A Novel Congestion Avoidance Technique for
Simultaneous Real-Time Medical Data Transmission
Abstract— The use of Wireless Body Sensor Networks (WBSN) in medical services aims at providing continuous monitoring of patients’ physiological data. However, the scarce resources in WBSN nodes limit their capabilities to cope with massive trafﬁc during multiple, simultaneous data transmissions. This will create a high tendency for congestion, causing severe performance degradation. Congestion may lead to high number of packet loss and unbounded delay which are critical and may lead to wrong diagnosis. This paper therefore, aims at improving this limitation using a novel congestion avoidance technique to avoid losing real-time and life-critical medical data (e.g. Electrocardiogram (ECG) and electroencephalography (EEG)) which are vital for diagnosis. The main idea is to integrate the existing rate control scheme of Relaxation Theory (RT) with a method known as Max-Min Fairness < Final Year Projects 2016 > MMF to achieve better performance. The MMF can be accomplished using a Progressive Filling algorithm, which cuts-down excessive sending rates that may overwhelmed the limited buffer in WBSN. This paper builds upon our prior work, which provides a preliminary analysis of RT technique in single node. Our current technique integrates the MMF phase to enhance RT performance when the transmission rates exceed certain threshold. Performance evaluation on RT-MMF technique shows remarkable performance improvements, while maintaining the desired Quality of Service (QoS).
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