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Farzaneh Bahalgardi, N., Yaghmaee, M., Adjeroh, D. (2012). An Adaptive Congestion Alleviating Protocol for Healthcare Applications in Wireless Body Sensor Networks: Learning Automata Approach. AUT Journal of Electrical Engineering, 44(1), 31-41. doi: 10.22060/eej.2012.38
Nazbanoo Farzaneh Bahalgardi; Mohammad Hossein Yaghmaee; Donald Adjeroh. "An Adaptive Congestion Alleviating Protocol for Healthcare Applications in Wireless Body Sensor Networks: Learning Automata Approach". AUT Journal of Electrical Engineering, 44, 1, 2012, 31-41. doi: 10.22060/eej.2012.38
Farzaneh Bahalgardi, N., Yaghmaee, M., Adjeroh, D. (2012). 'An Adaptive Congestion Alleviating Protocol for Healthcare Applications in Wireless Body Sensor Networks: Learning Automata Approach', AUT Journal of Electrical Engineering, 44(1), pp. 31-41. doi: 10.22060/eej.2012.38
Farzaneh Bahalgardi, N., Yaghmaee, M., Adjeroh, D. An Adaptive Congestion Alleviating Protocol for Healthcare Applications in Wireless Body Sensor Networks: Learning Automata Approach. AUT Journal of Electrical Engineering, 2012; 44(1): 31-41. doi: 10.22060/eej.2012.38

An Adaptive Congestion Alleviating Protocol for Healthcare Applications in Wireless Body Sensor Networks: Learning Automata Approach

Article 3, Volume 44, Issue 1, Winter and Spring 2012, Page 31-41  XML PDF (687 K)
Document Type: Research Article
DOI: 10.22060/eej.2012.38
Authors
Nazbanoo Farzaneh Bahalgardi1; Mohammad Hossein Yaghmaee; Donald Adjeroh2
1Nazbanoo Farzaneh. Computer Engineering Department, Ferdowsi University of Mashhad, Azadi Square, Mashhad, IRAN. (email: Farzaneh@stu-mail.um.ac.ir)
2Donald Adjeroh, Full Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506 (email: don@csee.wvu.edu)
Abstract
Wireless Body Sensor Networks (WBSNs) involve a convergence of biosensors, wireless communication and networks technologies. WBSN enables real-time healthcare services to users. Wireless sensors can be used to monitor patients’ physical conditions and transfer real time vital signs to the emergency center or individual doctors. Wireless networks are subject to more packet loss and congestion. To alleviate congestion, the source transmission rate and node arrival rate should be controlled.  In this paper, we propose Learning based Congestion Control Protocol (LCCP) for wireless body sensor networks.  LCCP joins active queue management and rate adjustment mechanism to alleviate congestion. The proposed system is able to discriminate different physiological signals and assign them different priorities. Thus, it would be possible to provide better quality of service for transmitting highly important vital signs. The simulation results confirm that the proposed protocol improves system throughput and reduces delay and packet dropping. We also evaluate the performance of the AQM mechanism with no rate adjustment mechanism to show the advantage of using both AQM and rate adjustment mechanism together. 
Keywords
Active Queue Management; Congestion Control; Learning Automata; Transport protocol; Wireless Body Sensor Network
References

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