3,470 research outputs found

    Path loss modeling for vehicular system performance and communicaitons protocols evaluation

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    Vehicular communications are receiving considerable attention due to the introduction of the intelligent transportation system (ITS) concept, enabling smart and intelligent driving technologies and applications. To design, evaluate and optimize ITS applications and services oriented to improve vehicular safety, but also non-safety applications based on wireless systems, the knowledge of the propagation channel is vital. In particular, the mean path loss is one of the most important parameters used in the link budget, being a measure of the channel quality and limiting the maximum allowed distance between the transmitter (Tx) and the receiver (Rx). From a narrowband vehicular-to-vehicular (V2V) channel measurement campaign carried out at 5.9 GHz in three different urban environments characterized by high traffic density, this paper analyzes the path loss in terms of the Tx-Rx separation distance and fading statistics. Based on a linear slope model, values for the path loss exponent and the standard deviation of shadowing are reported. We have evaluated the packet error rate (PER) and the maximum achievable Tx-Rx separation distance for a PER threshold level of 10% according to the digital short-range communications (DSRC) specifications. The results reported here can be incorporated in an easy way to vehicular networks (VANETs) simulators in order to develop, evaluate and validate new protocols and systems architecture configurations under realistic propagation conditions.Fernández González, HA.; Rubio Arjona, L.; Reig, J.; Rodrigo Peñarrocha, VM.; Valero-Nogueira, A. (2013). Path loss modeling for vehicular system performance and communicaitons protocols evaluation. Mobile Networks and Applications. 18(6):755-765. doi:10.1007/s11036-013-0463-xS755765186Gallager B, Akatsuka H, Suzuki H (2006) Wireless communications for vehicle safety: radio link performance and wireless connectivity. IEEE Veh Technol Mag 1(4):4–24Rubio L, Reig J, Fernández H (2011) Propagation aspects in vehicular networks, Vehicular technologies. Almeida M (ed) InTechWang C-X, Vasilakos A, Murch R, Shen SGX, Chen W, Kosch T (2011) Guest editorial. Vehicular communications and networks – part I. IEEE J Select Areas Commun 29(1):1–6ASTM E2213-03 (2003) Standard specification for telecommunications and information exchange between roadside and vehicle systems – 5 GHz band Dedicated Short Range Communications (DSRC) Medium Access Control (MAC) and Physical Layer (PHY) specifications. American Society for Testing Materials (ASTM), West ConshohockenIEEE 1609 – Family of Standards for Wireless Access in Vehicular Environments (WAVE). [Online]. Available: http://www.standards.its.dot.govETSI TR 102 492–2 Part 2 (2006) Technical characteristics for Pan European Harminized Communications Equipment Operating in the 5 GHz frequency range intended for road safety and traffic management, and for non-safety related ITS applications, European Telecommunications Standard Institute (ETSI), Technical Report, Sophia Antipolis, FranceThe Car-to-Car Communication Comsortium (C2CC): http:/www.car-to-car.orgMecklenbräuker C, Molisch A, Karedal J, Tufvesson F, Paier A, Bernado L, Zemen T, Klemp O, Czink N (2011) Vehicular channel characterization and its implications for wireless system design and performance. IEEE Proc 99(7):1189–1212Ghafoor KZ, Bakar KA, Lloret J, Khokhar RH, Lee KC (2013) Intelligent beaconless geographical routing for urban vehicular environments. Int J Wireless Netw 19(3):345–362Ghafoor KZ, Lloret J, Bakar KA, Sadiq AS, Mussa SAB (2013) Beaconing approaches in vehicular ad hoc networks: a survey. Int J Wirel Pers Commun. Published Online (May 2013)Michelson DG, Ghassemzadeh SS (2009) New directions in wireless communications, Springer Science+Busines Media (Chapter 1)IEEE 802.11p (2010) Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 6: Wireless Access in Vehicular Environments, Institute of Electrical and Electronic Engineers (IEEE), New York, USA.Karedal J, Czink N, Paier A, Tufvesson F, Moisch AF (2011) Path loss modeling for vehicle-to-vehicle communications. IEEE Trans Veh Technol 60(1):323–327Cheng L, Henty B, Stancil D, Bai F, Mudalige P (2007) Mobile vehicle-to-vehicle narrow-band channel measurement and characterization of the 5.9 GHz dedicated short range communication (DSRC) frequency band. IEEE J Select Areas Commun 25(8):1501–1516Cheng L, Henty B, Cooper R, Stancil D, Bai F (2008) Multi-path propagation measurements for vehicular networks at 5.9 GHz. IEEE Wireless Communications and Networking Conference, pp. 1239–1244Tan I, Tang W, Laberteaux K, Bahai N (2008) Measurement and analysis of wireless channel impairments in dsrc vehicular communications. IEEE International Conference on Communications, pp. 4882–4888.Campuzano AJ, Fernández H, Balaguer D, Vila-Jiménez A, Bernardo-Clemente B, Rodrigo-Peñarrocha VM, Reig J, Valero-Nogueira A, Rubio L (2012) Vehicular-to-vehicular channel characterization and measurement results. WAVES 4(1):14–24Kunisch J, Pamp J (2008) Wideband car-to-car radio channel measurements and model at 5.9 GHz. IEEE 68th Vehicular Technology Conference, pp. 1–5Gozalvez J, Sepulcre M (2007) Opportunistic technique for efficient wireless vehicular communications. IEEE Veh Technol Mag 2(4):33–39Zang Y, Stibor L, Orfanos G, Guo S, Reumerman H (2005) An error model for inter-vehicle communications in highway scenarios at 5.9 GHz. Proc. Int. Workshop on performance evaluation of wireless ad hoc, sensor, and ubiquitous networks, pp. 49–5

