Abstract
Emergence of Wireless Sensor Networks provided the ability to connect, collect and disseminate information across various sensor nodes. Deploying this concept in the transportation domain evolved into the concept of Vehicular Ad-hoc Sensor Networks (VASNETs) or Vehicular Ad-hoc Networks (VANETs). VANETs turned out to act as a boon to enhance the safety and non-safety aspects of the transportation domain, giving way to the future of Intelligent Transport Systems. To generate cooperative awareness in the network, VANETs use beacons, which are small packets of information transmitted as BSMs (Basic Safety Messages). Beaconing was developed in the initial phases of development of VANETs and mainly suffers a trade-off between channel congestion and the level of accuracy of exchanged information. In this work, an adaptive speed based beaconing approach is proposed, the approach uses probability as a means to answer two key questions. First is whether to beacon or not and second is at what rate beaconing should be done to reduce channel congestion and increase the accuracy of information. The results are compared with an adaptive density-based approach and with normal static beaconing cases. Performance evaluation on Veins framework demonstrates that it gives better results as compared to both the other approaches. Further, the results concerning generated BSMs, received BSMs and total packet loss are compared. The simulation is modeled to make it as realistic as possible by introducing a vast heterogeneous network with random vehicle mobility trips.
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References
Singhal, A., Sarishma, Tomar, R.: Intelligent accident management system using IoT and cloud computing. In: Proceedings of 2016 2nd International Conference on Next Generation Computing Technology, NGCT 2016, pp. 89–92 (2017)
Chang, B.-J., Liang, Y.-H., Yang, H.-J.: Performance analysis with traffic accident for cooperative active safety driving in VANET/ITS. Wireless Pers. Commun. 74, 731–755 (2013). https://doi.org/10.1007/s11277-013-1318-2
Barrachina, J., et al.: Journal of network and computer applications VEACON: a vehicular accident ontology designed to improve safety on the roads. J. Netw. Comput. Appl. 35(6), 1891–1900 (2012)
Aadil, F., Rizwan, S., Akram, A.: Vehicular Ad Hoc Networks ( VANETs ), Past Present and Future : A survey, January 2013
Adeel, S., et al.: Adaptive beaconing approaches for vehicular ad hoc networks: a survey. IEEE Syst. J. 12, 1263–1277 (2016)
Van Eenennaam, M., Wolterink, W.K., Karagiannis, G., Heijenk, G.: Exploring the Solution Space of Beaconing in VANETs, pp. 1–8
Ghafoor, K.Z., Lloret, J., Bakar, K.A., et al.: Beaconing approaches in vehicular ad hoc networks: a survey. Wireless Pers. Commun. 73, 885–912 (2013). https://doi.org/10.1007/s11277-013-1222-9
Feng, Y., Du, Y., Ren, Z., Wang, Z., Liu, Y., Zhang, L.: Adaptive beacon rate adjusting mechanism for safety communication in cooperative IEEE 802.11 p-3g vehicle-infrastructure systems. In: 2010 16th Asia-Pacific Conference on Communications (APCC), pp. 441–446 (2010)
Panichpapiboon, S., Pattara-Atikom, W.: A review of information dissemination protocols for vehicular ad hoc networks. IEEE Commun. Surveys Tutor. 14(3), 784–798 (2011)
Jiang, D., Delgrossi, L.: IEEE 802.11 p: towards an international standard for wireless access in vehicular environments. In: VTC Spring 2008-IEEE Vehicular Technology Conference, pp. 2036–2040 (2008)
Qian, J., Jing, T., Huo, Y., Li, H., Ma, L., Lu, Y.: An adaptive beaconing scheme based on traffic environment parameters prediction in VANETs. In: Yang, Qing, Yu, Wei, Challal, Yacine (eds.) WASA 2016. LNCS, vol. 9798, pp. 524–535. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-42836-9_46
Thaina, C., Nakorn, K.N., Rojviboonchai, K.: A study of adaptive beacon transmission on Vehicular Ad-Hoc Networks. In: 2011 IEEE 13th International Conference on Communication Technology, pp. 597–602 (2011)
Djahel, S., Ghamri-Doudane, Y.: A robust congestion control scheme for fast and reliable dissemination of safety messages in VANETs. In: 2012 IEEE Wireless Communications and Networking Conference (WCNC), pp. 2264–2269 (2012)
Egea-Lopez, E., Pavon-Marino, P.: Distributed and fair beaconing rate adaptation for congestion control in vehicular networks. IEEE Trans. Mob. Comput. 15(12), 3028–3041 (2016)
Zrar, K., Abu Bakar, K., van Eenennaam, M., Khokhar, R.H., Gonzalez, A.J.: A fuzzy logic approach to beaconing for vehicular ad hoc networks. Telecommun. Syst. 52(1), 139–149 (2013)
