807 research outputs found

    Effect of Packet Inter-arrival Time on the Energy Consumption of Beacon Enabled MAC Protocol for Body Area Networks

    Get PDF
    AbstractOne of the major concerns for the development of Wireless Body Area Network (WBAN) is to increase the network lifetime. IEEE 802.15.4 standard for Medium Access Control (MAC) layer can be used for energy efficient and reliable transmission by modifying the different control parameters. Such a modification is very difficult, because an accurate model for the influence of these control parameters of minimum energy and delay is not available. Moreover, there is no mechanism available how to adopt and implement these parameters that can implement on the Body Nodes (BNs). In this paper, we provide the mechanism for emergency data along with normal and periodic data by modifying the superframe structure. Coordinator transmits and extra beacon upon the request of emergency data. A comprehensive analysis of energy consumption of BNs including the affect of packet inter-arrival time is given in this paper. Analysis show that, Contention Access Period (CAP) of superframe is not feasible for emergency data due to its extra delay and energy

    A Study of Medium Access Control Protocols for Wireless Body Area Networks

    Get PDF
    The seamless integration of low-power, miniaturised, invasive/non-invasive lightweight sensor nodes have contributed to the development of a proactive and unobtrusive Wireless Body Area Network (WBAN). A WBAN provides long-term health monitoring of a patient without any constraint on his/her normal dailylife activities. This monitoring requires low-power operation of invasive/non-invasive sensor nodes. In other words, a power-efficient Medium Access Control (MAC) protocol is required to satisfy the stringent WBAN requirements including low-power consumption. In this paper, we first outline the WBAN requirements that are important for the design of a low-power MAC protocol. Then we study low-power MAC protocols proposed/investigated for WBAN with emphasis on their strengths and weaknesses. We also review different power-efficient mechanisms for WBAN. In addition, useful suggestions are given to help the MAC designers to develop a low-power MAC protocol that will satisfy the stringent WBAN requirements.Comment: 13 pages, 8 figures, 7 table

