3 research outputs found

    Transmission power adaption scheme for improving IoV awareness exploiting: evaluation weighted matrix based on piggybacked information

    Get PDF
    This is an accepted manuscript of an article published by Elsevier in Computer Networks on 04/06/2018, available online: https://doi.org/10.1016/j.comnet.2018.03.019 The accepted version of the publication may differ from the final published version.© 2018 Elsevier B.V. As part of the new era the Internet of Things, an evolved form of Vehicle Ad-hoc Networks has recently emerged as the Internet of Vehicles (IoV). IoV has obtained a lot of attention among smart vehicle manufactures and illustrations due to its promising potential, but there are still some problems and challenges that need to be addressed. Transmission error occurs when an emergency message is disseminated to provide traffic awareness, and vehicles have to increase their channel transmission power to ensure further coverage and mitigate possible accidents. This might cause channel congestion and unnecessary power consumption due to an inaccurate transmission power setup. A promising solution could be achieved via periodically and predictively evaluating channel and GEO information that is transmitted over piggybacked beacons. Thus, in this paper we propose a Transmission Power Adaptation (TPA) scheme for obtaining better power tuning, which senses and examines the probability of channel congestion. Afterwards, it proactively predicts upcoming channel statuses using developed evaluation-weighted matrix, which observes correlations between coefficients of variance for estimated metrics. Considering beacon transmission error rate, crowding inter-vehicle distance, and channel delay, the matrix is periodically constructed and proavtively weighted for each metric based on a predefined threshold value. Eventually, predicted channel status is used as an indicator to adjust transmission power. This leads to decreased channel congestion and better awareness in IoV. The performance of the proposed TPA scheme is evaluated using OMNeT++ simulation tools. The simulation results show that our proposed TPA scheme performs better than existing method in terms of overall throughput, average beacon congestion rate, beacon recipient rate probabilities, channel-busy time, transmission power over distance, and accident probabilities.Published versio

    Improved Geographical Routing in Vehicular Ad Hoc Networks

    Get PDF
    Vehicular Ad Hoc Networks (VANET) has emerged to establish communication between intelligent vehicles. The high mobility of vehicles and existing of obstacles in urban area make the communication link between vehicles to be unreliable. In this environment, most geographical routing protocols does not consider stable and reliable link during packet forwarding towards destination. Thus, the network performance will be degraded due to large number of packet losses and high packet delay. In this paper, we propose an improved geographical routing protocol named IG for VANET. The proposed IG incorporates relative direction between source vehicle and candidate vehicles, distance between candidate node and destination and beacon reception rate in order to improve geographical greedy forwarding between intersection. Simulation results show that the proposed routing protocols performs better as compared to the existing routing solution

