127,427 research outputs found

    Stochastic Petri Nets for Wireless Networks

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    This SpringerBrief presents research in the application of Stochastic Petri Nets (SPN) to the performance evaluation of wireless networks under bursty traffic. It covers typical Quality-of-Service performance metrics such as mean throughput, average delay and packet dropping probability. Along with an introduction of SPN basics, the authors introduce the key motivation and challenges of using SPN to analyze the resource sharing performance in wireless networks. The authors explain two powerful modeling techniques that treat the well-known state space explosion problem: model decomposition and iteration, and model aggregation using stochastic high-level petri nets. The first technique assists in performance analysis of opportunistic scheduling, Device-to-Device communications with full frequency reuse and partial frequency reuse. The second technique is used to formulate a wireless channel mode for cross-layer performance analysis in OFDM system. Stochastic Petri Nets for Wireless Networks reveals useful insights for the design of radio resource management algorithms and a new line of thinking for the performance evaluation of future wireless networks. This material is valuable as a reference for researchers and professionals working in wireless networks and for advanced-level students studying wireless technologies in electrical engineering or computer science

    Feasibility Study of Enabling V2X Communications by LTE-Uu Radio Interface

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    Compared with the legacy wireless networks, the next generation of wireless network targets at different services with divergent QoS requirements, ranging from bandwidth consuming video service to moderate and low date rate machine type services, and supporting as well as strict latency requirements. One emerging new service is to exploit wireless network to improve the efficiency of vehicular traffic and public safety. However, the stringent packet end-to-end (E2E) latency and ultra-low transmission failure rates pose challenging requirements on the legacy networks. In other words, the next generation wireless network needs to support ultra-reliable low latency communications (URLLC) involving new key performance indicators (KPIs) rather than the conventional metric, such as cell throughput in the legacy systems. In this paper, a feasibility study on applying today's LTE network infrastructure and LTE-Uu air interface to provide the URLLC type of services is performed, where the communication takes place between two traffic participants (e.g., vehicle-to-vehicle and vehicle-to-pedestrian). To carry out this study, an evaluation methodology of the cellular vehicle-to-anything (V2X) communication is proposed, where packet E2E latency and successful transmission rate are considered as the key performance indicators (KPIs). Then, we describe the simulation assumptions for the evaluation. Based on them, simulation results are depicted that demonstrate the performance of the LTE network in fulfilling new URLLC requirements. Moreover, sensitivity analysis is also conducted regarding how to further improve system performance, in order to enable new emerging URLLC services.Comment: Accepted by IEEE/CIC ICCC 201

    Wireless Performance Evaluation of Building Layouts: Closed-Form Computation of Figures of Merit

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    This paper presents a part of our ground-breaking work on evaluation of buildings in terms of wireless friendliness in the building-design stage. The main goal is to devise construction practices that provide for a good performance of wireless networks deployed in buildings. In this paper, the interference gain (IG) and power gain (PG) are defined as two figures of merit (FoM) of the wireless performance of buildings. The FoMs bridge the gap between building design and wireless communications industries. An approach to derive exact closed-form equations for these FoMs is proposed for the first time. The derived analytic expressions facilitate straightforward and more computationally efficient numerical evaluation of the proposed FoMs as compared to Monte Carlo simulations for well-known indoor propagation models. It is shown that the derived closed-form expression can be readily employed to evaluate the impact of building properties, such as the sizes and the aspect ratios (ARs) of rooms, on the wireless performance. The proposed approach sheds light to architects on evaluation and design of wireless-friendly building layouts

    Modulation Schemes and Connectivity in Wireless Underground Channel

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    In this chapter, a thorough treatment of the modulation schemes for UG Wireless is presented. The effects of soil texture and water content on the capacity of multi-carrier modulation in WUC are discussed. The multi-carrier capacity model results are analyzed. Moreover, the underground MIMO design for underground communications is explained thoroughly. An analysis of medium access in wireless underground is done as well. Furthermore, the soil properties are considered for cross-layer communications of UG wireless. The performance analysis of traditional modulation schemes is also considered. The soil moisture-based modulation approach is also explored in this chapter. The connectivity and diversity reception approaches are discussed for wireless underground communications. The connectivity and interference models are studied for Ad-Hoc and Hybrid Networks. The topology control mechanisms for maintaining network connectivity are explored for maximizing network capacity under the physical models (e.g., the protocol interference model and physical interference model). Moreover, the underground diversity is examined for 3W-Rake receiver and coherent detection along with experimental evaluation and comprehensive analysis of performance of equalization techniques

