Wireless body area network is a type of wireless sensor network that enables efficient healthcare system. To minimize frequent sensor replacement due to resource restrictions, it is necessary to improve energy efficiency in wireless body area network. This article deals with energy efficiency and quality-of-service improvement together in novel wireless body area network architecture. A novel wireless body area network architecture is designed with dual sink nodes in order to minimize delay and energy consumption. A novel insistence-aware medium access control protocol which is aware of criticality of sensed data is presented in the proposed wireless body area network. Prior knowledge-based weighted routing algorithm is responsible to select optimal route for data transmission. In prior knowledge-based weighted routing, weight value is computed by considering significant metrics such as residual energy, link stability, distance, and delay in order to improve energy efficiency and quality of service in the network. Energy consumption is further minimized by incorporating graph-based sleep scheduling algorithm. In graph-based sleep scheduling, criticality of sensor node is also considered as major metric. In coordinator, split and map–based neural network classifier is involved to perform packet classification. After classification, packets are assigned to corresponding sink node according to packet type. Then, throughput and delay metrics are improved by frame aggregation process which is involved in sink node. Extensive simulation in OMNeT++ shows better performance in network lifetime, throughput, residual energy, dropped packets, and delay.
Packet Size Optimization for Energy Efficiency in Multipath Fading for Wireless Body Area Network
