335 research outputs found

    Optimisation of Mobile Communication Networks - OMCO NET

    Get PDF
    The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

    Design and Implementation of Intelligent Traffic-Management System for Smart Cities using Roaming Agent and Deep Neural Network (RAD2N)

    Get PDF
    In metropolitan areas, the exponential growth in quantity of vehicles has instigated gridlock, pollution, and delays in the transportation of freight. IoT is the modern revolution which pushes the world towards intelligent management systems and automated procedures. This makes a significant contribution to automation and intelligent societies. Traffic regulation and effective congestion management assist conserve many priceless resources. In order to recognize, collect and send data, autonomous vehicles are furnished with IoT powered Intelligent Traffic Management System (ITMS) having a set of sensors.  Moreover, machine learning (ML) algorithms can also be employed to enhance the transportation system.  Traffic jams, delays, and a high death rate are the results of the problems that the current transport management systems face.  In this paper, an active traffic control for VANET is proposed which merges Roaming Agents (RA) with deep neural networks (DNN). The effectiveness of the DNN with RA (RAD2N) routing method in VANETs is evaluated experimentally and compared with the traditional ML and other DL routing algorithms. Several traffic congestion indicators, including delay, packet delivery ratio (PDR) and throughput are used to validate RAD2N. The outcomes demonstrate that the proposed approach delivers lower latency and energy consumption

    Smart handoff technique for internet of vehicles communication using dynamic edge-backup node

    Get PDF
    © 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/electronics9030524A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.Published onlin

    A Comparative Survey of VANET Clustering Techniques

    Full text link
    © 2016 Crown. A vehicular ad hoc network (VANET) is a mobile ad hoc network in which network nodes are vehicles - most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organized nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, information dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation, and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming - the lack of realistic vehicular channel modeling - is identified. The importance of a rigorous and standardized performance evaluation regime utilizing realistic vehicular channel models is demonstrated

    AN ADAPTIVE INFORMATION DISSEMINATION MODEL FOR VANET COMMUNICATION

    Get PDF
    Vehicular ad hoc networks (VANETs) have been envisioned to be useful in road safety and many commercial applications. The growing trend to provide communication among the vehicles on the road has provided the opportunities for developing a variety of applications for VANET. The unique characteristics of VANET bring about new research challenges

    Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

    Get PDF
    We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches

    SDN-based VANET routing: A comprehensive survey on architectures, protocols, analysis, and future challenges

    Get PDF
    As the automotive and telecommunication industries advance, more vehicles are becoming connected, leading to the realization of intelligent transportation systems (ITS). Vehicular ad-hoc network (VANET) supports various ITS services, including safety, convenience, and infotainment services for drivers and passengers. Generally, such services are realized through data sharing among vehicles and nearby infrastructures or vehicles over multi-hop data routing mechanisms. Vehicular data routing faces many challenges caused by vehicle dynamicity, intermittent connectivity, and diverse application requirements. Consequently, the software-defined networking (SDN) paradigm offers unique features such as programmability and flexibility to enhance vehicular network performance and management and meet the quality of services (QoS) requirements of various VANET services. Recently, VANET routing protocols have been improved using the multilevel knowledge and an up-to-date global view of traffic conditions offered by SDN technology. The primary objective of this study is to furnish comprehensive information regarding the current SDN-based VANET routing protocols, encompassing intricate details of their underlying mechanisms, forwarding algorithms, and architectural considerations. Each protocol will be thoroughly examined individually, elucidating its strengths, weaknesses, and proposed enhancements. Also, the software-defined vehicular network (SDVN) architectures are presented according to their operation modes and controlling degree. Then, the potential of SDN-based VANET is explored from the aspect of routing and the design requirements of routing protocols in SDVNs. SDVN routing algorithms are uniquely classified according to various criteria. In addition, a complete comparative analysis will be achieved to analyze the protocols regarding performance, optimization, and simulation results. Finally, the challenges and upcoming research directions for developing such protocols are widely stated here. By presenting such insights, this paper provides a comprehensive overview and inspires researchers to enhance existing protocols and explore novel solutions, thereby paving the way for innovation in this field

    Beaconing Approaches in Vehicular Ad Hoc Networks: A Survey

    Full text link
    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
    • …
    corecore