Abstract
The traffic forecast system is critical in intelligent transportation system. Vehicular Ad-hoc Networks will play a significant role in future intelligent transportation system (VANET). On the highways, they give perfect service to the drivers. For traffic control systems, information systems for drivers and passengers, such as speed, journey time, congestion, emergency services, weather alerts, and many more services, pattern clarity and traffic forecast are critical. Problematic nonlinear pattern complicates these systems. This study offers a Cloud Based Random Forest Algorithm to prevent such issues (CRFA). For road facilities, the Random Forest approach is used to expect the next condition of traffic based on traffic changing in brief intervals of time. The suggested approach employs Random Forest on VANET to evaluate route optimization to get a congestion free road, accident detection, and prevention, as well as providing various services to drivers and passengers while maintaining QOS. Because it is based on the cloud and the Global Positioning System, even in foggy or misty conditions, each vehicle will know exactly where it is going, and if a target approaches another vehicle, a flash of warning will appear on the screen with a loud beep sound, resulting in the automatic reduction of speed to maintain the speed and distance between the vehicles.
Similar content being viewed by others
References
Hartenstein, H., & Laberteaux, K. (2010).VANET: Vehicular applications and inter-networking technologies. Wiley. ISBN: 978-0-470-74056-9.
Lu, R., Lin, X., & Shen, X. (2010). A social-based privacy- preserving packet forwarding protocol for vehicular delay tolerant networks, SPRING. In Proceedings IEEE INFOCOM. https://doi.org/10.1109/INFCOM.2010.5462161
Liu, K., & Lee, S. C. V., (2010). RSU-based real-time data access in dynamic vehicular networks. In Proceeding of 13th international IEEE conference on intelligent transportation systems (ITSC) (pp. 1051–1056). https://doi.org/10.1109/ITSC.2010.5625189
Cunha, F., Villas, L., Boukerche, A., Maia, G., Viana, A., Mini, A. F. R., & Loureiroa, A. A. F. (2016). Data communication in VANETs: Protocols, applications and challenges. Elsevier Ad Hoc Networks. https://doi.org/10.1016/j.adhoc.2016.02.017
Velte, T,A., Velte, T, J., & Elsenpeter,R.(2009). Cloud computing a practical approach. TATA McGRAW-HILL. ISBN: 978-0-07-162695-8.
Randles, M., Lamb, D., & Taleb-Bendiab, A.(2010). A Comparative study into distributed load balancing algorithms for cloud computing. In IEEE 24th international conference on advanced information networking and applications workshops (pp. 551–556). https://doi.org/10.1109/WAINA.2010.85
Bitam, S., Mellouk, A., & Zeadally, S. (2015). Vanet-cloud: A generic cloud computing model for vehicular AD HOC networks. IEEE Wireless Communications. https://doi.org/10.1109/MWC.2015.7054724
Domanal, S. G., & Reddy, G. R. M. (2013). Load balancing in cloud computing modified throttled algorithm. In IEEE international conference on cloud computing in emerging markets (CCEM.). https://doi.org/10.1109/CCEM.2013.6684434
Nuaimi, K. A., Mohamed, N., Nuaimi, M. A. & Jaroodi, J. A. (2012). A survey of load balancing in cloud computing: Challenges and algorithms. In IEEE 2nd symposium on network cloud computing and applications (pp. 137–142). https://doi.org/10.1109/NCCA.2012.29
Shoja, H., Nahid, H., & Azizi, R. (2014). A comparative survey on load balancing algorithms in cloud computing. In IEEE 5th international conference on computing, communication and networking technologies (ICCCNT). https://doi.org/10.1109/ICCCNT.2014.6963138
Afzal, S., & Kavitha, G. (2019). Load balancing in cloud computing-a hierarchical taxonomical classification. Springer Journal of Cloud Computing, Advances, System and Applications.https://doi.org/10.1186/s13677-019-0146-7
Shetty, S. M., & Shetty, S. (2019). Analysis of load balancing in cloud data centers. Springer Journal of Ambient Intelligence and Humanized Computing.https://doi.org/10.1007/s12652-018-1106-7
Rastogi,G., & Sushil, R. (2015). Analytical literature survey on existing load balancing schemes in cloud computing. IEEE international conference on green computing and internet of things (ICGCIOT). https://doi.org/10.1109/ICGCIoT.2015.7380705
Radojevic, B., & Zagar, M. (2011). Analysis of issues with load balancing algorithms in cloud environment. In Proceedings IEEE 34th international convention on MLPRO. https://ieeexplore.ieee.org/document/5967092
Van, P.T., & Nguyen, D.V.,(2010). Location-aware and load-balanced data delivery at road-side units in vehicular Ad hoc networks. In IEEE international symposium on consumer electronics (ISCE 2010) (pp. 1–5). https://doi.org/10.1109/ISCE.2010.5522761
Ramezani, F., Lu, L., & Hussain, F. K. (2013). Task-based system load balancing in cloud computing using particle swarm optimization. Springer International Journal of Parallel Programming 739–754.
