Abstract
The application of Wireless Sensor Networks (WSNs) in healthcare is dominant and fast growing. In healthcare WSN applications (HWSNs) such as medical emergencies, the network may encounter an unpredictable load which leads to congestion. Congestion problem which is common in any data network including WSN, leads to packet loss, increasing end-to-end delay and excessive energy consumption due to retransmission. In modern wireless biomedical sensor networks, increasing these two parameters for the packets that carry EKG signals may even result in the death of the patient. Furthermore, when congestion occurs, because of the packet loss, packet retransmission increases accordingly. The retransmission directly affects the lifetime of the nodes. In this paper, an Optimized Congestion management protocol is proposed for HWSNs when the patients are stationary. This protocol consists of two stages. In the first stage, a novel Active Queue Management (AQM) scheme is proposed to avoid congestion and provide quality of service (QoS). This scheme uses separate virtual queues on a single physical queue to store the input packets from each child node based on importance and priority of the source’s traffic. If the incoming packet is accepted, in the second stage, three mechanisms are used to control congestion. The proposed protocol detects congestion by a three-state machine and virtual queue status; it adjusts the child’s sending rate by an optimization function. We compare our proposed protocol with CCF, PCCP and backpressure algorithms using the OPNET simulator. Simulation results show that the proposed protocol is more efficient than CCF, PCCP and backpressure algorithms in terms of packet loss, energy efficiency, end-to-end delay and fairness.
Similar content being viewed by others
References
Vieira, M. A. M., Coelho, C. N., Jr., da Silva, D. C., Jr., & da Mata, J. M. (2003). Survey on wireless sensor network devices. In Emerging technologies and factory automation, 2003. Proceedings. ETFA ’03. IEEE conference, September 16–19, 2003 (Vol. 1, pp. 537–544, vol. 531). doi:10.1109/etfa.2003.1247753.
Alemdar, H., & Ersoy, C. (2010). Wireless sensor networks for healthcare: A survey. Computer Networks, 54(15), 2688–2710. doi:10.1016/j.comnet.2010.05.003.
Boulis, A., Smith, D., Miniutti, D., Libman, L., & Tselishchev, Y. (2012). Challenges in body area networks for healthcare: The MAC. Communications Magazine, IEEE, 50(5), 100–106. doi:10.1109/mcom.2012.6194389.
Baker, C. R., Armijo, K., & Wright, P. K. (2007). Wireless sensor networks for home health care. Paper presented at the proceedings of the 21st international conference on advanced information networking and applications workshops—Volume 02.
Dishongh, T. J., & McGrath, M. E. (2010). Wireless sensor networks for healthcare applications. London: Artech House.
Zhao, W., Ning, S., & Liu, L. (2011). Wireless sensor networks for in-home healthcare: Issues, trend and prospect. In International conference on computer science and network technology (ICCSNT), 2011, December 24–26, 2011 (Vol. 2, pp. 970–973). doi:10.1109/iccsnt.2011.6182123.
Darwish, A., & Hassanien, A. E. (2012). Correction: Darwish, A. and Hassanien, A.E. Wearable and implantable wireless sensor network solutions for healthcare monitoring [published erratum]. Sensors (Basel), 12(9), 12375–12376. doi:10.3390/s120912375.
Chen, B., & Pompili, D. (2011). Transmission of patient vital signs using wireless body area networks. Mobile Networks and Applications, 16(6), 663–682. doi:10.1007/s11036-010-0253-7.
Lo, B., Atallah, L., Aziz, O., ElHew, M., Darzi, A., & Yang, G.-Z. (2007). Real-time pervasive monitoring for postoperative care. In S. Leonhardt, T. Falck & P. Mähönen (Eds.), 4th international workshop on wearable and implantable body sensor networks (BSN 2007) (Vol. 13, pp. 122–127, IFMBE proceedings). Berlin: Springer.
Tia, G., Massey, T., Selavo, L., Crawford, D., Bor-rong, C., Lorincz, K., et al. (2007). The advanced health and disaster aid network: A light-weight wireless medical system for triage. IEEE Transactions on Biomedical Circuits and Systems, 1(3), 203–216. doi:10.1109/tbcas.2007.910901.
Wang, C., Li, B., Sohraby, K., Daneshmand, M., & Hu, Y. (2007). Upstream congestion control in wireless sensor networks through cross-layer optimization. IEEE Journal on Selected Areas in Communications, 25(4), 786–795. doi:10.1109/jsac.2007.070514.
Ee, C. T., & Bajcsy, R. (2004). Congestion control and fairness for many-to-one routing in sensor networks. Paper presented at the proceedings of the 2nd international conference on embedded networked sensor systems, Baltimore, MD, USA.
Chonggang, W., Sohraby, K., Bo, L., Daneshmand, M., & Yueming, H. (2006). A survey of transport protocols for wireless sensor networks. Network, IEEE, 20(3), 34–40. doi:10.1109/mnet.2006.1637930.
Rathnayaka, A. J. D., & Potdar, V. M. (2013). Wireless sensor network transport protocol: A critical review. Journal of Network and Computer Applications, 36(1), 134–146, doi:10.1016/j.jnca.2011.10.001.
