A Fuzzy Congestion Control Protocol Based on Active Queue Management in Wireless Sensor Networks with Medical Applications

Wireless Personal Communications - Tập 98 - Trang 815-842 - 2017
Abbas Ali Rezaee1, Faezeh Pasandideh2
1Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran
2Science and Research Branch, Islamic Azad University, Tehran, Iran

Tóm tắt

Wireless Sensor Network has been widely used in a variety of applications such as; medical, agriculture, military, monitoring environment and so on. In healthcare wireless sensor networks, sensors which are placed on specific parts of the patient’s body, detect patient’s vital signs and transmit them to a medical center. As a matter of fact, too many of these sensors begin to simultaneously send the information congestion which is likely to happen in a network. In other words, when the sensors on the patient’s body are constantly sending data packets, the congestion is more likely to happen. This could result in an increase of packet loss ratio and thus efficiency decreases and it affects the overall performance of the system, In this regard, so the congestion control is a major challenge. Congestion detection and control are essential for such systems. In this protocol a new active queue management method is proposed to determine packet loss probability. The proposed AQM integrates the random early detection and fuzzy proportional integral derivative (FuzzyPID) controller methods together. When fuzzy logic combines with PID, it helps to control the target buffer queue. A fuzzy logical controller also estimates and adjusts the sending rate of each node. With the help of OPNET simulator and MATLAB, we compared this proposed protocol with Priority-based Congestion Control protocol and Optimized Congestion management protocol protocols, and simulation results suggest that the proposed protocol performs better than other approaches regarding aspects such as data loss rate and end-to-end delay.

Tài liệu tham khảo

Khanafer, M., Guennoun, M., & Mouftah, H. T. (2010). Intrusion detection system for WSN-based intelligent transportation systems. In Global telecommunications conference (GLOBECOM 2010), 2010 IEEE (pp. 1–6). IEEE. doi: 10.1109/GLOCOM.2010.5683730.

Han, K., Luo, J., Liu, Y., & Vasilakos, A. V. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine, 51(7), 107–113. doi:10.1109/MCOM.2013.6553686.

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. doi:10.1002/dac.3098

Maiti, P., Sahoo, B., Turuk, A. K., & Satpathy, S. (2017). Sensors data collection architecture in the internet of mobile things as a service (IoMTaaS) platform.

Ee, C.T., & Bajcsy, R. Congestion control and fairness for many-to-one routing in sensor networks. In Proceedings of the 2nd international conference on embedded networked sensor systems. 2004. ACM. doi:10.1145/1031495.1031513.

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. doi:10.1109/jsac.2007.070514.

Misra, S., Tiwari, V., & Obaidat, M. S. (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.

Samiullah, M., S. Abdullah, & Anwar, S. (2012). Queue management based congestion control in wireless body sensor network. In Informatics, electronics & vision (ICIEV), 2012 international conference on. 2012. IEEE. doi:10.1109/iciev.2012.6317349.

Chuan, Z., & Xuejiao, L., A robust AQM algorithm based on fuzzy-inference. In Measuring technology and mechatronics automation, 2009. ICMTMA’09. international conference on (Vol. 2, pp. 534–537). IEEE. doi: 10.1109/ICMTMA.2009.520.

Rezaee, A. A., Yaghmaee, M. H., & Rahmani, A. M. (2013). COCM: Class based optimized congestion management protocol for healthcare. Wireless Sensor Networks, 5, 137.