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

    Full text link
    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. Brown L Grundlehner B Gyselinckx B Van Hoof C Potential and challenges of body area networks for personal health Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC Minneapolis, U.S. 2009 6569 6572Ullah, S., Higgins, H., Braem, B., Latre, B., Blondia, C., Moerman, I., … Kwak, K. S. (2010). A Comprehensive Survey of Wireless Body Area Networks. Journal of Medical Systems, 36(3), 1065-1094. doi:10.1007/s10916-010-9571-3Cao, H., Leung, V., Chow, C., & Chan, H. (2009). Enabling technologies for wireless body area networks: A survey and outlook. IEEE Communications Magazine, 47(12), 84-93. doi:10.1109/mcom.2009.5350373Hall, P. S., Yang Hao, Nechayev, Y. I., Alomainy, A., Constantinou, C. C., Parini, C., … Bozzetti, M. (2007). Antennas and propagation for on-body communication systems. IEEE Antennas and Propagation Magazine, 49(3), 41-58. doi:10.1109/map.2007.4293935Mamaghanian, H., Khaled, N., Atienza, D., & Vandergheynst, P. (2011). Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes. IEEE Transactions on Biomedical Engineering, 58(9), 2456-2466. doi:10.1109/tbme.2011.2156795LAN-MAN Standards Committee the IEEE Computer Society IEEE standard for local and metropolitan area networks - part 15.4: low rate wireless personal area networks (LR-WPANs) 2011Petrova M Riihijarvi J Mahonen P Labella S Performance study of IEEE 802.15.4 using measurements and simulations IEEE Wireless Communications and Networking Conference (WCNC) Las Vegas, U.S. 2006 487 492Vaithiyanathan, J., Raju, R. K., & Sadayan, G. (2011). Performance Evaluation of IEEE 802.15.4 Using Association Process and Channel Measurement. Communications in Computer and Information Science, 409-417. doi:10.1007/978-3-642-22555-0_42Yazdi E Moravejosharieh A Willig A Pawlikowski K Coupling power and frequency adaptation for interference mitigation in IEEE 802.15.4-based mobile body sensor networks: part II 2014 Australasian Telecommunication Networks and Applications Conference (ATNAC) Melbourne, Australia 2014 105 110Pelegris P Banitsas K Investigating the efficiency of IEEE 802.15.4 for medical monitoring applications 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC Boston, U.S. 2011 8215 8218Ranjit, J. S., & Shin, S. (2013). A Modified IEEE 802.15.4 Superframe Structure for Guaranteed Emergency Handling in Wireless Body Area Network. Network Protocols and Algorithms, 5(2), 1. doi:10.5296/npa.v5i2.3375Jianliang Zheng, & Lee, M. J. (2004). Will IEEE 802.15.4 make ubiquitous networking a reality?: a discussion on a potential low power, low bit rate standard. 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. Cognitive Radio Networks, 61-75. doi:10.1007/978-3-319-07329-3_4Wu C Yan H Huo H A multi-channel MAC protocol design based on IEEE 802.15.4 standard in industry 2012 10th IEEE International Conference on Industrial Informatics (INDIN) Beijing, China 2012 1206 1211 10.1109/INDIN.2012.6300916Incel, O. D. (2011). A survey on multi-channel communication in wireless sensor networks. Computer Networks, 55(13), 3081-3099. doi:10.1016/j.comnet.2011.05.020Kim Y Shin H Cha H Y-MAC: an energy-efficient multi-channel MAC protocol for dense wireless sensor networks Proceedings of the 7th International Conference on Information Processing in Sensor Networks IPSN '08 St. Louis MO, U.S. 2008 53 63Demirkol, I., Ersoy, C., & Alagoz, F. (2006). MAC protocols for wireless sensor networks: a survey. IEEE Communications Magazine, 44(4), 115-121. doi:10.1109/mcom.2006.1632658Wykret T Correia L Macedo D Giacomin J Andrade L Evaluation and avoidance of interference in WSN: a multi-radio node prototype using dynamic spectrum allocation IFIP Wireless Days (WD) Valencia, Spain 2013 1 3 10.1109/WD.2013.6686533Doyle L Sutton P Nolan K Lotze J Ozgul B Rondeau T Fahmy S Lahlou H DaSilva L Experiences from the IRIS testbed in dynamic spectrum access and cognitive radio experimentation IEEE Symposium on New Frontiers in Dynamic Spectrum Singapore 2010 1 8 10.1109/DYSPAN.2010.5457835Ansari, J., Zhang, X., & Mahonen, P. (2010). Multi-radio medium access control protocol for wireless sensor networks. International Journal of Sensor Networks, 8(1), 47. doi:10.1504/ijsnet.2010.034066Liu Z Wu W A dynamic