Dogru, N., & Subasi, A. (2018). Traffic accident detection using random forest classifier. In IEEE 15th learning and technology conference (L&T) (pp. 40–45). https://doi.org/10.1109/LT.2018.8368509
Shaw, S, B., & Singh, A. K. (2014). A survey on cloud computing. In IEEE International conference on green computing communication and electrical engineering (ICGCCEE). https://ieeexplore.ieee.org/document/6921423
Hussain, R., Son, J., Eun, H., Kim, S., & Oh, H., (2012). Rethinking vehicular communications: Merging VANET with cloud computing. In IEEE 4th international conference on cloud computing technology and science (pp. 606–609). https://doi.org/10.1109/CloudCom.2012.6427481
Wang, M., Liang, H., Zhang, R., Deng, R., & Shen, X. (2014). Mobility-aware coordinated charging for electric vehicles in VANET-enhanced smart grid. IEEE Journal on Selected Areas in Communications., 32(7), 1344–1360. https://doi.org/10.1109/JSAC.2014.2332078
Wong, W. J. (1988). Broadcast delivery. Proceedings of the IEEE, 76(12), 1566–1577. https://doi.org/10.1109/5.16350
Su, J. C., & Tassiulas, L. (1997). Broadcast scheduling for information distribution. In Proceedings of IEEE INFOCOM’97 (pp. 107–117). https://doi.org/10.1109/INFCOM.1997.635120
Awad, A. I., El-Hefnawy, N. A., & Abdel_kader, H. M. (2015). Enhanced particle swarm optimization for task scheduling in cloud computing environments. In Elsevier international conference on communication, management and information technology (ICCMIT) (pp. 920–929). https://doi.org/10.1016/j.procs.2015.09.064
Buyya, R. R., & Ranjan, R. (2010). Intercloud: Utility-oriented federation of cloud computing environments for scaling of application services. In Springer international conference on algorithms and architectures for parallel processing (ICAPP) (pp. 13–31).
Barria, J. A., & Thajchayapong, S. (2011). Detection and Classification of Traffic Anomalies Using Microscopic Traffic Variables. IEEE Transactions on Intelligent Transportation Systems, 12(3), 695–704. https://doi.org/10.1109/TITS.2011.2157689
Ahmed, E., Yaqoob, I., Khan, I., & Vasilakos, A. V. (2017). The role of big data analytics in Internet of Things. Elsevier Computer Networks., 129(2), 459–471. https://doi.org/10.1016/j.comnet.2017.06.013
Zhao, J., & Cao, G. (2008). VADD: vehicle assisted data delivery in vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 57(3), 1910–1922. https://doi.org/10.1109/TVT.2007.901869
Shirani, R., Hendessi, R., Montazeri, A. M., & Zefreh, S. M. (2008). Absolute priority for a vehicle in VANET. In Springer advances in computer science and engineering (pp. 955–959).
