Skip to main content
SpringerLink
Log in

Fire Controlling Under Uncertainty in Urban Region Using Smart Vehicular Ad hoc Network

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Every year thousands of urban and industrial fires occur, which leads to the destruction of infrastructure, buildings, and loss of lives. One of the reasons behind this is the delayed transmission of information to the fire station and the nearer hospitals for ambulance service as the transmission of information is dependent on observer at the location where the fire is caught and cellular network. This paper proposed an automated routing protocol for the urban vehicular ad-hoc network to send the information from the location where the fire is caught to the nearest fire stations and hospitals with optimum service time. This transmission of information involves Road Side Unit (RSU) at the junction and the vehicles present in the transmission path. Selection of route to transmit faulty vehicle information from the RSU to the required faulty vehicle is based on a parameter called path value. The computation of path value is done by the attributes such as expected End To End (E2E) delay, the shortest distance to destination, the density of vehicle between the junctions, and attenuation. From the current junction, the selection of the next junction is based on minimum path value. The proposed routing protocol considers the performance parameters such as E2E delay, total service time (TST), number of network fragments or network gaps, number of hops, and attenuation for the propagation path for the evaluation of the proposed methodology. The proposed routing algorithm is implemented through OmNet++ and SUMO. Results obtained for the proposed routing protocol is compared with three existing VANET protocols (GSR, A-STAR, and ARP) in terms of End To End delay, number of hops, number of vehicular gaps, and Total Service Time (TST).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Ghori, M.R., Zamli, K.Z., Quosthoni, N., Hisyam, M., & Montaser, M. (2018). Vehicular ad-hoc network (vanet). In 2018 IEEE international conference on innovative research and development (ICIRD) (pp. 1–6) IEEE.

  2. Zeadally, S., Hunt, R., Chen, Y. S., Irwin, A., & Hassan, A. (2012). Vehicular ad hoc networks (vanets): Status, results, and challenges. Telecommunication Systems, 50(4), 217–241.

    Article  Google Scholar 

  3. Harri, J., Filali, F., & Bonnet, C. (2009). Mobility models for vehicular ad hoc networks: A survey and taxonomy. IEEE Communications Surveys & Tutorials, 11(4), 19–41.

    Article  Google Scholar 

  4. 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.

    Article  Google Scholar 

  5. Yousefi, S., Mousavi, M.S., & Fathy, M. (2006). Vehicular ad hoc networks (vanets): Challenges and perspectives. In 2006 6th international conference on ITS telecommunications (pp. 761–766) IEEE.

  6. Zhou, J., Dong, X., Cao, Z., & Vasilakos, A. V. (2015). Secure and privacy preserving protocol for cloud-based vehicular dtns. IEEE Transactions on Information Forensics and Security, 10(6), 1299–1314.

    Article  Google Scholar 

  7. Jiau, M. K., Huang, S. C., Hwang, J. N., & Vasilakos, A. V. (2015). Multimedia services in cloud-based vehicular networks. IEEE Intelligent Transportation Systems Magazine, 7(3), 62–79.

    Article  Google Scholar 

  8. Abdelhamid, S., Hassanein, H., & Takahara, G. (2015). Vehicle as a resource (vaar). IEEE Network, 29(1), 12–17.

    Article  Google Scholar 

  9. Bhoi, S. K., & Khilar, P. M. (2013). Vehicular communication: A survey. IET. Networks, 3(3), 204–217.

    Google Scholar 

  10. Shit, R. C., Sharma, S., Puthal, D., & Zomaya, A. Y. (2018). Location of things (LoT): A review and taxonomy of sensors localization in IOT infrastructure. IEEE Communications Surveys & Tutorials, 20(3), 2028–2061.

    Article  Google Scholar 

  11. Kumar, V., Mishra, S., Chand, N., et al. (2013). Applications of vanets: Present & future. Communications and Network, 5(01), 12.

    Article  Google Scholar 

  12. Senapati, B.R., Swain, R.R., & Khilar, P.M. (2020). Environmental monitoring under uncertainty using smart vehicular ad hoc network. In Smart intelligent computing and applications (pp. 229–238) Springer.

  13. Lyu, F., Zhu, H., Zhou, H., Qian, L., Xu, W., Li, M., et al. (2018). MoMAC: Mobility-aware and collision-avoidance MAC for safety applications in vanets. IEEE Transactions on Vehicular Technology, 67(11), 10590–10602.