multi-radio multi-channel MAC protocol for wireless sensor networks 2nd International Conference on Communication Software and Networks (ICCSN) Singapore 2010 105 109Xu, W., Trappe, W., & Zhang, Y. (2008). Defending wireless sensor networks from radio interference through channel adaptation. ACM Transactions on Sensor Networks, 4(4), 1-34. doi:10.1145/1387663.1387664Kim Y Shin H Cha H Y-MAC: an energy-efficient multi-channel MAC protocol for dense wireless sensor networks Proceedings of the 7th IEEE Computer Society International Conference on Information Processing in Sensor Networks IPSN '08 Washington, DC, USA 2008 53 63Tae Hyun Kim, Jae Yeol Ha, & Sunghyun Choi. (2009). Improving Spectral and Temporal Efficiency of Collocated IEEE 802.15.4 LR-WPANs. IEEE Transactions on Mobile Computing, 8(12), 1596-1609. doi:10.1109/tmc.2009.85Chowdhury, K. R., Nandiraju, N., Chanda, P., Agrawal, D. P., & Zeng, Q.-A. (2009). Channel allocation and medium access control for wireless sensor networks. Ad Hoc Networks, 7(2), 307-321. doi:10.1016/j.adhoc.2008.03.004Deylami, M., & Jovanov, E. (2012). A distributed and collaborative scheme for mitigating coexistence in IEEE 802.15.4 based WBANs. Proceedings of the 50th Annual Southeast Regional Conference on - ACM-SE ’12. doi:10.1145/2184512.2184514Deylami, M. N., & Jovanov, E. (2014). A Distributed Scheme to Manage The Dynamic Coexistence of IEEE 802.15.4-Based Health-Monitoring WBANs. IEEE Journal of Biomedical and Health Informatics, 18(1), 327-334. doi:10.1109/jbhi.2013.2278217Deylami M Jovanov E An implementation of a distributed scheme for managing the dynamic coexistence of wireless body area networks Southeastcon, 2013 Proceedings of IEEE Jacksonville, U.S. 2013 1 6 10.1109/SECON.2013.6567446Cavallari, R., Martelli, F., Rosini, R., Buratti, C., & Verdone, R. (2014). A Survey on Wireless Body Area Networks: Technologies and Design Challenges. IEEE Communications Surveys & Tutorials, 16(3), 1635-1657. doi:10.1109/surv.2014.012214.00007Chen, M., Gonzalez, S., Vasilakos, A., Cao, H., & Leung, V. C. M. (2010). Body Area Networks: A Survey. Mobile Networks and Applications, 16(2), 171-193. doi:10.1007/s11036-010-0260-8Movassaghi, S., Abolhasan, M., Lipman, J., Smith, D., & Jamalipour, A. (2014). Wireless Body Area Networks: A Survey. IEEE Communications Surveys & Tutorials, 16(3), 1658-1686. doi:10.1109/surv.2013.121313.00064Patel, M., & Wang, J. (2010). Applications, challenges, and prospective in emerging body area networking technologies. IEEE Wireless Communications, 17(1), 80-88. doi:10.1109/mwc.2010.5416354ULLAH, S., KHAN, P., ULLAH, N., SALEEM, S., HIGGINS, H., & Sup KWAK, K. (2009). A Review of Wireless Body Area Networks for Medical Applications. International Journal of Communications, Network and System Sciences, 02(08), 797-803. doi:10.4236/ijcns.2009.28093Boulis, A., Smith, D., Miniutti, D., Libman, L., & Tselishchev, Y. (2012). Challenges in body area networks for healthcare: the MAC. IEEE Communications Magazine, 50(5), 100-106. doi:10.1109/mcom.2012.6194389Pantelopoulos A Bourbakis N A survey on wearable biosensor systems for health monitoring 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vancouver, Canada 2008 4887 4890 10.1109/IEMBS.2008.4650309Takei, K., Honda, W., Harada, S., Arie, T., & Akita, S. (2014). Toward Flexible and Wearable Human-Interactive Health-Monitoring Devices. Advanced Healthcare Materials, 4(4), 487-500. doi:10.1002/adhm.201400546Caldeira, J. M. L. P., Rodrigues, J. J. P. C., & Lorenz, P. (2013). Intra-Mobility Support Solutions for Healthcare Wireless Sensor Networks–Handover Issues. IEEE Sensors Journal, 13(11), 4339-4348. doi:10.1109/jsen.2013.2267729Carrano, R. C., Passos, D., Magalhaes, L. C. S., & Albuquerque, C. V. N. (2014). Survey and Taxonomy of Duty Cycling Mechanisms in Wireless Sensor Networks. IEEE Communications Surveys & Tutorials, 16(1), 181-194. doi:10.1109/surv.2013.052213.00116Sudevalayam, S., & Kulkarni, P. (2011). Energy Harvesting Sensor Nodes: Survey and Implications. IEEE Communications Surveys & Tutorials, 13(3), 443-461. doi:10.1109/surv.2011.060710.00094Khanafer, M., Guennoun, M., & Mouftah, H. T. (2014). A Survey of Beacon-Enabled IEEE 802.15.4 MAC Protocols in Wireless Sensor Networks. IEEE Communications Surveys & Tutorials, 16(2), 856-876. doi:10.1

