A Review on Dynamic Buffer Traffic Condition Protocol in Telemedicine
DOI:
https://doi.org/10.35806/ijoced.v4i2.247Keywords:
Adaptive wake-up interval, Buffer traffic condition, Cluster head, Sink node, Transmitter nodeAbstract
Various MAC-protocol has been adopted over the years in Telemedicine, also known as Wireless Body Area Network system (WBANs), to enhance the proper transmission of the busy congestion of data message. However, these techniques could not coordinate traffic congestion in the receiver node, which could make the receiver nodes experience an "active mode" most of the time compared to the transmit node. This is dangerous to the network system because of uncontrollable energy usage. In this protocol, the intelligent sensor is strategically located around or implanted in the human body for the collection of human body physiological parameters. WBANs experienced some limitations such as latency and excessive consumption of energy which may hinder the lifetime maximization of the system if not taken care of properly. In this work, four elements are responsible for carrying-out only traffic data, and they are implemented by using the highest priority sensor nodes within a short period used for communicating to the Buffer Traffic Condition (BTC) discussed and the traffic measurement to mitigate active-mode interval in the receiving phase of the improved superframe structure of IEEE 802.15.6. Furthermore, meaningful information about the superframe to mitigate the busy traffic and enhance this protocol was also discussed as its possible functions with the help of an adaptive system. No article depicts the analysis of the work on the dynamic buffer traffic condition scheme, and this proposed scheme can improve on the existing one.
References
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Choi, J. S., & Kim, J. G. (2014). An energy efficient MAC protocol for WBAN through flexible frame structure. Information (Japan), 17(6 A). https://doi.org/10.14257/astl.2013.41.02
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Dong, C., & Yu, F. (2017). A prediction-based asynchronous MAC protocol for heavy traffic load in wireless sensor networks. AEU - International Journal of Electronics and Communications, 82. https://doi.org/10.1016/j.aeue.2017.09.003
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Li, H., & Tan, J. (2010). Heartbeat-driven medium-access control for body sensor networks. IEEE Transactions on Information Technology in Biomedicine, 14(1). https://doi.org/10.1109/TITB.2009.2028136
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Manzoor, B., Javaid, N., Bibi, A., Khan, Z. A., & Tahir, M. (2012). Noise filtering, channel modeling and energy utilization in wireless body area networks. Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012. https://doi.org/10.1109/HPCC.2012.264
Marinković, S. J., Popovici, E. M., Spagnol, C., Faul, S., & Marnane, W. P. (2009). Energy-efficient low duty cycle MAC protocol fo wireless body area networks. IEEE Transactions on Information Technology in Biomedicine, 13(6). https://doi.org/10.1109/TITB.2009.2033591
Matthew Iyobhebhe., Aliyu D Usman., A. M. S. Tekany., Ezekiel Ehimen Agbon., (2022). Hop- Count Aware Body Area network for Effective Data Transmission. Indonesian Journal of Computing, Engineering, and Design (IJOCED) 4(1), 47-56.
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Nguyen, V.-T., Gautier, M., & Berder, O. (2014). Implementation of an adaptive energy-efficient MAC protocol in OMNeT++/MiXiM. CAIRN - Energy Efficient Computing Architectures with Embedded Reconfigurable Resources. https://hal.archives-ouvertes.fr/hal-01070701
Pegatoquet, A., Le, T. N., & Magno, M. (2019). A Wake-Up Radio-Based MAC Protocol for Autonomous Wireless Sensor Networks. IEEE/ACM Transactions on Networking, 27(1). https://doi.org/10.1109/TNET.2018.2880797