    Improved Geographical Routing in Vehicular Ad Hoc Networks

    Full text link
    Vehicular Ad Hoc Networks (VANET) has emerged to establish communication between intelligent vehicles. The high mobility of vehicles and existing of obstacles in urban area make the communication link between vehicles to be unreliable. In this environment, most geographical routing protocols does not consider stable and reliable link during packet forwarding towards destination. Thus, the network performance will be degraded due to large number of packet losses and high packet delay. In this paper, we propose an improved geographical routing protocol named IG for VANET. The proposed IG incorporates relative direction between source vehicle and candidate vehicles, distance between candidate node and destination and beacon reception rate in order to improve geographical greedy forwarding between intersection. Simulation results show that the proposed routing protocols performs better as compared to the existing routing solution.Ghafoor, KZ.; Lloret, J.; Sadiq, AS.; Mohammed, MA. (2015). Improved Geographical Routing in Vehicular Ad Hoc Networks. Wireless Personal Communications. 80(2):785-804. doi:10.1007/s11277-014-2041-3S785804802European-ITS, Eits-technical report 102 638 v1.1.1, European Telecommunications Standards Institute (ETSI). http://www.etsi.org/WebSite/homepage.aspx (2009).Pereira, P., Casaca, A., Rodrigues, J., Soares, V., Triay, J., & Cervelló-Pastor, C. (2011). From delay-tolerant networks to vehicular delay-tolerant networks. IEEE Communications Surveys & Tutorials, 14(4), 1166–1182.Soares, V. N., Farahmand, F., & Rodrigues, J. (2009). A layered architecture for vehicular delay-tolerant networksomputer. In IEEE symposium on computers and communications (ISCC) (pp. 122–127). Tunisia: IEEE.Cabrera, V., Ros, F., & Ruiz, P. (2009). Simulation-based study of common issues in vanet routing protocols. In Proceedings of the 2009 IEEE vehicular technology conference (pp. 1–5). Barcelona: IEEE.Chen, Y., Lin, Y., & Pan, C. (2010). Dir: Diagonal-intersection-based routing protocol for vehicular ad hoc networks. In Telecommunication systems 10 (1007), pp. 1–18. Netherlands: Springer.Cheng, P., Lee, K., Gerla, M., & Harri, J. (2010). Geodtn+ nav: Geographic dtn routing with navigator prediction for urban vehicular environments. Mobile Networks and Applications, 15(1), 61–82. Kluwer Academic Publishers.Djahel, S., & Ghamri-Doudane, Y. (2012). A robust congestion control scheme for fast and reliable dissemination of safety messages in vanets. In Proceeding of the 2012 IEEE conference wireless communications and networking (pp. 2264–2269). France, Paris: IEEE.Ghafoor, K., & Bakar, K. (2010). A novel delay and reliability aware inter vehicle routing protocol. Network Protocols and Algorithms, 2(2), 66–88.Soares, V. N., Farahmand, F., & Rodrigues, J. J. (2009). Evaluating the impact of storage capacity constraints on vehicular delay-tolerant networks. In Proceedings of the conference on communication theory, reliability, and quality of service (pp. 75–80). France: IEEE.Lee, K., Lee, U., & Gerla, M. (2009). To-go: Topology-assist geo-opportunistic routing in urban vehicular grids. In Proceedings of the 2009 IEEE international conference on wireless on-demand network systems and services, Snowbird (pp. 11–18). Utah: IEEE.Moustafa, H., & Zhang, Y. (2009). Vehicular networks: Techniques, standards and applications (1st ed.). Boca Raton: Auerbach Publications.Yan, G., & Olariu, S. (2011). A probabilistic analysis of link duration in vehicular ad hoc networks. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1227–1236.Hasan, S. F., Ding, X., Siddique, N. H., & Chakraborty, S. (2011). Measuring disruption in vehicular communications. IEEE Transactions on Vehicular Technology, 60(1), 148–159.Paula, M. C., Isento, J. N., Dias, J. A., & Rodrigues, J. J. (2011). A real-world vdtn testbed for advanced vehicular services and applications. In Proceedings of the conference on computer aided modeling and design of communication links and networks (CAMAD) (16–20). Spain: IEEE.Barr, R. (2004). An efficient, unifying approach to simulation using virtual machines, Ph.D. thesis, Cornell University.Finn, G. (1987) Routing and addressing problems in large metropolitan-scale internetworks. technical report isi/rr-87-i80.Basagni, S., Chlamtac, I., Syrotiuk, V., Woodward, B. (1998).A distance routing effect algorithm for mobility (dream). In Proceedings of the 1998 ACM/IEEE international conference on mobile computing and networking (76–84). Dallas, TX: ACM.Khamayseh, Y. M., BaniYassein, M., AbdAlghani, M., & Mavromoustakis, C. X. (2013). Network size estimation in vanets. Network Protocols and Algorithms, 5(3), 136–152.Ghafoor, K. Z., Mohammed, M. A., Lloret, J., Bakar, K. A., & Zainuddin, Z. M. (2013). Routing protocols in vehicular ad hoc networks: Survey and research challenges. Network Protocols and Algorithms, 5(4), 39–83.Bhattacharjee, S., Calvert, K., & Zegura, E. (1998). Self-organizing wide-area network caches. In Proceedings of the 1998 IEEE conference on computer and communications (pp. 600–608). San Francisco: IEEE.Blum, B., He, T., Son, S., & Stankovic, J. (2003). Igf: A state-free robust communication protocol for wireless sensor networks. Technical report cs-2003-11, Department of Computer Science, University of Virginia.Jarupan, B., & Ekici, E. (2010). Prompt: A cross-layer position-based communication protocol for delay-aware vehicular access networks. Ad Hoc Networks, 8(5), 489–505.Lequerica, I., Garcia Longaron, M., & Ruiz, P. (2010). Drive and share: Efficient provisioning of social networks in vehicular scenarios. IEEE Communications Magazine, 48(11), 90–97.Karp, B., & Kung, H. (2000). Gpsr: Greedy perimeter stateless routing for wireless networks. In Proceedings of the 2000 ACM International Conference on Mobile Computing and Networking (pp. 243–254). Boston, MA: ACM.Lochert, C., Mauve, M., Fußler, H., & Hartenstein, H. (2005). Geographic routing in city scenarios. Mobile Computing and Communications Review, 9(1), 69–72.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 2003 IEEE international symposium on intelligent vehicles (156–161) Columbus, Ohio: IEEE.Nzouonta, J., Rajgure, N., Wang, G., & Borcea, C. (2009). Vanet routing on city roads using real-time vehicular traffic information. IEEE Transactions on Vehicular Technology, 58(7), 3609–3626.Jerbi, M., Senouci, S., Rasheed, T., & Ghamri-Doudane, Y. (2009). Towards efficient geographic routing in urban vehicular networks. IEEE Transactions on Vehicular Technology, 58(9), 5048–5059.Sadiq, A., Abu Bakar, K., & Ghafoor, K. Z. (2011). A fuzzy logic approach for reducing handover latency in wireless networks. Network Protocols and Algorithms, 2(4), 61–87.Choffnes, D., Bustamante, F. (2005). An integrated mobility and traffic model for vehicular wireless networks. In Proceedings of the 2005 ACM international workshop on Vehicular ad hoc networks (pp. 69–78). Cologne: ACM.Torrent-Moreno, M., Santi, P., & Hartenstein, H. (2009). Vehicle-to-vehicle communication: Fair transmit power control for safety critical information. IEEE Transaction for Vehicular Technology, 58(7), 3684–3703.Nakagami, M. (1960). The m-distribution-a general formula of intensity distribution of rapid fading. Statistical Method of Radio Propagation, 1, 1–20.Nikolić, P., Krstic, D., Stefanovic, M., Panić, S., & Destović, F. (2010). Performance evaluation of mrc systems in the presence of nakagami-m fading and shadowing. In Proceedings of the 2010 9th international symposium on electronics and telecommunications (ISETC) (pp. 289–293) IEEE.Lee, K., Cheng, P., & Gerla, M. (2010). Geocross: A geographic routing protocol in the presence of loops in urban scenarios. Ad Hoc Networks, 8(5), 474–488.Jarupan, B., & Ekici, E. (2009). Location-and delay-aware cross-layer communication in V2I multihop vehicular networks. IEEE Communications Magazine, 47(11), 112–118.Wang, X., Yang, Y., & An, J. (2009). Multi-metric routing decisions in vanet. In Proceedings of the 2009 IEEE international conference on dependable, autonomic and secure computing (pp. 551–556). Chengdu: IEEE
    corecore