Jena, R. K. (2015). Multi objective task scheduling in cloud environment using nested PSO framework. In Elsevier 3rd international conference on recent trends in computing (ICRTC) (pp. 1219–1227). https://doi.org/10.1016/j.procs.2015.07.419
Jhang, F., & Liao, W. (2008). On cooperative and opportunistic channel access for vehicle to roadside (V2R) communications. IEEE Global Telecommunications Conference. https://doi.org/10.1109/GLOCOM.2008.ECP.966
Yasser, A., Zorkany, M., & Kader, N. A. (2017). VANET routing protocol for V2V implementation: A suitable solution for developing countries. Taylor & Francis Cognet Enginering Journal, 4(1), 1. https://doi.org/10.1080/23311916.2017.1362802
Mitropoulos, G., Karanasiou, I. S., Hinsberger, A., Aguado-Agelet, F., & Wieker, H. (2010). Wireless local danger warning: Cooperative foresighted driving using intervehicle communication. IEEE Transactions on Intelligent Transportation Systems, 11(3), 539–553. https://doi.org/10.1109/TITS.2009.2034839
Kothai, G., Poovammal, E., Gaurav, D., Kadiyala, R., Ashutosh, S., Mohammed, A. Zain., Gurjot S.G. & Mehedi, M.(2021). A New hybrid deep learning algorithm for prediction of wide traffic congestion in smart cities. In Hindawi wireless communication and mobile computing AI-Based Federated Learning for 6G Mobile Netwoks. https://doi.org/10.1155/2021/5583874
Muhammad, S., Jun, L., & Wensong, W. (2021). Efficient privacy-preservation scheme for securing urban P2P VANET networks. Egyptian Informatics Journal Science Direct, 22(3), 317–328. https://doi.org/10.1016/j.eij.2020.12.002
Drira, W., Ahn, K. H., Rakha, H., & Filali, F. (2016). Development and testing of a 3G/LTE adaptive data collection system in vehicular networks. IEEE Transactions on Intelligent Transportation Systems, 17(1), 240–249. https://doi.org/10.1109/TITS.2015.2464792
Tyagi, P., & Dembla, D. (2017). Performance analysis and implementation of proposed mechanism for detection and prevention of security attacks in routing protocols of vehicular ad-hoc network (VANET). Egyptian Informatics Journal, 18(2), 133–139. https://doi.org/10.1016/j.eij.2016.11.003
Tashakkori, H., & Khorsandi, S. (2012). Load balanced VANET routing in city environments. In IEEE 75th vehicular technology conference (VTC Spring). https://doi.org/10.1109/VETECS.2012.6240114
Dogru, N., & Subasi, A. (2018). Traffic accident detection using random forest classifier. In IEEE 15th learning and technology conference. https://doi.org/10.1109/LT.2018.8368509
Warsaw, Bangui P.H., Ge, M., & Buhnova B. (2021). A hybrid data-driven model for intrusion detection in VANET. In 12th international conference on ambient systems, networks and technologies (ANT) science direct Elsevier (pp. 516–523). https://doi.org/10.1016/j.procs.2021.03.065
Grover, J., Laxmi, V., & Gaur, M. S. (2011). Misbehaviour detection based on ensemble learning in VANET. In Springer international conference on advanced computing, network and security (pp. 602–611).
Bitam, S., Mellouk, A., & Zeadally, S. (2015). Vanet-cloud: A generic cloud computing model for vehicular ad hoc networks. IEEE Wireless Communications., 22(1), 96–102. https://doi.org/10.1109/MWC.2015.7054724
Babua, L. D. D., & Krishna, P. V. (2013). Honey bee behavior inspired load balancing of tasks in cloud computing environments. Elsevier Applied Soft Computing, 13(5), 2292–2303. https://doi.org/10.1016/j.asoc.2013.01.025
Sharma, S., & Kaula, A. (2018). A survey on Intrusion Detection Systems and Honeypot based proactive security mechanisms in VANETs and VANET Cloud. Elsevier Vehicular Communications, 1, 138–164. https://doi.org/10.1016/j.vehcom.2018.04.005
Grover, J., Jain, A., Singhal, S., & Yadav, A. (2018). Real-time VANET applications using fog computing. In Springer proceedings of first international conference on smart system, innovations and computing (pp. 683–691).
Abdelatif, S., Derdour, M., Ghoualmi-Zine, N., & Marzak, B. (2020). VANET: A novel service for predicting and disseminating vehicle traffic information. International journal of communication system. https://doi.org/10.1002/dac.4288
Sheikh, M., Liang, J., & Wang, W. (2020). Security and privacy in vehicular ad hoc network and vehicle cloud computing: A survey. Hindwai Wireless Communications and Mobile Computing. https://doi.org/10.1155/2020/5129620
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
Singh, S., Verma, S.K. Congestion and Accident Alerts Using Cloud Load Balancing & Random Forest in VANET. Wireless Pers Commun 128, 43–65 (2023). https://doi.org/10.1007/s11277-022-09473-9
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-022-09473-9