    Article  Google Scholar 

  14. Oliveira, R., Montez, C., Boukerche, A., & Wangham, M. S. (2017). Reliable data dissemination protocol for vanet traffic safety applications. Ad Hoc Networks, 63, 30–44.

    Article  Google Scholar 

  15. Bhoi, S. K., Puthal, D., Khilar, P. M., Rodrigues, J. J., Panda, S. K., & Yang, L. T. (2018). Adaptive routing protocol for urban vehicular networks to support sellers and buyers on wheels. Computer Networks, 142, 168–178.

    Article  Google Scholar 

  16. Senapati, B. R., & Khilar, P. M. (2020). Automatic parking service through VANET: A convenience application. In Progress in Computing, Analytics and Networking (pp. 151–159). Singapore: Springer.

    Chapter  Google Scholar 

  17. Senapati, B.R., Khilar, P.M., Sabat, N.K. (2019). An automated toll gate system using vanet. In: 2019 IEEE 1st international conference on energy, systems and information processing (ICESIP) (pp. 1–5) IEEE.

  18. Popoola, S.I., Popoola, O.A., Oluwaranti, A.I., Atayero, A.A., Badejo, J.A., & Misra, S. (2017). A cloud-based intelligent toll collection system for smart cities. In International conference on next generation computing technologies (pp. 653–663) Springer.

  19. Panayappan, R., Trivedi, J.M., Studer, A., & Perrig, A. (2007). Vanet-based approach for parking space availability. In Proceedings of the fourth ACM international workshop on Vehicular ad hoc networks (pp. 75–76).

  20. Safi, Q. G. K., Luo, S., Pan, L., Liu, W., & Yan, G. (2018). Secure authentication framework for cloud-based toll payment message dissemination over ubiquitous vanets. Pervasive and Mobile Computing, 48, 43–58.

    Article  Google Scholar 

  21. Senapati, B.R., & Khilar, P.M. (2020) Optimization of performance parameter for vehicular ad-hoc network (vanet) using swarm intelligence. In Nature Inspired Computing for Data Science (pp. 83–107) Springer.

  22. Sichitiu, M. L., & Kihl, M. (2008). Inter-vehicle communication systems: A survey. IEEE Communications Surveys & Tutorials, 10(2), 88–105.

    Article  Google Scholar 

  23. Schoch, E., Kargl, F., Weber, M., & Leinmuller, T. (2008). Communication patterns in vanets. IEEE Communications Magazine, 46(11), 119–125.

    Article  Google Scholar 

  24. Hafeez, K. A., Zhao, L., Ma, B., & Mark, J. W. (2013). Performance analysis and enhancement of the DSRC for vanet’s safety applications. IEEE Transactions on Vehicular Technology, 62(7), 3069–3083.

    Article  Google Scholar 

  25. Kenney, J. B. (2011). Dedicated short-range communications (DSRC) standards in the united states. Proceedings of the IEEE, 99(7), 1162–1182.

    Article  Google Scholar 

  26. Ho, K.Y., Kang, P.C., Hsu, C.H., & Lin, C.H. (2010). Implementation of wave/DSRC devices for vehicular communications. In 2010 international symposium on computer communication control and automation (3CA) (Vol. 2, pp. 522–525) IEEE.

  27. Deng, D. J., Chen, H. C., Chao, H. C., & Huang, Y. M. (2011). A collision alleviation scheme for IEEE 802.11 p vanets. Wireless Personal Communications, 56(3), 371–383.

    Article  Google Scholar 

  28. Crow, B. P., Widjaja, I., Kim, J. G., & Sakai, P. T. (1997). IEEE 802.11 wireless local area networks. IEEE Communications magazine, 35(9), 116–126.

    Article  Google Scholar 

  29. Milojevic, M., & Rakocevic, V. (2014). Distributed road traffic congestion quantification using cooperative vanets. In 2014 13th annual Mediterranean ad hoc networking workshop (MED-HOC-NET) (pp. 203–210) IEEE.

  30. Cherkaoui, B., Beni-Hssane, A., El Fissaoui, M., & Erritali, M. (2019). Road state novel detection approach in vanet networks based on hadoop ecosystem. Wireless Personal Communications, 107(4), 1643–1660.

    Article  Google Scholar 

  31. Zhang, L., Gao, D., Zhao, W., & Chao, H. C. (2013). A multilevel information fusion approach for road congestion detection in vanets. Mathematical and Computer Modelling, 58(5–6), 1206–1221.

