Design and analysis of a beacon-less routing protocol for large volume content dissemination in vehicular ad hoc networks

Largevolumecontentdisseminationispursuedbythegrowingnumberofhighquality applications for Vehicular Ad hoc NETworks(VANETs), e.g., the live road surveillance service and the video-based overtaking assistant service. For the highly dynamical vehicular network topology, beacon-less routing protocols have been proven to be efficient in achieving a balance between the system performance and the control overhead. However, to the authors’ best knowledge, the routing design for large volume content has not been well considered in the previous work, which will introduce new challenges, e.g., the enhanced connectivity requirement for a radio link. In this paper, a link Lifetime-aware Beacon-less Routing Protocol (LBRP) is designed for large volume content delivery in VANETs. Each vehicle makes the forwarding decision based on the message header information and its current state, including the speed and position information. A semi-Markov process analytical model is proposed to evaluate the expected delay in constructing one routing path for LBRP. Simulations show that the proposed LBRP scheme outperforms the traditional dissemination protocols in providing a low end-to-end delay. The analytical model is shown to exhibit a good match on the delay estimation with Monte Carlo simulations, as well

Node Density Estimation in VANETs Using Received Signal Power

Accurately estimating node density in Vehicular Ad hoc Networks, VANETs, is a challenging and crucial task. Various approaches exist, yet none takes advantage of physical layer parameters in a distributed fashion. This paper describes a framework that allows individual nodes to estimate the node density of their surrounding network independent of beacon messages and other infrastructure-based information. The proposal relies on three factors: 1) a discrete event simulator to estimate the average number of nodes transmitting simultaneously; 2) a realistic channel model for VANETs environment; and 3) a node density estimation technique. This work provides every vehicle on the road with two equations indicating the relation between 1) received signal strength versus simultaneously transmitting nodes, and 2) simultaneously transmitting nodes versus node density. Access to these equations enables individual nodes to estimate their real-time surrounding node density. The system is designed to work for the most complicated scenarios where nodes have no information about the topology of the network and, accordingly, the results indicate that the system is reasonably reliable and accurate. The outcome of this work has various applications and can be used for any protocol that is affected by node density

A Taxonomy for Congestion Control Algorithms in Vehicular Ad Hoc Networks

One of the main criteria in Vehicular Ad hoc Networks (VANETs) that has attracted the researchers' consideration is congestion control. Accordingly, many algorithms have been proposed to alleviate the congestion problem, although it is hard to find an appropriate algorithm for applications and safety messages among them. Safety messages encompass beacons and event-driven messages. Delay and reliability are essential requirements for event-driven messages. In crowded networks where beacon messages are broadcasted at a high number of frequencies by many vehicles, the Control Channel (CCH), which used for beacons sending, will be easily congested. On the other hand, to guarantee the reliability and timely delivery of event-driven messages, having a congestion free control channel is a necessity. Thus, consideration of this study is given to find a solution for the congestion problem in VANETs by taking a comprehensive look at the existent congestion control algorithms. In addition, the taxonomy for congestion control algorithms in VANETs is presented based on three classes, namely, proactive, reactive and hybrid. Finally, we have found the criteria in which fulfill prerequisite of a good congestion control algorithm