Hassan, A., Ahmed, M.H., Rahman, M.A.: Adaptive beaconing system based on fuzzy logic approach for vehicular network. In: 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 2581–2585 (2013)
Sommer, C., Tonguz, O.K., Dressler, F., Systems, C.: Traffic Information Systems : Efficient Message Dissemination via Adaptive Beaconing
Kloiber, B., Härri, J., Strang, T.: Dice the TX power—Improving awareness quality in VANETs by random transmit power selection. In: 2012 IEEE vehicular networking conference (VNC), pp. 56–63 (2012)
Ben Mussa, S.A., Manaf, M., Ghafoor, K.Z.: Beaconing and transmission range adaptation approaches in vehicular ad hoc networks: trends & research challenges. In: 2014 International Conference on Computational Science and Technology (ICCST), pp. 1–6 (2014)
Torrent-Moreno, M., Mittag, J., Santi, P., Hartenstein, H.: Vehicle-to-vehicle communication: fair transmit power control for safety-critical information. IEEE Trans. Veh. Technol. 58(7), 3684–3703 (2009)
Li, F., Huang, C.: A mobility prediction based beacon rate adaptation scheme in VANETs. In: 2018 IEEE Symposium and Computing Communication, pp. 671–677 (2018)
Zidani, F., Semchedine, F., Ayaida, M.: Estimation of neighbors position privacy scheme with an adaptive beaconing approach for location privacy in VANETs ☆. Comput. Electr. Eng. 71(July), 359–371 (2018)
Schmidt, R.K., et al.: Exploration of adaptive beaconing for efficient intervehicle safety communication, pp. 14–19 (2010)
Barbieri, D., Thibault, I., Lister, D., Bazzi, A., Masini, B.M., Andrisano, O.: Adaptive beaconing for safety enhancement in vehicular networks. In: 2017 15th International Conference on ITS Telecommunications (ITST), pp. 1–6 (2017)
Haouari, N., Moussaoui, S., Senouci, S.: Application reliability analysis of density-aware congestion control in VANETs. In: 2018 IEEE International Conference on Communication, pp. 1–6 (2018)
Lyu, F., et al.: ABC: adaptive beacon control for rear-end collision avoidance in VANETs. In: 2018 15th Annual IEEE International Conference on Sensing, Communication Network, pp. 1–9 (2018)
Chaabouni, N., Hafid, A., Sahu, P.K.: A collision-based beacon rate adaptation scheme (CBA) for VANETs. In: 2013 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pp. 1–6 (2013)
Lee, K.C., Gerla, M.: Opportunistic Vehicular Routing
Bansal, G., Kenney, J.B., Rohrs, C.E.: LIMERIC: a linear adaptive message rate algorithm for DSRC congestion control. IEEE Trans. Veh. Technol. 62(9), 4182–4197 (2013)
Sommer, C., Eckhoff, D., Brummer, A., Buse, D., Hagenauer, F., Joerer, S., Segata, M.: Veins: the open source vehicular network simulation framework. In: Virdis, Antonio, Kirsche, Michael (eds.) Recent Advances in Network Simulation. EICC, pp. 215–252. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-12842-5_6
Krajzewicz, D., Hertkorn, G., Rössel, C., Wagner, P.: SUMO (Simulation of Urban MObility)-an open-source traffic simulation. In: Proceedings of the 4th middle East Symposium on Simulation and Modelling (MESM 2002), pp. 183–187 (2002)
Kaisser, F., Gransart, C., Kassab, M., Berbineau, M.: A framework to simulate VANET scenarios with SUMO. In: Opnetwork (2011)
Varga, A., Hornig, R.: An overview of the OMNeT++ simulation environment. In: Proceedings of the 1st International Conference on Simulation Tools and Techniques for Communications, Networks and Systems & Workshops, p. 60 (2008)
Varga, A.: OMNeT++. In: Wehrle, K., Günes, M., Gross, J.: Modeling and Tools for Network Simulation, pp. 35–59. Springer, Cham (2010). https://doi.org/10.1007/978-3-642-12331-3_3
Krajzewicz, D., Rossel, C.: Simulation of Urban MObility (SUMO). German Aerospace Centre (2007)
Behrisch, M., Bieker, L., Erdmann, J., Krajzewicz, D.: SUMO–simulation of urban mobility: an overview. In: Proceedings of SIMUL 2011, The Third International Conference on Advances in System Simulation (2011)
Tomar, R., Sastry, H.G., Prateek, M.: A V2I based approach to multicast in vehicular networks. Malaysian J. Comput. Sci. 93–107 (2020). ISSN 0127-9084. https://ejournal.um.edu.my/index.php/MJCS/article/view/27337. Accessed 11 Dec 2020
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Sarishma, Tomar, R., Kumar, S., Awasthi, M.K. (2021). To Beacon or Not?: Speed Based Probabilistic Adaptive Beaconing Approach for Vehicular Ad-Hoc Networks. In: Paiva, S., Lopes, S.I., Zitouni, R., Gupta, N., Lopes, S.F., Yonezawa, T. (eds) Science and Technologies for Smart Cities. SmartCity360° 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-030-76063-2_12
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