Qureshi, K. N., Bashir, M. U., Lloret, J., & Leon, A. (2020). Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision. Journal of Sensors, 2020. https://doi.org/10.1155/2020/9040395
Qureshi, K. N., Idrees, M. M., Lloret, J., & Bosch, I. (2020). Self-Assessment Based Clustering Data Dissemination for Sparse and Dense Traffic Conditions for Internet of Vehicles. IEEE Access, 8. https://doi.org/10.1109/ACCESS.2020.2964530
Rahim, A., Javaid, N., Aslam, M., Qasim, U., & Khan, Z. A. (2012). Adaptive-reliable medium access control protocol for wireless body area networks. Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops, 1. https://doi.org/10.1109/SECON.2012.6275829
Rezvani, S. (2012). A Novel WBAN MAC protocol with Improved Energy Consumption and Data Rate. KSII Transactions on Internet and Information Systems. https://doi.org/10.3837/tiis.2012.09.019
Salayma, M., Al-Dubai, A., Romdhani, I., & Nasser, Y. (2017). Wireless Body Area Network (WBAN): A survey on reliability, fault tolerance, and technologies coexistence. ACM Computing Surveys, 50(1). https://doi.org/10.1145/3041956
Shu, M., Yuan, D., Zhang, C., Wang, Y., & Chen, C. (2015). A MAC protocol for medical monitoring applications of wireless body area networks. Sensors (Switzerland), 15(6). https://doi.org/10.3390/s150612906
Siddiqui, S., Ghani, S., & Khan, A. A. (2018). ADP-MAC: An adaptive and dynamic polling-based MAC protocol for wireless sensor networks. IEEE Sensors Journal, 18(2). https://doi.org/10.1109/JSEN.2017.2771397
Song, L., & Hatzinakos, D. (2007). A cross-layer architecture of wireless sensor networks for target tracking. IEEE/ACM Transactions on Networking, 15(1). https://doi.org/10.1109/TNET.2006.890084
Sun, P., Li, G., & Wang, F. (2017). An adaptive back-off mechanism for wireless sensor networks. Future Internet, 9(2). https://doi.org/10.3390/fi9020019
Tachtatzis, C., Di Franco, F., Tracey, D. C., Timmons, N. F., & Morrison, J. (2012). An energy analysis of IEEE 802.15.6 scheduled access modes for medical applications. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 89 LNICST. https://doi.org/10.1007/978-3-642-29096-1_15
Venkateswari, R., Rani, S. S., & Meeravali, S. K. A. (2015). A robust MAC protocol for wireless body sensor network. Journal of Scientific and Industrial Research, 74(6).
Ye, D., & Au, M. Z. (2018). A Self-Adaptive Sleep/Wake-Up Scheduling Approach for Wireless Sensor Networks. IEEE Transactions on Cybernetics, 48(3). https://doi.org/10.1109/TCYB.2017.2669996
Yessad, N., Omar, M., Tari, A., & Bouabdallah, A. (2018). QoS-based routing in Wireless Body Area Networks: a survey and taxonomy. Computing, 100(3). https://doi.org/10.1007/s00607-017-0575-4
Zhang, D. Gan, Zhou, S., & Tang, Y. Meng. (2018). A Low Duty Cycle Efficient MAC Protocol Based on Self-Adaption and Predictive Strategy. Mobile Networks and Applications, 23(4). https://doi.org/10.1007/s11036-017-0878-x
Alam, M. M., Hamida, E. Ben, Berder, O., Menard, D., & Sentieys, O. (2016). A Heuristic Self-Adaptive Medium Access Control for Resource-Constrained WBAN Systems. IEEE Access, 4. https://doi.org/10.1109/ACCESS.2016.2539299
Anwar, M., Abdullah, A. H., Altameem, A., Qureshi, K. N., Masud, F., Faheem, M., Cao, Y., & Kharel, R. (2018). Green communication for wireless body area networks: Energy aware link efficient routing approach. Sensors (Switzerland), 18(10). https://doi.org/10.3390/s18103237
Awan, K., Qureshi, K. N., & Mehwish. (2016). Wireless body area networks routing protocols: A review. In Indonesian Journal of Electrical Engineering and Computer Science (Vol. 4, Issue 3). https://doi.org/10.11591/ijeecs.v4.i3.pp594-604
Cai, X., Li, J., Yuan, J., Zhu, W., & Wu, Q. (2015). Energy-aware adaptive topology adjustment in wireless body area networks. Telecommunication Systems, 58(2). https://doi.org/10.1007/s11235-014-9899-y