    Adaptive parameters adjustment in WBAN to mitigate Wi-Fi interferences

    Get PDF
    Wireless Body Area Network (WBAN), called also Wireless Body Sensor Network (WBSN), is composed of a set of tiny wireless devices (sensors) attached, implanted or ingested into the body. It offers real time and ubiquitous applications thanks to the small form, the lightness, and the wireless interface of sensors. WBAN performance is expected to be considerably degraded in the presence of Wi-Fi networks. Their operating channels overlap in the 2.4 GHz Industrial Scientific and Medical (ISM) band which produces interference when they transmit data, accompanied by data losses and quick battery exhaustion. Therefore, it is crucial to mitigate the interference between WBAN and Wi-Fi networks in order to maintain the efficiency and the reliability of the WBAN system. Proposals in the literature use an added complex hardware in WBAN system, or perform the exchange of additional information, or establish expensive communications, or affect the quality of service of the WBAN. Unlike previous researches, we proposed simple, low cost and dynamic method that adaptively adjusts specific parameters in the Medium Access Control (MAC) layer. We have proved the effectiveness of our approach based on theoretical analysis and simulation using MiXiM framework of OMNet++ simulato

    Energy-aware medium access control protocols for wireless sensors network applications

    Get PDF
    The main purpose of this thesis was to investigate energy efficient Medium Access Control (MAC) protocols designed to extend the lifetime of a wireless sensor network application, such as tracking, environment monitoring, home security, patient monitoring, e.g., foetal monitoring in the last weeks of pregnancy. From the perspective of communication protocols, energy efficiency is one of the most important issues, and can be addressed at each layer of the protocol stack; however, our research only focuses on the medium access control (MAC) layer. An energy efficient MAC protocol was designed based on modifications and optimisations for a synchronized power saving Sensor MAC (SMAC) protocol, which has three important components: periodic listen and sleep, collision and overhearing avoidance and message passing. The Sensor Block Acknowledgement (SBACK) MAC protocol is proposed, which combines contention-based, scheduling-based and block acknowledgement-based schemes to achieve energy efficiency. In SBACK, the use of ACK control packets is reduced since it will not have an ACK packet for every DATA packet sent; instead, one special packet called Block ACK Response will be used at the end of the transmission of all data packets. This packet informs the sender of how many packets were received by the receiver, reducing the number of ACK control packets we intended to reduce the power consumption for the nodes. Hence more useful data packets can be transmitted. A comparison study between SBACK and SMAC protocol is also performed. Considering 0% of packet losses, SBACK decreases the energy consumption when directly compared with S-MAC, we will have always a decrease of energy consumption. Three different transceivers will be used and considering a packet loss of 10% we will have a decrease of energy consumption between 10% and 0.1% depending on the transceiver. When there are no retransmissions of packets, SBACK only achieve worst performance when the number of fragments is less than 12, after that the decrease of average delay increases with the increase of the fragments sent. When 10% of the packets need retransmission only for the TR1000 transceiver worst results occurs in terms of energy waste, all other transceivers (CC2420 and AT86RF230) achieve better results. In terms of delay if we need to retransmit more than 10 packets the SBACK protocol always achieves better performance when comparing with the other MAC protocols that uses ACK

    Wireless sensor network for health monitoring

    Get PDF
    Wireless Sensor Network (WSN) is becoming a significant enabling technology for a wide variety of applications. Recent advances in WSN have facilitated the realization of pervasive health monitoring for both homecare and hospital environments. Current technological advances in sensors, power-efficient integrated circuits, and wireless communication have allowed the development of miniature, lightweight, low-cost, and smart physiological sensor nodes. These nodes are capable of sensing, processing, and communicating one or more vital signs. Furthermore, they can be used in wireless personal area networks (WPANs) or wireless body sensor networks (WBSNs) for health monitoring. Many studies were performed and/or are under way in order to develop flexible, reliable, secure, real-time, and power-efficient WBSNs suitable for healthcare applications. To efficiently control and monitor a patient’s status as well as to reduce the cost of power and maintenance, IEEE 802.15.4/ZigBee, a communication standard for low-power wireless communication, is developed as a new efficient technology in health monitoring systems. The main contribution of this dissertation is to provide a modeling, analysis, and design framework for WSN health monitoring systems. This dissertation describes the applications of wireless sensor networks in the healthcare area and discusses the related issues and challenges. The main goal of this study is to evaluate the acceptance of the current wireless standard for enabling WSNs for healthcare monitoring in real environment. Its focus is on IEEE 802.15.4/ZigBee protocols combined with hardware and software platforms. Especially, it focuses on Carrier Sense Multiple Access with Collision Avoidance mechanism (CSMA/CA) algorithms for reliable communication in multiple accessing networks. The performance analysis metrics are established through measured data and mathematical analysis. This dissertation evaluates the network performance of the IEEE 802.15.4 unslotted CSMA/CA mechanism for different parameter settings through analytical modeling and simulation. For this protocol, a Markov chain model is used to derive the analytical expression of normalized packet transmission, reliability, channel access delay, and energy consumption. This model is used to describe the stochastic behavior of random access and deterministic behavior of IEEE 802.15.4 CSMA/CA. By using it, the different aspects of health monitoring can be analyzed. The sound transmission of heart beat with other smaller data packet transmission is studied. The obtained theoretical analysis and simulation results can be used to estimate and design the high performance health monitoring systems