    Modeling of Duty-Cycled MAC Protocols for Heterogeneous WSN with Priorities

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    [EN] Wireless Sensor Networks (WSN) have experienced an important revitalization, particularly with the arrival of Internet of Things applications. In a general sense, a WSN can be composed of different classes of nodes, having different characteristics or requirements (heterogeneity). Duty-cycling is a popular technique used in WSN, that allows nodes to sleep and wake up periodically in order to save energy. We believe that the modeling and performance evaluation of heterogeneous WSN with priorities operating in duty-cycling, being of capital importance for their correct design and successful deployment, have not been sufficiently explored. The present work presents a performance evaluation study of a WSN with these features. For a scenario with two classes of nodes composing the network, each with a different channel access priority, an approximate analytical model is developed with a pair of two-dimensional discrete-time Markov chains. Note that the same modeling approach can be used to analyze networks with a larger number of classes. Performance parameters such as average packet delay, throughput and average energy consumption are obtained. Analytical results are validated by simulation, showing accurate results. Furthermore, a new procedure to determine the energy consumption of nodes is proposed that significantly improves the accuracy of previous proposals. We provide quantitative evidence showing that the energy consumption accuracy improvement can be up to two orders of magnitudeThis work is part of the project PGC2018-094151-B-I00, which is financed by the Ministerio de Ciencia, Innovacion y Universidades (MCIU), Agencia Estatal de Investigacion (AEI) and Fondo Europeo de Desarrollo Regional (FEDER) (MCIU/AEI/FEDER.UE). C. Portillo acknowledges the funding received from the European Union under the program Erasmus Mundus Partnerships, project EuroinkaNet, GRANT AGREEMENT NUMBER -2014 -0870/001/001, and the support received from SEP-SES (DSA/103.5/15/6629)Portillo, C.; Martínez Bauset, J.; Pla, V.; Casares-Giner, V. (2020). Modeling of Duty-Cycled MAC Protocols for Heterogeneous WSN with Priorities. Electronics. 9(3):1-16. https://doi.org/10.3390/electronics9030467S11693Gomes, D. A., & Bianchini, D. (2016). Interconnecting Wireless Sensor Networks with the Internet Using Web Services. IEEE Latin America Transactions, 14(4), 1937-1942. doi:10.1109/tla.2016.7483537Libo, Z., Tian, H., & Chunyun, G. (2019). Wireless multimedia sensor network for rape disease detections. EURASIP Journal on Wireless Communications and Networking, 2019(1). doi:10.1186/s13638-019-1468-3Shi, X., An, X., Zhao, Q., Liu, H., Xia, L., Sun, X., & Guo, Y. (2019). State-of-the-Art Internet of Things in Protected Agriculture. Sensors, 19(8), 1833. doi:10.3390/s19081833Rajandekar, A., & Sikdar, B. (2015). A Survey of MAC Layer Issues and Protocols for Machine-to-Machine Communications. IEEE Internet of Things Journal, 2(2), 175-186. doi:10.1109/jiot.2015.2394438Dai, H.