Beaconing Approaches in Vehicular Ad Hoc Networks: A Survey

A Vehicular Ad hoc Network (VANET) is a type of wireless ad hoc network that facilitates ubiquitous connectivity between vehicles in the absence of fixed infrastructure. Beaconing approaches is an important research challenge in high mobility vehicular networks with enabling safety applications. In this article, we perform a survey and a comparative study of state-of-the-art adaptive beaconing approaches in VANET, that explores the main advantages and drawbacks behind their design. The survey part of the paper presents a review of existing adaptive beaconing approaches such as adaptive beacon transmission power, beacon rate adaptation, contention window size adjustment and Hybrid adaptation beaconing techniques. The comparative study of the paper compares the representatives of adaptive beaconing approaches in terms of their objective of study, summary of their study, the utilized simulator and the type of vehicular scenario. Finally, we discussed the open issues and research directions related to VANET adaptive beaconing approaches.Ghafoor, KZ.; Lloret, J.; Abu Bakar, K.; Sadiq, AS.; Ben Mussa, SA. (2013). Beaconing Approaches in Vehicular Ad Hoc Networks: A Survey. Wireless Personal Communications. 73(3):885-912. doi:10.1007/s11277-013-1222-9S885912733ITS-Standards (1996) Intelligent transportation systems, U.S. Department of Transportation, http://www.standards.its.dot.gov/about.aspCheng, L., Henty, B., Stancil, D., Bai, F., & Mudalige, P. (2005). Mobile vehicle-to-vehicle narrow-band channel measurement and characterization of the 5.9 Ghz dedicated short range communication (DSRC) frequency band. IEEE Transactions on Selected Areas in Communications, 25(8), 1501–1516.van Eenennaam, E., Wolterink, K., Karagiannis, G., & Heijenk, G. (2009). Exploring the solution space of beaconing in vanets. In Proceedings of the 2009 IEEE international vehicular networking conference, Tokyo (pp. 1–8).Torrent-Moreno, M. (2007). Inter-vehicle communications: Assessing information dissemination under safety constraints. In Proceedings of the 2007 IEEE conference wireless on demand network systems and services, Austria (pp. 59–64).Lloret, J., Canovas, A., Catalá, A., & Garcia, M. (2012). Group-based protocol and mobility model for vanets to offer internet access. Journal of Network and Computer Applications 2224–2245 doi: 10.1016j.jnca.2012.02.009 .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.Fukui, R., Koike, H., & Okada, H. (2002). Dynamic integrated transmission control(ditrac) over inter-vehicle communications. In Proceedings of the 2002 IEEE vehicular technology conference, Birmingham (pp. 483–487).Schmidt, R., Leinmuller, T., Schoch, E., Kargl, F., & Schafer, G. (2010). Exploration of adaptive beaconing for efficient intervehicle safety communication. IEEE Network, 24(1), 14–19.Ghafoor, K., Bakar, K., van Eenennaam, E., Khokhar, R., Gonzalez, A. A fuzzy logic approach to beaconing for vehicular ad hoc networks, Accepted for publication in Telecommunication Systems Journal.Ghafoor, K., & Bakar, K. (2010). A novel delay and reliability aware inter vehicle routing protocol. Network Protocols and Algorithms, 2(2), 66–88.Mittag, J., Thomas, F., Härri, J., & Hartenstein, H. (2009). A comparison of single-and multi-hop beaconing in vanets. In Proceedings of the 2009 ACM international workshop on vehicular internetworking, Beijing (pp. 69–78).Sommer, C., Tonguz, O., & Dressler, F. (2010). Adaptive beaconing for delay-sensitive and congestion-aware traffic information systems. In Proceedings of the 2010 IEEE international vehicular networking conference (VNC), New Jersey (pp. 1–8).Guan, X., Sengupta, R., Krishnan, H., & Bai, F. (2007). A feedback-based power control algorithm design for vanet. In Proceedings of the 2007 IEEE international conference on mobile networking for vehicular environments, USA (pp. 67–72).AL-Hashimi, H., Bakar, K., & Ghafoor, K. (2011). Inter-domain proxy mobile ipv6 based vehicular network. Network Protocols and Algorithms, 2(4), 1–15.Rawat, D., Popescu, D., Yan, G., & Olariu, S. (2011). Enhancing