Cai, X., Yuan, J., Yuan, X., Zhu, W., Li, J., Li, C., & Ullah, S. (2013). Energy-efficient relay MAC with dynamic power control in wireless body area networks. KSII Transactions on Internet and Information Systems, 7(7). https://doi.org/10.3837/tiis.2013.07.002
Choi, J. S., & Kim, J. G. (2014). An energy efficient MAC protocol for WBAN through flexible frame structure. Information (Japan), 17(6 A). https://doi.org/10.14257/astl.2013.41.02
Dinh, T., Kim, Y., Gu, T., & Vasilakos, A. V. (2018). An adaptive low-power listening protocol for wireless sensor networks in noisy environments. IEEE Systems Journal, 12(3). https://doi.org/10.1109/JSYST.2017.2720781
Dong, C., & Yu, F. (2017). A prediction-based asynchronous MAC protocol for heavy traffic load in wireless sensor networks. AEU - International Journal of Electronics and Communications, 82. https://doi.org/10.1016/j.aeue.2017.09.003
Esteves, V., Antonopoulos, A., Kartsakli, E., Puig-Vidal, M., Miribel-Català , P., & Verikoukis, C. (2015). Cooperative energy harvesting-adaptive MAC protocol for WBANs. Sensors (Switzerland), 15(6). https://doi.org/10.3390/s150612635
Fujimoto, A., Masui, Y., & Yoshihiro, T. (2018). Scheduling beacon transmission to improve delay for receiver-initiated-MAC based wireless sensor networks. Journal of Information Processing, 26. https://doi.org/10.2197/ipsjjip.26.140
Hasan, K., Biswas, K., Ahmed, K., Nafi, N. S., & Islam, M. S. (2019). A comprehensive review of wireless body area network. In Journal of Network and Computer Applications (Vol. 143). https://doi.org/10.1016/j.jnca.2019.06.016
Jovanov, E., Milenkovic, A., Otto, C., & De Groen, P. C. (2005). A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. Journal of Neuro Engineering and Rehabilitation, 2. https://doi.org/10.1186/1743-0003-2-6
Jung, B. H., Akbar, R. U., & Sung, D. K. (2012). Throughput, energy consumption, and energy efficiency of IEEE 802.15.6 body area network (BAN) MAC protocol. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC. https://doi.org/10.1109/PIMRC.2012.6362852
Kim, R. H., Kim, P. S., & Kim, J. G. (2015). An effect of delay reduced MAC protocol for WBAN based medical signal monitoring. IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings, 2015-November. https://doi.org/10.1109/PACRIM.2015.7334876
Kirbas, I., Karahan, A., Sevin, A., & Bayilmis, C. (2013). isMAC: An adaptive and energy-efficient MAC protocol based on multi-channel communication for wireless body area networks. KSII Transactions on Internet and Information Systems, 7(8). https://doi.org/10.3837/tiis.2013.08.004
Li, H., & Tan, J. (2010). Heartbeat-driven medium-access control for body sensor networks. IEEE Transactions on Information Technology in Biomedicine, 14(1). https://doi.org/10.1109/TITB.2009.2028136
Maman, M., Miras, D., & Ouvry, L. (2013). Implementation of a self-organizing, adaptive, flexible and ultra - low-power MAC protocol for wireless Body Area Networks. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC. https://doi.org/10.1109/PIMRC.2013.6666423
Manzoor, B., Javaid, N., Bibi, A., Khan, Z. A., & Tahir, M. (2012). Noise filtering, channel modeling and energy utilization in wireless body area networks. Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012. https://doi.org/10.1109/HPCC.2012.264
Marinković, S. J., Popovici, E. M., Spagnol, C., Faul, S., & Marnane, W. P. (2009). Energy-efficient low duty cycle MAC protocol fo wireless body area networks. IEEE Transactions on Information Technology in Biomedicine, 13(6). https://doi.org/10.1109/TITB.2009.2033591
Matthew Iyobhebhe., Aliyu D Usman., A. M. S. Tekany., Ezekiel Ehimen Agbon., (2022). Hop- Count Aware Body Area network for Effective Data Transmission. Indonesian Journal of Computing, Engineering, and Design (IJOCED) 4(1), 47-56.