-N., Ng, K.-W., & Wu, M.-Y. (2013). On Busy-Tone Based MAC Protocol for Wireless Networks with Directional Antennas. Wireless Personal Communications, 73(3), 611-636. doi:10.1007/s11277-013-1206-9Padilla, P., Padilla, J. L., Valenzuela-Valdés, J. F., Serrán-González, J.-V., & López-Gordo, M. A. (2015). Performance Analysis of Different Link Layer Protocols in Wireless Sensor Networks (WSN). Wireless Personal Communications, 84(4), 3075-3089. doi:10.1007/s11277-015-2783-6Ye, W., Heidemann, J., & Estrin, D. (2004). Medium Access Control With Coordinated Adaptive Sleeping for Wireless Sensor Networks. IEEE/ACM Transactions on Networking, 12(3), 493-506. doi:10.1109/tnet.2004.828953Kuo, Y.-W., Li, C.-L., Jhang, J.-H., & Lin, S. (2018). Design of a Wireless Sensor Network-Based IoT Platform for Wide Area and Heterogeneous Applications. IEEE Sensors Journal, 18(12), 5187-5197. doi:10.1109/jsen.2018.2832664He, X., Liu, S., Yang, G., & Xiong, N. (2018). Achieving Efficient Data Collection in Heterogeneous Sensing WSNs. IEEE Access, 6, 63187-63199. doi:10.1109/access.2018.2876552Ortin, J., Cesana, M., Redondi, A. E. C., Canales, M., & Gallego, J. R. (2019). Analysis of Unslotted IEEE 802.15.4 Networks With Heterogeneous Traffic Classes. IEEE Wireless Communications Letters, 8(2), 380-383. doi:10.1109/lwc.2018.2873347Bianchi, G. (2000). Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 18(3), 535-547. doi:10.1109/49.840210Liu, R. P., Sutton, G. J., & Collings, I. B. (2010). A New Queueing Model for QoS Analysis of IEEE 802.11 DCF with Finite Buffer and Load. IEEE Transactions on Wireless Communications, 9(8), 2664-2675. doi:10.1109/twc.2010.061010.091803Ou Yang, & Heinzelman, W. (2012). Modeling and Performance Analysis for Duty-Cycled MAC Protocols with Applications to S-MAC and X-MAC. IEEE Transactions on Mobile Computing, 11(6), 905-921. doi:10.1109/tmc.2011.121Martinez-Bauset, J., Guntupalli, L., & Li, F. Y. (2015). Performance Analysis of Synchronous Duty-Cycled MAC Protocols. IEEE Wireless Communications Letters, 4(5), 469-472. doi:10.1109/lwc.2015.2439267Guntupalli, L., Martinez-Bauset, J., Li, F. Y., & Weitnauer, M. A. (2017). Aggregated Packet Transmission in Duty-Cycled WSNs: Modeling and Performance Evaluation. IEEE Transactions on Vehicular Technology, 66(1), 563-579. doi:10.1109/tvt.2016.2536686Zhang, R., Moungla, H., Yu, J., & Mehaoua, A. (2017). Medium Access for Concurrent Traffic in Wireless Body Area Networks: Protocol Design and Analysis. IEEE Transactions on Vehicular Technology, 66(3), 2586-2599. doi:10.1109/tvt.2016.2573718Guntupalli, L., Martinez-Bauset, J., & Li, F. Y. (2018). Performance of frame transmissions and event-triggered sleeping in duty-cycled WSNs with error-prone wireless links. Computer Networks, 134, 215-227. doi:10.1016/j.comnet.2018.01.047(July, 2019). The State Transition Probabilities of the Two 2D-DTMC. Technical Report http://personales.upv.es/jmartine/public/2DDTMC.pdfCrossbow Technology Incorporated, San Jose, CA, USA http://www.openautomation.net/uploadsproductos/micaz-datasheet.pd