vanet performance by joint adaptation of transmission power and contention window size. Transactions on Parallel and Distributed Systems, 22(9), 1528–1535.European-ITS (2009) Eits-technical report 102 638 v1.1.1, European Telecommunications Standards Institute (ETSI), http://www.etsi.org/WebSite/homepage.aspxNHTSA, I. Joint program office”, report to congress on the national highway traffic safety administration its program, program progress during 1992–1996 and strategic plan for 1997–2002, US Department of Transportation, Washington, DC.Godbole, D., Sengupta, R., Misener, J., Kourjanskaia, N., & Michael, J. (1998). Benefit evaluation of crash avoidance systems. Transportation Research, 1621(1), 1–9.Reinders, R., van Eenennaam, M., Karagiannis, G., & Heijenk, G. (2004). Contention window analysis for beaconing in vanets. In Proceedings of the 2011 IEEE international conference on wireless communications and mobile computing (IWCMC), Istanbul (pp. 1481–1487).Yang, L., Guo, J., & Wu, Y. (2008). Channel adaptive one hop broadcasting for vanets. In Proceedings of the 2008 IEEE international conference on intelligent transportation systems, Beijing (pp. 369–374).Tseng, Y., Ni, S., Chen, Y., & Sheu, J. (2002). The broadcast storm problem in a mobile ad hoc network. Wireless Networks, 8(2), 153–167.van Eenennaam, E. M., Karagiannis, G., & Heijenk, G. (2010). Towards scalable beaconing in vanets. In Proceedings of the 2010 ERCIM workshop on eMobility, Lulea (pp. 103–108).Ros, F., Ruiz, P., & Stojmenovic, I. (2012). Acknowledgment-based broadcast protocol for reliable and efficient data dissemination in vehicular ad-hoc networks. IEEE Transactions on Mobile Computing, 11(1), 33–46.Torrent-Moreno, M., Santi, P., & Hartenstein, H. (2006). Distributed fair transmit power adjustment for vehicular ad hoc networks. In Proceedings of the 2007 IEEE international conference on sensor and ad hoc communications and networks, Reston, VA (pp. 479–488).Artimy, M. (2007). Local density estimation and dynamic transmission-range assignment in vehicular ad hoc networks. IEEE Transactions on Intelligent Transportation Systems, 8(3), 400–412.Caizzone, G., Giacomazzi, P., Musumeci, L., & Verticale, G. (2005). A power control algorithm with high channel availability for vehicular ad hoc networks. In Proceedings of the 2005 IEEE international conference on communications, Seoul (pp. 3171–3176).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.Torrent-Moreno, M., Schmidt-Eisenlohr, F., Fubler, H., & Hartenstein, H. (2006). Effects of a realistic channel model on packet forwarding in vehicular ad hoc networks. In Proceedings of the 2007 IEEE conference on wireless communications and networking, USA (pp. 385–391).NS, Network simulator (June 2011). http://nsnam.isi.edu/nsnam/index.php/MainPageNakagami, M. (1960). The m-distribution: A general formula of intensity distribution of rapid fadinge. In W. C. Hoffman (Ed.), Statistical method of radio propagation. New York: Pergamon Press.Narayanaswamy, S., Kawadia, V., Sreenivas, R., & Kumar, P. (2002). Power control in ad-hoc networks: Theory, architecture, algorithm and implementation of the compow protocol. In Proceedings of the 2002 European wireless conference next generation wireless networks: technologies, protocols, Italy (pp. 1–6).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.Gomez, J., & Campbell, A. (2004). A case for variable-range transmission power control in wireless multihop networks. In Proceedings twenty-third annual joint conference of the IEEE computer and communications societies, Hong kong (pp. 1425–1436).Ramanathan, R., & Rosales-Hain, R. (2000). Topology control of multihop wireless networks using transmit power adjustment. In Proceedings nineteenth annual joint conference of the IEEE computer and communications societies, Hong kong (pp. 404–413).Artimy, M., Robertson, W., & Phillips, W. (2005). Assignment of dynamic transmission range based on estimation of vehicle density. In Proceedings of the 2nd ACM international workshop on vehicular ad hoc networks, Germany (pp. 