intelligent transportation systems, Shanghai, China.
Bovy, P. L., & Thijs, R. (Eds.). (2000). Estimators of travel time for road networks—New developments, evaluation results, and applications. Delft: Delft University Press.
Brilon, W. (2000). Traffic flow analysis beyond traditional methods. In Transportation research circular EC018: 4th international symposium on highway capacity (pp. 26–41). Transportation Research Board and National Research Council.
Buckley, D. J., & Yagar, S. (1974). Capacity funnels near onramps. In D. J. Buckley (Ed.), Proceedings of the 6th international symposium on transportation and traffic theory, London, United Kingdom (pp.105–123).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Regin, R., Menakadevi, T. Dynamic Clustering Mechanism to Avoid Congestion Control in Vehicular Ad Hoc Networks Based on Node Density. Wireless Pers Commun 107, 1911–1931 (2019). https://doi.org/10.1007/s11277-019-06366-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-019-06366-2