Yaghmaee, M. H., & Adjeroh, D. A. (2009). Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks. Computer Networks, 53(11), 1798–1811. doi:10.1016/j.comnet.2009.02.011.
Wan, C.-Y., Eisenman, S. B., & Campbell, A. T. (2003). CODA: Congestion detection and avoidance in sensor networks. Paper presented at the proceedings of the 1st international conference on embedded networked sensor systems, Los Angeles, California, USA.
Xiaoyan, Y., Xingshe, Z., Rongsheng, H., Yuguang, F., & Shining, L. (2009). A fairness-aware congestion control scheme in wireless sensor networks. IEEE Transactions on Vehicular Technology, 58(9), 5225–5234. doi:10.1109/tvt.2009.2027022.
Misra, S., Tiwari, V., & Obaidat, M. (2009). LACAS: Learning automata-based congestion avoidance scheme for healthcare wireless sensor networks. Selected Areas in Communications, IEEE Journal on, 27(4), 466–479. doi:10.1109/jsac.2009.090510.
Tao, L., & Yu, F. (2009). ECODA: Enhanced congestion detection and avoidance for multiple class of traffic in sensor networks. Paper presented at the proceedings of the 15th Asia-Pacific conference on communications, Shanghai, China.
Samimi, M., Rezaee, A., & Yaghmaee, M. H. (2012). Design a new fuzzy congestion controller in wireless sensor networks. International Journal of Information and Electronics Engineering, 2(3), 395–399. doi:10.7763/IJIEE.2012.V2.123.
Esmailpour, B., Rezaee, A., & Abad, J. (2010). Congestion avoidance and energy efficient routing protocol for WSN healthcare applications. In T.-H. Kim, T. Vasilakos, K. Sakurai, Y. Xiao, G. Zhao, & D. Śløgonezak (Eds.), Communication and networking (Vol. 120, pp. 1–10, Communications in Computer and Information Science). Berlin: Springer.
Yaghmaee, M. H., & Adjeroh, D. (2008). A new priority based congestion control protocol for wireless multimedia sensor networks. In International symposium on a world of wireless, mobile and multimedia networks, WoWMoM 2008, June 23–26, 2008, pp. 1–8. doi:10.1109/wowmom.2008.4594816.
Yaghmaee, M., Bahalgardi, N., & Adjeroh, D. (2013). A prioritization based congestion control protocol for healthcare monitoring application in wireless sensor networks. Wireless Personal Communications, 1–27. doi:10.1007/s11277-013-1169-x.
Brahma, S., Chatterjee, M., Kwiat, K., & Varshney, P. K. (2012). Traffic management in wireless sensor networks: Decoupling congestion control and fairness. Computer Communications, 35(6), 670–681. doi:10.1016/j.comcom.2011.09.014.
Rezaee, A. A., Yaghmaee, M. H., & Rahmani, A. M. (December 2011). Class based congestion control method for healthcare wireless sensor networks. International Geoinformatics Research and Development Journal, 2(4).
Samiullah, M., Abdullah, S. M., Bappi, A. F. M. I. H., & Anwar, S. (2012). Queue management based congestion control in wireless body sensor network. In International conference on informatics, electronics and vision (ICIEV), 2012, May 18–19, 2012 (pp. 493–496). doi:10.1109/iciev.2012.6317349.
Kunniyur, S. S., & Srikant, R. (2004). An adaptive virtual queue (AVQ) algorithm for active queue management. IEEE/ACM Transactions on Networking, 12(2), 286–299. doi:10.1109/tnet.2004.826291.
Firoiu, V., & Borden, M. (2000). A study of active queue management for congestion control. In INFOCOM 2000. Nineteenth annual joint conference of the IEEE computer and communications societies Proceedings. IEEE, March 26–30, 2000 (Vol. 3, pp. 1435–1444, vol. 1433). doi:10.1109/infcom.2000.832541.
Wang, H., Liao, C., & Tian, Z. (2011). Effective adaptive virtual queue: A stabilising active queue management algorithm for improving responsiveness and robustness. Communications, IET, 5(1), 99–109. doi:10.1049/iet-com.2009.0700.
Reddy, T. B., & Ahammed, A. (2008). Performance comparison of active queue management techniques. Journal of Computer Science, 4(12), 1020–1023. doi:10.3844/jcssp.2008.1020.1023.
Chen, W., Fan, X.-L., & Zhang, J. (2012). An adaptive BLUE algorithm for active queue management. Paper presented at the proceedings of the 2012 international conference on electronics, communications and control.
Narendra, K.S., & Thathachar, M. A. L. (1989). Learning automata—an introduction. Englewood Cliffs, NJ: Prentice Hall.
Gross, D., Shortle, J. F., Thompson, J. M., & Harris, C. M. (2008). Fundamentals of queueing theory. London : Wiley-Interscience.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Rezaee, A.A., Yaghmaee, M.H. & Rahmani, A.M. Optimized Congestion Management Protocol for Healthcare Wireless Sensor Networks. Wireless Pers Commun 75, 11–34 (2014). https://doi.org/10.1007/s11277-013-1337-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-013-1337-z