Mohamed, M., Joseph, W., Vermeeren, G., Tanghe, E., & Cheffena, M. (2019). Characterization of Off-Body Area Network Channels during Walking. International Symposium on Medical Information and Communication Technology, ISMICT, 2019-May. https://doi.org/10.1109/ISMICT.2019.8743848
Nguyen, V.-T., Gautier, M., & Berder, O. (2014). Implementation of an adaptive energy-efficient MAC protocol in OMNeT++/MiXiM. CAIRN - Energy Efficient Computing Architectures with Embedded Reconfigurable Resources. https://hal.archives-ouvertes.fr/hal-01070701
Pegatoquet, A., Le, T. N., & Magno, M. (2019). A Wake-Up Radio-Based MAC Protocol for Autonomous Wireless Sensor Networks. IEEE/ACM Transactions on Networking, 27(1). https://doi.org/10.1109/TNET.2018.2880797
Qureshi, K. N., Bashir, M. U., Lloret, J., & Leon, A. (2020). Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision. Journal of Sensors, 2020. https://doi.org/10.1155/2020/9040395
Qureshi, K. N., Idrees, M. M., Lloret, J., & Bosch, I. (2020). Self-Assessment Based Clustering Data Dissemination for Sparse and Dense Traffic Conditions for Internet of Vehicles. IEEE Access, 8. https://doi.org/10.1109/ACCESS.2020.2964530
Rahim, A., Javaid, N., Aslam, M., Qasim, U., & Khan, Z. A. (2012). Adaptive-reliable medium access control protocol for wireless body area networks. Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops, 1. https://doi.org/10.1109/SECON.2012.6275829
Rezvani, S. (2012). A Novel WBAN MAC protocol with Improved Energy Consumption and Data Rate. KSII Transactions on Internet and Information Systems. https://doi.org/10.3837/tiis.2012.09.019
Salayma, M., Al-Dubai, A., Romdhani, I., & Nasser, Y. (2017). Wireless Body Area Network (WBAN): A survey on reliability, fault tolerance, and technologies coexistence. ACM Computing Surveys, 50(1). https://doi.org/10.1145/3041956
Shu, M., Yuan, D., Zhang, C., Wang, Y., & Chen, C. (2015). A MAC protocol for medical monitoring applications of wireless body area networks. Sensors (Switzerland), 15(6). https://doi.org/10.3390/s150612906
Siddiqui, S., Ghani, S., & Khan, A. A. (2018). ADP-MAC: An adaptive and dynamic polling-based MAC protocol for wireless sensor networks. IEEE Sensors Journal, 18(2). https://doi.org/10.1109/JSEN.2017.2771397
Song, L., & Hatzinakos, D. (2007). A cross-layer architecture of wireless sensor networks for target tracking. IEEE/ACM Transactions on Networking, 15(1). https://doi.org/10.1109/TNET.2006.890084
Sun, P., Li, G., & Wang, F. (2017). An adaptive back-off mechanism for wireless sensor networks. Future Internet, 9(2). https://doi.org/10.3390/fi9020019
Tachtatzis, C., Di Franco, F., Tracey, D. C., Timmons, N. F., & Morrison, J. (2012). An energy analysis of IEEE 802.15.6 scheduled access modes for medical applications. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 89 LNICST. https://doi.org/10.1007/978-3-642-29096-1_15
Venkateswari, R., Rani, S. S., & Meeravali, S. K. A. (2015). A robust MAC protocol for wireless body sensor network. Journal of Scientific and Industrial Research, 74(6).
Ye, D., & Au, M. Z. (2018). A Self-Adaptive Sleep/Wake-Up Scheduling Approach for Wireless Sensor Networks. IEEE Transactions on Cybernetics, 48(3). https://doi.org/10.1109/TCYB.2017.2669996
Yessad, N., Omar, M., Tari, A., & Bouabdallah, A. (2018). QoS-based routing in Wireless Body Area Networks: a survey and taxonomy. Computing, 100(3). https://doi.org/10.1007/s00607-017-0575-4
Zhang, D. Gan, Zhou, S., & Tang, Y. Meng. (2018). A Low Duty Cycle Efficient MAC Protocol Based on Self-Adaption and Predictive Strategy. Mobile Networks and Applications, 23(4). https://doi.org/10.1007/s11036-017-0878-x
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2022-10-03
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A Review on Dynamic Buffer Traffic Condition Protocol in Telemedicine (M. Iyobhebhe, A. Adikpe, J. G. Bashayi, A. C. Akezi, I. C. Botson, E. Chukwudi, & O. B. Akinyele , Trans.). (2022). Indonesian Journal of Computing, Engineering, and Design (IJoCED), 4(2), 15-24. https://doi.org/10.35806/ijoced.v4i2.247
