Learning automata: an introduction
Learning automata: an introduction
IEEE Transactions on Computers
RCRT: rate-controlled reliable transport for wireless sensor networks
Proceedings of the 5th international conference on Embedded networked sensor systems
Computer Networks: The International Journal of Computer and Telecommunications Networking
LACAS: learning automata-based congestion avoidance scheme for healthcare wireless sensor networks
IEEE Journal on Selected Areas in Communications - Special issue on wireless and pervasive communications for healthcare
Wireless Personal Communications: An International Journal
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Wireless Body Sensor Network (WBSN) consists of a large number of distributed sensor nodes. Wireless sensor networks are offering the next evolution in biometrics and healthcare monitoring applications. The present paper proposes a congestion control protocol based on the learning automata which prevents the congestion by controlling the source rate. Furthermore, a new active queue management mechanism is developed. The main objective of the proposed active queue management mechanism is to control and manage the entry of each packet to sensor nodes based on learning automata. 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.