    A novel energy-safe algorithm for enhancing the battery life for IoT sensors applications

    Get PDF
    Energy safe is mandatory for all isolated IoT tools, as in long way roads, mountains, or even in smart cities. If increasing the lifetime of these tools, the rentability of the global network loop becomes more efficient. Therefore, this paper's base main is to present a new approach for saving energy inside the source nods by supervising the state of energy inside each source nod and calculating the duty cycle factor. The relationship between these parameters is based on an optimization problem formulation. In this respect, the present paper is designed to propose a new approach that deals with increasing the lifetime of the Wireless Sensors Network (WSN) attached nodes, as fixed in the application. The newly devised design rests on implementing the IEEE 802.15.4 standard beacon-enabled mode, involving a cluster tree topology. Accordingly, every subgroup is allotted to apply a specifically different duty cycle, depending on the battery's remaining energy level, which contributes to creating a wide range of functional modes. Hence, various thresholds are defined. Simulation results are proving the efficiency of the proposed approach and show the energetic benefit. The proposed flowchart has minimized the consumed energy for the WSN, which improve the battery lifetime and enhance the IoT applications robustness. Simulations and experiments have been carried out under different conditions and the results proved that the proposed method is a viable solution.publishedVersio

    Efficient GTS Allocation Schemes for IEEE 802.15.4

    Get PDF
    IEEE 802.15.4 is a standard defined for wireless sensor network applications with limited power and relaxed throughput needs. The devices transmit data during two periods: Contention Access Period (CAP) by accessing the channel using CSMA/CA and Contention Free Period (CFP), which consists of Guaranteed Time Slots (GTS) allocated to individual devices by the network coordinator. The GTS is used by devices for cyclic data transmission and the coordinator can allocate GTS to a maximum of only seven devices. In this work, we have proposed two algorithms for an efficient GTS allocation. The first algorithm is focused on improving the bandwidth utilization of devices, while the second algorithm uses traffic arrival information of devices to allow sharing of GTS slots between more than seven devices. The proposed schemes were tested through simulations and the results show that the new GTS allocation schemes perform better than the original IEEE 802.15.4 standard

    Energy-Efficiency Analysis of a Distributed Queuing Medium Access Control Protocol for Biomedical Wireless Sensor Networks in Saturation Conditions

    Get PDF
    The aging population and the high quality of life expectations in our society lead to the need of more efficient and affordable healthcare solutions. For this reason, this paper aims for the optimization of Medium Access Control (MAC) protocols for biomedical wireless sensor networks or wireless Body Sensor Networks (BSNs). The hereby presented schemes always have in mind the efficient management of channel resources and the overall minimization of sensors’ energy consumption in order to prolong sensors’ battery life. The fact that the IEEE 802.15.4 MAC does not fully satisfy BSN requirements highlights the need for the design of new scalable MAC solutions, which guarantee low-power consumption to the maximum number of body sensors in high density areas (i.e., in saturation conditions). In order to emphasize IEEE 802.15.4 MAC limitations, this article presents a detailed overview of this de facto standard for Wireless Sensor Networks (WSNs), which serves as a link for the introduction and initial description of our here proposed Distributed Queuing (DQ) MAC protocol for BSN scenarios. Within this framework, an extensive DQ MAC energy-consumption analysis in saturation conditions is presented to be able to evaluate its performance in relation to IEEE 802.5.4 MAC in highly dense BSNs. The obtained results show that the proposed scheme outperforms IEEE 802.15.4 MAC in average energy consumption per information bit, thus providing a better overall performance that scales appropriately to BSNs under high traffic conditions. These benefits are obtained by eliminating back-off periods and collisions in data packet transmissions, while minimizing the control overhead
    corecore