    IEEE Access special section editorial: Artificial intelligence enabled networking

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    With today’s computer networks becoming increasingly dynamic, heterogeneous, and complex, there is great interest in deploying artificial intelligence (AI) based techniques for optimization and management of computer networks. AI techniques—that subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have long been applied to optimize computer networks in many diverse settings. Such an approach is gaining increased traction with the emergence of novel networking paradigms that promise to simplify network management (e.g., cloud computing, network functions virtualization, and software-defined networking) and provide intelligent services (e.g., future 5G mobile networks). Looking ahead, greater integration of AI into networking architectures can help develop a future vision of cognitive networks that will show network-wide intelligent behavior to solve problems of network heterogeneity, performance, and quality of service (QoS)

    Guest editorial: Time-critical communication and computation for intelligent vehicular networks

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    Vehicular networks are expected to empower auto mated driving and intelligent transportation via vehicle-to-everything (V2X) communications and edge/cloud-assisted computation, and in the meantime Cellular V2X (C-V2X) is gaining wide support from the global industrial ecosystem. The 5G NR-V2X technology is the evolution of LTE-V2X, which is expected to provide ultra-Reliable and Low-Latency Communications (uRLLC) with 1ms latency and 99.999% reliability. Nevertheless, vehicular networks still face great challenges in supporting many emerging time-critical applications, which comprise sensing, communication and computation as closed-loops

    IEEE Access Special Section Editorial: Energy Management in Buildings

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    Energy usage in buildings has become a critical concern globally, and with that, the concept of energy management in buildings has emerged to help tackle these challenges. The energy management system provides a new opportunity for the building's energy requirements, and is an essential method for energy service, i.e., energy saving, consumption,

    Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks

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    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-

    Ieee access special section editorial: Cloud and big data-based next-generation cognitive radio networks

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    In cognitive radio networks (CRN), secondary users (SUs) are required to detect the presence of the licensed users, known as primary users (PUs), and to find spectrum holes for opportunistic spectrum access without causing harmful interference to PUs. However, due to complicated data processing, non-real-Time information exchange and limited memory, SUs often suffer from imperfect sensing and unreliable spectrum access. Cloud computing can solve this problem by allowing the data to be stored and processed in a shared environment. Furthermore, the information from a massive number of SUs allows for more comprehensive information exchanges to assist the
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