    A survey of IEEE 802.15.4 effective system parameters for wireless body sensor networks

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    This is the peer reviewed version of the following article: Moravejosharieh, Amirhossein, Lloret, Jaime. (2016). A survey of IEEE 802.15.4 effective system parameters for wireless body sensor networks.International Journal of Communication Systems, 29, 7, 1269-1292. DOI: 10.1002/dac.3098, which has been published in final form at http://doi.org/10.1002/dac.3098. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving[EN] Wireless body sensor networks are offered to meet the requirements of a diverse set of applications such as health-related and well-being applications. For instance, they are deployed to measure, fetch and collect human body vital signs. Such information could be further used for diagnosis and monitoring of medical conditions. IEEE 802.15.4 is arguably considered as a well-designed standard protocol to address the need for low-rate, low-power and low-cost wireless body sensor networks. Apart from the vast deployment of this technology, there are still some challenges and issues related to the performance of the medium access control (MAC) protocol of this standard that are required to be addressed. This paper comprises two main parts. In the first part, the survey has provided a thorough assessment of IEEE 802.15.4 MAC protocol performance where its functionality is evaluated considering a range of effective system parameters, that is, some of the MAC and application parameters and the impact of mutual interference. The second part of this paper is about conducting a simulation study to determine the influence of varying values of the system parameters on IEEE 802.15.4 performance gains. More specifically, we explore the dependability level of IEEE 802.5.4 performance gains on a candidate set of system parameters. Finally, this paper highlights the tangible needs to conduct more investigations on particular aspect(s) of IEEE 802.15.4 MAC protocol. Copyright (c) 2015 John Wiley & Sons, Ltd.Moravejosharieh, A.; Lloret, J. (2016). A survey of IEEE 802.15.4 effective system parameters for wireless body sensor networks. International Journal of Communication Systems. 29(7):1269-1292. https://doi.org/10.1002/dac.3098S12691292297Alrajeh, N. A., Lloret, J., & Canovas, A. (2014). A Framework for Obesity Control Using a Wireless Body Sensor Network. International Journal of Distributed Sensor Networks, 10(7), 534760. doi:10.1155/2014/534760Lopes I Silva B Rodrigues J Lloret J Proenca M A mobile health monitoring solution for weight control International Conference on Wireless Communications and Signal Processing (WCSP) Nanjing / China 2011 1 5Singh, N., Singh, A. K., & Singh, V. K. (2015). Design and performance of wearable ultrawide band textile antenna for medical applications. Microwave and Optical Technology Letters, 57(7), 1553-1557. doi:10.1002/mop.29131Lan, K., Chou, C.-M., Wang, T., & Li, M.-W. (2012). Using body sensor networks for motion detection: a cluster-based approach for green radio. Transactions on Emerging Telecommunications Technologies, 25(2), 199-216. doi:10.1002/ett.2559Lloret, J., Garcia, M., Catala, A., & Rodrigues, J. J. P. C. (2016). A group-based wireless body sensors network using energy harvesting for soccer team monitoring. International Journal of Sensor Networks, 21(4), 208. doi:10.1504/ijsnet.2016.079172Garcia M Catala A Lloret J Rodrigues J A wireless sensor network for soccer team monitoring International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS) Barcelona / Spain 2011 1 6Penders J Gyselinckx B Vullers R De Nil M Nimmala V van de Molengraft J Yazicioglu F Torfs T Leonov V Merken P Van Hoof C Human++: from technology to emerging health monitoring concepts 5th International Summer School and Symposium ISSS-MDBS on Medical Devices and Biosensors Hong Kong 2008 94 98Penders J Van de Molengraft J. 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IEEE Communications Magazine, 42(6), 140-146. doi:10.1109/mcom.2004.1304251Toscano E Lo Bello L Cross-channel interference in IEEE 802.15.4 networks IEEE International Workshop on Factory Communication Systems, 2008. WFCS 2008 Dresden, Germany 2008 139 148Bashir F Baek WS Sthapit P Pandey D young Pyun J Coordinator assisted passive discovery for mobile end devices in IEEE 802.15.4 2013 IEEE Consumer Communications and Networking Conference (CCNC) Las Vegas, U.S. 2013 601 604Tabatabaei Yazdi E Willig A Pawlikowski K Shortening orphan time in IEEE 802.15.4: what can be gained 2013 19th IEEE International Conference on Networks (ICON) Singapore 2013 1 6Park, T. R., Kim, T. H., Choi, J. Y., Choi, S., & Kwon, W. H. (2005). Throughput and energy consumption analysis of IEEE 802.15.4 slotted CSMA∕CA. Electronics Letters, 41(18), 1017. doi:10.1049/el:20051662Bianchi, G. (2000). Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 18(3), 535-547. doi:10.1109/49.840210IEEE Computer Society LAN MAN Standards Committee Wireless LAN medium access control (MAC) and physical layer (PHY) specifications 1997Pollin, S., Ergen, M., Ergen, S. C., Bougard, B., Der Perre, L. V., Moerman, I., … Catthoor, F. (2008). Performance Analysis of Slotted Carrier Sense IEEE 802.15.4 Medium Access Layer. IEEE Transactions on Wireless Communications, 7(9), 3359-3371. doi:10.1109/twc.2008.060057Xinhua Ling, Yu Cheng, Mark, J. W., & Xuemin Shen. (2008). A Renewal Theory Based Analytical Model for the Contention Access Period of IEEE 802.15.4 MAC. IEEE Transactions on Wireless Communications, 7(6), 2340-2349. doi:10.1109/twc.2008.070048Lee, C. Y., Cho, H. I., Hwang, G. U., Doh, Y., & Park, N. (2011). Performance modeling and analysis of IEEE 802.15.4 slotted CSMA/CA protocol with ACK mode. AEU - International Journal of Electronics and Communications, 65(2), 123-131. doi:10.1016/j.aeue.2010.02.007Wang, F., Zhao, Y., & Li, D. (2011). Analysis of CSMA/CA in IEEE 802.15.4. IET Communications, 5(15), 2187-2195. doi:10.1049/iet-com.2010.1007Zhu, J., Tao, Z., & Lv, C. (2011). Performance Evaluation of IEEE 802.15.4 CSMA/CA Scheme Adopting a Modified LIB Model. Wireless Personal Communications, 65(1), 25-51. doi:10.1007/s11277-011-0226-6Shu F Sakurai T Analysis of an energy conserving CSMA-CA GLOBECOM Washington DC, U.S. 2007 2536 2540Shu, F., & Sakurai, T. (2011). A new analytical model for the IEEE 802.15.4 CSMA-CA protocol. Computer Networks, 55(11), 2576-2591. doi:10.1016/j.comnet.2011.04.017Cano-Garcia, J. M., & Casilari, E. (2011). An empirical evaluation of the consumption of 802.15.4/ZigBee sensor motes in noisy environments. 2011 International Conference on Networking, Sensing and Control. doi:10.1109/icnsc.2011.5874886Baz, M., Mitchell, P. D., & Pearce, D. A. J. (2013). Versatile Analytical Model for Delay and Energy Evaluation in WPANs: A Case Study for IEEE 802.15.4 CSMA-CA. Wireless Personal Communications, 75(1), 415-445. doi:10.1007/s11277-013-1370-yLiu Q Czylwik A A priority-based adaptive service differentiation scheme for IEEE 802.15.4 sensor networks Proceedings of European Wireless 2014; 20th European Wireless Conference Barcelona, Spain 2014 1 6Golmie, N., Cypher, D., & Rebala, O. (s. f.). Performance evaluation of low rate WPANs for medical applications. IEEE MILCOM 2004. Military Communications Conference, 2004. doi:10.1109/milcom.2004.1494952Misic, J., Misic, V. B., & Shafi, S. (s. f.). Performance of IEEE 802.15.4 beacon enabled PAN with uplink transmissions in non-saturation mode - access delay for finite buffers. First International Conference on Broadband Networks. doi:10.1109/broadnets.2004.61Mišić, J., Shafi, S., & Mišić, V. B. (2005). The impact of MAC parameters on the performance of 802.15.4 PAN. Ad Hoc Networks, 3(5), 509-528. doi:10.1016/j.adhoc.2004.08.002Anastasi, G., Conti, M., & Di Francesco, M. (2011). A Comprehensive Analysis of the MAC Unreliability Problem in IEEE 802.15.4 Wireless Sensor Networks. IEEE Transactions on Industrial Informatics, 7(1), 52-65. doi:10.1109/tii.2010.2085440Lee, B.-H., Al Rasyid, M. U. H., & Wu, H.-K. (2012). Analysis of superframe adjustment and beacon transmission for IEEE 802.15.4 cluster tree networks. EURASIP Journal on Wireless Communications and Networking, 2012(1). doi:10.1186/1687-1499-2012-219Zimmerling, M., Ferrari, F., Mottola, L., Voigt, T., & Thiele, L. (2012). pTunes. Proceedings of the 11th international conference on Information Processing in Sensor Networks - IPSN ’12. doi:10.1145/2185677.2185730Rohm, D., Goyal, M., Hosseini, H., Divjak, A., & Bashir, Y. (2009). Configuring Beaconless IEEE 802.15.4 Networks Under Different Traffic Loads. 2009 International Conference on Advanced Information Networking and Applications. doi:10.1109/aina.2009.84Jin-Shyan Lee. (2006). Performance evaluation of IEEE 802.15.4 for low-rate wireless personal area networks. IEEE Transactions on Consumer Electronics, 52(3), 742-749. doi:10.1109/tce.2006.1706465De Paz Alberola, R., & Pesch, D. (2012). Duty cycle learning algorithm (DCLA) for IEEE 802.15.4 beacon-enabled wireless sensor networks. Ad Hoc Networks, 10(4), 664-679. doi:10.1016/j.adhoc.2011.06.006Barbieri, A., Chiti, F., & Fantacci, R. (2006). WSN17-2: Proposal of an Adaptive MAC Protocol for Efficient IEEE 802.15.4 Low Power Communications. IEEE Globecom 2006. doi:10.1109/glocom.2006.989Jeon, J., Lee, J. W., Ha, J. Y., & Kwon, W. H. (2007). DCA: Duty-Cycle Adaptation Algorithm for IEEE 802.15.4 Beacon-Enabled Networks. 