An Efficient Congestion Avoidance Scheme for Mobile Healthcare Wireless Sensor Networks

Wireless Sensor Networks (WSN) in healthcare environment continuously monitors critically ailing patients. Congestion is one of the major challenges in WSN; it causes overall channel quality to degrade, loss rates to raise, leads to buffer drops and increased delays, and tends to be grossly unfair toward nodes whose data has to traverse a larger number of radio hops. Congestion avoidance deserves first place in healthcare environment. The problem of congestion in the nodes of healthcare WSN is addressed using a Learning Automata (LA).The Learning Automata Based Congestion Avoidance Scheme (LACAS) can counter the congestion problem efficiently. LACAS intelligently learns from the past and improves its performance significantly as time progresses awnd it is suitable only for stationary environments. Mobile healthcare provides accessible services that are welcoming to homeless people who cannot go to fixed-site clinics, so that mobility for nodes in healthcare WSN is needed. Congestion avoidance in mobile healthcare WSN is addressed by implementing LACAS in the nodes.