Dynamic Adaptation of Joint Transmission Power and Contention Window in VANET

In this paper, we propose an algorithm for joint adaptation of transmission power and contention window to improve the performance of vehicular network in a cross layer approach. The high mobility of vehicles in vehicular communication results in the change in topology of the Vehicular Ad-hoc Network (VANET) dynamically, and the communication link between two vehicles might remain active only for short duration of time. In order for VANET to make a connection for long time and to mitigate adverse effects due to high and fixed transmission power, the proposed algorithm adapts transmission power dynamically based on estimated local traffic density. In addition to that, the prioritization of messages according to their urgency is performed for timely propagation of high priority messages to the destination region. In this paper, we incorporate the contention based MAC protocol 802.11e enhanced distributed channel access (EDCA) mechanism to implement a priority-based vehicle-to-vehicle (V2V) communication. Simulation results show that the proposed algorithm is successful in getting better throughput with lower average end-to-end delay than the algorithm with static/default parameters

Towards reliable geographic broadcasting in vehicular networks

In Vehicular ad hoc Networks (VANETs), safety-related messages are broadcasted amongst cars, helping to improve drivers' awareness of the road situation. VANETs’ reliability are highly affected by channel contention. This thesis first addresses the issue of channel use efficiency in geographical broadcasts (geocasts). Constant connectivity changes inside a VANET make the existing routing algorithms unsuitable. This thesis presents a geocast algorithm that uses a metric to estimate the ratio of useful to useless packet received. Simulations showed that this algorithm is more channel-efficient than the farthest-first strategy. It also exposes a parameter, allowing it to adapt to channel load. Second, this thesis presents a method of estimating channel load for providing feedback to moderate the offered load. A theoretical model showing the relationship between channel load and the idle time between transmissions is presented and used to estimate channel contention. Unsaturated stations on the network were shown to have small but observable effects on this relationship. In simulations, channel estimators based on this model show higher accuracy and faster convergence time than by observing packet collisions. These estimators are also less affected by unsaturated stations than by observing packet collisions. Third, this thesis couples the channel estimator to the geocast algorithm, producing a closed-loop load-reactive system that allows geocasts to adapt to instantaneous channel conditions. Simulations showed that this system is not only shown to be more efficient in channel use and be able to adapt to channel contention, but is also able to self-correct suboptimal retransmission decisions. Finally, this thesis demonstrates that all tested network simulators exhibit unexpected behaviours when simulating broadcasts. This thesis describes in depth the error in ns-3, leading to a set of workarounds that allows results from most versions of ns-3 to be interpreted correctly

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

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

Intelligent and bandwidth-efficient medium access control protocols for IEEE 802.11p-based Vehicular Ad hoc Networks

Vehicle-to-Vehicle (V2V) technology aims to enable safer and more sophisticated transportation via the spontaneous formation of Vehicular Ad hoc Networks (VANETs). This type of wireless networks allows the exchange of kinematic and other data among vehicles, for the primary purpose of safer and more efficient driving, as well as efficient traffic management and other third-party services. Their infrastructure-less, unbounded nature allows the formation of dense networks that present a channel sharing issue, which is harder to tackle than in conventional WLANs. This thesis focuses on optimising channel access strategies, which is important for the efficient usage of the available wireless bandwidth and the successful deployment of VANETs. To start with, the default channel access control method for V2V is evaluated hardware via modifying the appropriate wireless interface Linux driver to enable finer on-the-fly control of IEEE 802.11p access control layer parameters. More complex channel sharing scenarios are evaluated via simulations and findings on the behaviour of the access control mechanism are presented. A complete channel sharing efficiency assessment is conducted, including throughput, fairness and latency measurements. A new IEEE 802.11p-compatible Q-Learning-based access control approach that improves upon the studied protocol is presented. The stations feature algorithms that “learn” how to act optimally in VANETs in order to maximise their achieved packet delivery and minimise bandwidth wastage. The feasibility of Q-Learning to be used as the base of selflearning protocols for IEEE 802.11p-based V2V communication access control in dense environments is investigated in terms of parameter tuning, necessary time of exploration, achieving latency requirements, scaling, multi-hop and accommodation of simultaneous applications. Additionally, the novel Collection Contention Estimation (CCE) mechanism for Q-Learning-based access control is presented. By embedding it on the Q-Learning agents, faster convergence, higher throughput, better service separation and short-term fairness are achieved in simulated network deployments. The acquired new insights on the network performance of the proposed algorithms can provide precise guidelines for efficient designs of practical, reliable, fair and ultra-low latency V2V communication systems for dense topologies. These results can potentially have an impact across a range of related areas, including various types of wireless networks and resource allocation for these, network protocol and transceiver design as well as QLearning applicability and considerations for correct use

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

Reverse back-off mechanism for safety vehicular ad hoc networks

International audienceVehicular ad hoc networks can play an important role in enhancing transportation efficiency and improving road safety. Therefore, direct vehicle-to-vehicle communications are considered as one of the main building blocks of a future Intelligent Transportation System. The success and availability of IEEE 802.11 radios made this technology the most probable choice for the medium access control layer in vehicular networks. However, IEEE 802.11 was originally designed in a wireless local area network context and it is not optimised for a dynamic, ad hoc vehicular scenario. In this paper, we investigate the compatibility of the IEEE 802.11 medium access control protocol with the requirements of safety vehicular applications. As the protocols in this family are well-known for their scalability problems, we are especially interested in high density scenarios, quite frequent on today’s roads. Using an analytical framework, we study the performance of the back-off mechanism and the role of the contention window on the control channel of a vehicular network. Based on these findings, we propose a reverse back-off mechanism, specifically designed with road safety applications in mind. Extensive simulations are carried out to prove the efficiency of the proposed enhancement scheme and to better understand the characteristics of vehicular communications