    Article  Google Scholar 

  32. Ali, F., Shaikh, F. K., Ansari, A. Q., Mahoto, N. A., & Felemban, E. (2015). Comparative analysis of vanet routing protocols: On road side unit placement strategies. Wireless Personal Communications, 85(2), 393–406.

    Article  Google Scholar 

  33. Truong, N.B., Lee, G.M., & Ghamri-Doudane, Y. (2015). Software defined networking-based vehicular adhoc network with fog computing. In 2015 IFIP/IEEE international symposium on integrated network management (IM) (pp. 1202–1207) IEEE.

  34. Sabat, N.K., Pati, U.C., Senapati, B.R., Das, S.K. (2019). An IOT concept for region based human detection using PIR sensors and FRED cloud. In 2019 IEEE 1st international conference on energy, systems and information processing (ICESIP) (pp. 1–4) IEEE

  35. Swain, R. R., Khilar, P. M., & Bhoi, S. K. (2020). Underlying and persistence fault diagnosis in wireless sensor networks using majority neighbors co-ordination approach. Wireless Personal Communications, 111(2), 763–798.

    Article  Google Scholar 

  36. Swain, R. R., Khilar, P. M., & Bhoi, S. K. (2018). Heterogeneous fault diagnosis for wireless sensor networks. Ad Hoc Networks, 69, 15–37.

    Article  Google Scholar 

  37. Swain, R. R., & Khilar, P. M. (2017). Composite fault diagnosis in wireless sensor networks using neural networks. Wireless Personal Communications, 95(3), 2507–2548.

    Article  Google Scholar 

  38. Lim, K., Tuladhar, K.M., & Kim, H. (2019). Detecting location spoofing using ADAS sensors in vanets. In 2019 16th IEEE annual consumer communications & networking conference (CCNC) (pp. 1–4) IEEE.

  39. Liu, C., Chigan, C., & Gao, C. (2013). Compressive sensing based data collection in vanets. In: 2013 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1756–1761) IEEE.

  40. Li, F., & Wang, Y. (2007). Routing in vehicular ad hoc networks: A survey. IEEE Vehicular Technology Magazine, 2(2), 12–22.

    Article  Google Scholar 

  41. Nagaraj, U., Kharat, D. M., & Dhamal, P. (2011). Study of various routing protocols in vanet. IJCST, 2(4), 45–52.

    Google Scholar 

  42. Jaiswal, R. K., & Jaidhar, C. (2018). A performance evaluation of location prediction position-based routing using real GPS traces for vanet. Wireless Personal Communications, 102(1), 275–292.

    Article  Google Scholar 

  43. Kumar, S., & Verma, A. K. (2015). Position based routing protocols in vanet: A survey. Wireless Personal Communications, 83(4), 2747–2772.

    Article  Google Scholar 

  44. Lochert, C., Hartenstein, H., Tian, J., Fussler, H., Hermann, D., & Mauve, M. (2003). A routing strategy for vehicular ad hoc networks in city environments. In Proceedings of the IEEE intelligent vehicles symposium, 2003 (pp. 156–161) IEEE.

  45. Seet, B.C., Liu, G., Lee, B.S., Foh, C.H., Wong, K.J., & Lee, K.K. (2004). A-star: A mobile ad hoc routing strategy for metropolis vehicular communications. In International conference on research in networking (pp. 989–999) Springer.

  46. Gupta, V., Dharmaraja, S., & Arunachalam, V. (2015). Stochastic modeling for delay analysis of a VoIP network. Annals of Operations Research, 233(1), 171–180.

    Article  MathSciNet  Google Scholar 

  47. https://www.dataloggerinc.com

Download references

Author information

Author notes

  1. Rakesh Ranjan Swain

    Present address: School of Computer Science, National Institute of Science and Technology, Berhampur, 761008, India

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, 769008, India

    Biswa Ranjan Senapati, Pabitra Mohan Khilar & Rakesh Ranjan Swain

Authors
  1. Biswa Ranjan Senapati
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pabitra Mohan Khilar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rakesh Ranjan Swain
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Biswa Ranjan Senapati.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Senapati, B.R., Khilar, P.M. & Swain, R.R. Fire Controlling Under Uncertainty in Urban Region Using Smart Vehicular Ad hoc Network. Wireless Pers Commun 116, 2049–2069 (2021). https://doi.org/10.1007/s11277-020-07779-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-020-07779-0

Keywords

Search

Navigation