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring. doi:10.1109/vetecs.2007.35Kang, M., Chong, J., Hyun, H., Kim, S., Jung, B., & Sung, D. (2007). Adaptive Interference-Aware Multi-Channel Clustering Algorithm in a ZigBee Network in the Presence of WLAN Interference. 2007 2nd International Symposium on Wireless Pervasive Computing. doi:10.1109/iswpc.2007.342601Yi, P., Iwayemi, A., & Zhou, C. (2011). Developing ZigBee Deployment Guideline Under WiFi Interference for Smart Grid Applications. IEEE Transactions on Smart Grid, 2(1), 110-120. doi:10.1109/tsg.2010.2091655Tang, L., Wang, K.-C., Huang, Y., & Gu, F. (2007). Channel Characterization and Link Quality Assessment of IEEE 802.15.4-Compliant Radio for Factory Environments. IEEE Transactions on Industrial Informatics, 3(2), 99-110. doi:10.1109/tii.2007.898414Sha M Xing G Zhou G Liu S Wang X C-MAC: model-driven concurrent medium access control for wireless sensor networks IEEE INFOCOM 2009 Rio de Janeiro, Brazil 2009 1845 1853 10.1109/INFCOM.2009.5062105Peizhong Yi, Iwayemi, A., & Chi Zhou. (2010). Frequency agility in a ZigBee network for smart grid application. 2010 Innovative Smart Grid Technologies (ISGT). doi:10.1109/isgt.2010.5434747Torabi N Wong W Leung VCM A robust coexistence scheme for IEEE 802.15.4 wireless personal area networks IEEE Consumer Communications and Networking Conference (CCNC) Las Vegas, U.S. 2011 1031 1035 10.1109/CCNC.2011.5766322IEEE standard for local and metropolitan area networks - part 15.6: wireless body area networks IEEE Std 802.15.6-2012 2012 1 271 10.1109/IEEESTD.2012.6161600Kim, S., Kim, S., Kim, J.-W., & Eom, D.-S. (2012). Flexible beacon scheduling scheme for interference mitigation in body sensor networks. 2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON). doi:10.1109/secon.2012.6275772Bradai N Fourati LC Kamoun L Performance analysis of medium access control protocol for wireless body area networks 27th International Conference on Advanced Information Networking and Applications Workshops (WAINA) Barcelona, Spain 2013 916 921Moravejosharieh A Yazdi ET Study of resource utilization in IEEE 802.15.4 wireless body sensor network, part I: the need for enhancement IEEE 16th International Conference on Computational Science and Engineering (CSE) Sydney, Australia 2013 1226 1231Moravejosharieh A Yazdi ET Willig A Study of resource utilization in IEEE 802.15.4 wireless body sensor network, part II: greedy channel utilization 19th IEEE International Conference on Networks (ICON) Singapore 2013 1 6Moravejosharieh A Yazdi E Willig A Pawlikowski K Adaptive channel utilisation in IEEE 802.15.4 wireless body sensor networks: continuous hopping approach Australasian Telecommunication Networks and Applications Conference (ATNAC) Melbourne, Australia 2014 93 98 10.1109/ATNAC.2014.7020880Moravejosharieh, A. H. (2015). Frequency-Adaptive Approach In IEEE 802.15.4 Wireless Body Sensor Networks: Continuous-Assessment or Periodic-Assessment? International Journal of Information, Communication Technology and Applications, 1(1), 19. doi:10.17972/ajicta2015113Moravejosharieh A Yazdi E Pawlikowski K Sirisena H Adaptive channel utilisation in IEEE 802.15.4 wireless body sensor networks: adaptive phase-shifting approach International Telecommunication Networks and Applications Conference (ITNAC) Sydney, Australia 2015 93 98Bian, K., Park, J.-M., & Gao, B. (2014). Channel Assignment for Multi-hop Cognitive Radio Networks. Cognitive Radio Networks, 101-116. doi:10.1007/978-3-319-07329-3_6Bian, K., Park, J.-M., & Gao, B. (2014). Coexistence-Aware Spectrum Sharing for Homogeneous Cognitive Radio Networks. 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    AnaVANET: an experiment and visualization tool for vehicular networks

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    International audienceThe experimental evaluation of wireless and mobile networks is a challenge that rarely substitutes simulation in research works. This statement is even more evident in vehicular communications, due to the equipment and effort needed to obtain significant and realistic results. In this paper, key issues in vehicular experimental evaluation are analyzed by an evaluation tool called AnaVANET, especially designed for assessing the performance of vehicular networks. This software processes the output of well-known testing tools such as ping or iperf, together with navigation information, to generate geo-aware performance figures of merit both in numeric and graphical forms. Its main analysis capabilities are used to validate the good performance in terms of delay, packet delivery ratio and throughput of NEMO, when using a road-side segment based on IPv6 GeoNetworking
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