40–48).Samara, G., Ramadas, S., & Al-Salihy, W. (2010). Safety message power transmission control for vehicular ad hoc networks. Computer Science, 6(10), 1027–1032.Rezaei, S., Sengupta, R., Krishnan, H., Guan, X., & Student, P. (2008). Adaptive communication scheme for cooperative active safety system.Rezaei, S., Sengupta, R., Krishnan, H., & Guan, X. (2007). Reducing the communication required by dsrc-based vehicle safety systems. In Proceedings of the 2007 IEEE international conference on intelligent transportation systems, Bellevue, WA (pp. 361–366).Sommer, C., Tonguz, O., & Dressler, F. (2011). Traffic information systems: Efficient message dissemination via adaptive beaconing. IEEE Communications Magazine, 49(5), 173–179.Thaina, C., Nakorn, K., & Rojviboonchai, K. (2011). A study of adaptive beacon transmission on vehicular ad-hoc networks. In Proceeding of the 2011 IEEE 13th international conference on communication technology (ICCT), Vancouver (pp. 597–602).Boukerche, A., Rezende, C., & Pazzi, R. (2009). Improving neighbor localization in vehicular ad hoc networks to avoid overhead from periodic messages. In Proceedings of the 2009 IEEE global telecommunications conference, USA (pp. 1–6).Bai, F., Sadagopan, N., & Helmy, A. (2008). Important: A framework to systematically analyze the impact of mobility on performance of routing protocols for adhoc networks. In Proceedings of the 2003 22th annual joint conference of the IEEE computer and communications, USA (pp. 825–835).Nguyen, H., Bhawiyuga, A., & Jeong, H. (2012). A comprehensive analysis of beacon dissemination in vehicular networks. In Proceedings of the 75th IEEE vehicular technology conference, Korea (pp. 1–5).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, Paris, France (pp. 2264–2269).O. Technologies (Augast 2012) Opnet modeler, http://www.opnet.com/Huang, C., Fallah, Y., Sengupta, R., & Krishnan, H. (2010). Adaptive intervehicle communication control for cooperative safety systems. IEEE Network, 24(1), 6–13.OPNET (June 2012) Opnet modeler, http://www.opnet.com/Kerner, B. (2004). The physics of traffic: Empirical freeway pattern features, engineering applications, and theory. Berlin: Springer.Vinel, A., Vishnevsky, V., & Koucheryavy, Y. (2008). A simple analytical model for the periodic broadcasting in vehicular ad-hoc networks. In Proceedings of the 2008 IEEE international GLOBECOM workshops, Philadelphia, PA (pp. 1–5).Mariyasagayam, N., Menouar, H., & Lenardi, M. (2009). An adaptive forwarding mechanism for data dissemination in vehicular networks. In Proceedings of the 2009 IEEE Vehicular Networking Conference, Boston (pp. 1–5).Hung, C., Chan, H., & Wu, E. (2008). Mobility pattern aware routing for heterogeneous vehicular networks. In Proceedings of the 2008 international conference on wireless communications and networking, Las Vegas (pp. 2200–2205).Yang, K., Ou, S., Chen, H., & He, J. (2007). A multihop peer-communication protocol with fairness guarantee for ieee 802.16-based vehicular networks. IEEE Transactions on Vehicular Technology, 56(6), 3358–3370.Lequerica, I., Ruiz, P., & Cabrera, V. (2010). Improvement of vehicular communications by using 3G capabilities to disseminate control information. IEEE Network Magazine, 24(1), 32–38.Oh, D., Kim, P., Song, J., Jeon, S., & Lee, H. (2005). Design considerations of satellite-based vehicular broadband networks. IEEE Wireless Communications Magazine, 12(5), 91–97.Ko, Y., Sim, M., & Nekovee, M. (2006). Wi-fi based broadband wireless access for users on the road. BT Technology Journal, 24(2), 123–129.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, Cologne (pp. 69–78).TIGER (October 2010) Topologically integrated geographic encoding and referencing system, http://www.census.gov/geo/www/tiger/Mittag, J., Thomas, F., Harri, J., & Hartenstein, H. (2009). A comparison of single and multi-hop beaconing in vanets. In Proceedings of the 2009 ACM international workshop on vehiculaar internetworking, Beijing (pp. 69–78).Rappaport, T. (1996). Wireless communications: Principles and practice (2nd ed.). New Jersey: Prentice Hall PTR

Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks

Vehicular Ad Hoc Network (VANET) is an emerging area of wireless ad hoc networks that facilitates ubiquitous connectivity between smart vehicles through Vehicle-to-Vehicle (V2V) or Vehicle-to-Roadside (V2R) and Roadside-to- Vehicle (R2V) communications. This emerging field of technology aims to improve safety of passengers and traffic flow, reduces pollution to the environment and enables in-vehicle entertainment applications. The safety-related applications could reduce accidents by providing drivers with traffic information such as collision avoidances, traffic flow alarms and road surface conditions. Moreover, the passengers could exploit an available infrastructure in order to connect to the internet for infomobility and entertainment applications.Lloret, J.; Ghafoor, KZ.; Rawat, DB.; Xia, F. (2013). Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks. Mobile Networks and Applications. 18(6):749-754. doi:10.1007/s11036-013-0490-7S749754186Lloret J, Canovas A, Catalá A, Garcia M (2013) Group-based protocol and mobility model for VANETs to offer internet access. J Netw Comput Appl 36(3):1027–1038. doi: 10.1016/j.jnca.2012.02.009Khokhar RH, Zia T, Ghafoor KZ, Lloret J, Shiraz M (2013) Realistic and efficient radio propagation model for V2X communications. KSII Trans Internet Inform Syst 7(8):1933–1953. doi: 10.3837/tiis.2013.08.011Ghafoor KZ (2013) Routing protocols in vehicular ad hoc networks: survey and research challenges, Netw Protocol Algorithm 5(4). doi: 10.5296/npa.v5i4.4134Ghafoor KZ, Bakar KA, Lloret J, Ke C-H, Lee KC (2013) Intelligent beaconless geographical routing for urban vehicular environments. Wirel Netw 19(3):345–362. doi: 10.1007/s11276-012-0470-zGhafoor KZ, Bakar KA, Lee K, AL-Hashimi H (2010) A novel delay- and reliability- aware inter-vehicle routing protocol. Netw Protocol Algorithms 2(2):66–88. doi: 10.5296/npa.v2i2.427Dias JAFF, Rodrigues JJPC, Isento JN, Pereira PRBA, Lloret J (2011) Performance assessment of fragmentation mechanisms for vehicular delay-tolerant networks. EURASIP J Wirel Commun Netw 2011(195):1–14. doi: 10.1186/1687-1499-2011-195Zhang D, Yang Z, Raychoudhury V, Chen Z, Lloret J (2013) An energy-efficient routing protocol using movement trend in vehicular Ad-hoc networks. Comput J 58(8):938–946. doi: 10.1093/comjnl/bxt028Ghafoor KZ, Lloret J, Bakar KA, Sadiq AS, Mussa SAB (2013) Beaconing approaches in vehicular Ad Hoc networks: a survey. Wirel Pers Commun. doi: 10.1007/s11277-013-1222-9Sadiq AS, Bakar KA, Ghafoor KZ, Lloret J (2013) An intelligent vertical handover scheme for audio and video streaming in heterogeneous vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0465-8Khamayseh YM (2013) Network size estimation in VANETs. Netw Protocol Algorithm 5(3):136–152. doi: 10.5296/npa.v5i6.3838Rawat DB, Popescu DC, Yan G, Olariu S (2011) Enhancing VANET performance by joint adaptation of transmission power and contention window size. IEEE Trans Parallel Distrib Syst 22(9):1528–1535Yan G, Rawat DB, Bista BB. Provisioning vehicular ad hoc networks with quality of services. Int J Space-Based Situated Comput 2(2):104–111Rawat DB, Bista BB, Yan G, Weigle MC (2011) Securing vehicular ad-hoc networks against malicious drivers: a probabilistic approach, International Conference on Complex, Intelligent, and Software Intensive Systems Pp. 146–151. June 30, 2011Sun W, Xia F, Ma J, Fu T, Sun Y. An optimal ODAM-based broadcast algorithm for vehicular Ad-Hoc Networks. KSII Trans Internet Inform Syst 6(12): 3257–3274Vinel AV, Dudin AN, Andreev SD, Xia F (2010) Performance modeling methodology of emergency dissemination algorithms for vehicular ad-hoc networks, 6th Communication Systems, Networks & Digital Signal Processing (CSNDSP 2010), Pp. 397–400AL-Hashimi HN, Bakar KA, Ghafoor KZ (2010) Inter-domain proxy mobile IPv6 based vehicular network. Netw Protocol Algorithm 2(4):1–15. doi: 10.5296/npa.v2i4.488Ghafoor KZ, Bakar KA, Mohammed MA, Lloret J (2013) Vehicular cloud computing: trends and challenges, in the book “mobile computing over cloud: technologies, services, and applications”. IGI GlobalYan G, Rawat DB, Bista BB (2012) Towards secure vehicular clouds, Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS 2012), Pp. 370–375Fernández H, Rubio L, Reig J, Rodrigo-Peñarrocha VM, Valero A (2013) Path loss modeling for vehicular system performance and communication protocols evaluation. Mobile Netw Appl. doi: 10.1007/s11036-013-0463-xAllouche Y, Segal M (2013) A cluster-based beaconing approach in VANETs: near optimal topology via proximity information. Mobile Netw Appl. doi: 10.1007/s11036-013-0468-5Merah AF, Samarah S, Boukerche A, Mammeri A (2013) A sequential patterns data mining approach towards vehicular route prediction in VANETs. Mobile Netw Appl. doi: 10.1007/s11036-013-0459-6Zhang D, Huang H, Zhou J, Xia F, Chen Z (2013) Detecting hot road mobility of vehicular Ad Hoc Networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0467-6El Ajaltouni H, Boukerche A, Mammeri A (2013) A multichannel QoS MAC with dynamic transmit opportunity for. Mobile Netw Appl. doi: 10.1007/s11036-013-0475-6Reñé S, Esparza O, Alins J, Mata-Díaz J, Muñoz JL (2013) VSPLIT: a cross-layer architecture for V2I TCP services over. Mobile Netw Appl. doi: 10.1007/s11036-013-0473-8Blanco B, Liberal F (2013) Amaia Aguirregoitia, application of cognitive techniques to adaptive routing for VANETs in city environments. Mobile Netw Appl. doi: 10.1007/s11036-013-0466-7Kim J, Krunz M (2013) Spectrum-aware beaconless geographical routing protocol for cognitive radio enabled vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0476-5Dias JAFF, Rodrigues JJPC, Isento JNG, Niu J (2013) The impact of cooperative nodes on the performance of vehicular delay-tolerant networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0464-9Sadiq AS, Bakar KA, Ghafoor KZ, Lloret J, Khokhar R (2013) An intelligent vertical handover scheme for audio and video streaming in heterogeneous vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0465-8Machado S, Ozón J, González AJ, Ghafoor KZ (2013) Structured peer-to-peer real time video transmission over vehicular Ad Hoc networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0461-zLin C, Wu G, Xia F, Yao L (2013) Enhance the attacking efficiency of the node compromise attack in vehicular Ad-hoc network using connected dominating set. Mobile Netw Appl. doi: 10.1007/s11036-013-0469-

Novel Internet of Vehicles Approaches for Smart Cities

Smart cities are the domain where many electronic devices and sensors transmit data via the Internet of Vehicles concept. The purpose of deploying many sensors in cities is to provide an intelligent environment and a good quality of life. However, different challenges still appear in smart cities such as vehicular traffic congestion, air pollution, and wireless channel communication aspects. Therefore, in order to address these challenges, this thesis develops approaches for vehicular routing, wireless channel congestion alleviation, and traffic estimation. A new traffic congestion avoidance approach has been developed in this thesis based on the simulated annealing and TOPSIS cost function. This approach utilizes data such as the traffic average travel speed from the Internet of Vehicles. Simulation results show that the developed approach improves the traffic performance for the Sheffield the scenario in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO2 emissions as compared to other algorithms. In contrast, transmitting a large amount of data among the sensors leads to a wireless channel congestion problem. This affects the accuracy of transmitted information due to the packets loss and delays time. This thesis proposes two approaches based on a non-cooperative game theory to alleviate the channel congestion problem. Therefore, the congestion control problem is formulated as a non-cooperative game. A proof of the existence of a unique Nash equilibrium is given. The performance of the proposed approaches is evaluated on the highway and urban testing scenarios. This thesis also addresses the problem of missing data when sensors are not available or when the Internet of Vehicles connection fails to provide measurements in smart cities. Two approaches based on l1 norm minimization and a relevance vector machine type optimization are proposed. The performance of the developed approaches has been tested involving simulated and real data scenarios

A short-term vehicular density prediction scheme for enhanced beaconing control.

Channel congestion is a well-known problem in wireless networks in general and Vehicular Ad Hoc Networks (VANETs) in particular. Literature solutions propose to alleviate this problem by controlling the network load based on parameters like vehicle density or packet collision rate. In other words, each vehicle will observe the density of vehicles (or the packet collision rate) around itself in a certain time interval, and use this information to adjust its transmit parameters i.e. transmit rate and/or power, the next time it has a beacon to transmit (in the following time window). However, the information collected in the current time window might not still be valid in the next one. In fact, in a highly dynamic network like VANETs, vehicle density, and consequently the busy ratio and the collision rate, might vary a great deal even in the smallest time intervals. To cope with this newly identified problem, we propose a novel vehicle-centric short-term density prediction scheme that estimates the vehicular density around a given vehicle within the next time window allowing each vehicle to adapt its transmit parameters based on the current state of the network (as opposed to the previous state). The accuracy and the efficiency of our proposed scheme is demonstrated in a proof-of-concept case study, showing a significant improvement in terms of network performance