Wireless Body Area Networks ( Wbans )

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Abstract — Wireless Body Area Networks (WBANs) are a boon to today’s society. The WBANs find their use in wide variety of fields starting from medical to sports to military. However the main concern for WBANs is their energy efficiency that in turn illustrates the network longevity. Many different algorithms have been employed for this purpose. In this paper we are going to enhance the energy efficiency of our WBAN network by using Neural Network (NN) along with the Genetic algorithm (GA). The neural network will provide the fitness value for our body node coordinator (BNC node that provides the entire data from the sensor nodes deployed on the body to the PC or laptop of the specialist) at a much faster rate and hence this data could be utilized by the Genetic algorithm to generalize the BNC’s location. It could be seen that the optimized placement of BNC leads to the increased energy efficiency of the network which in turn makes the network more dependable and steady. As the energy proficiency upsurges, so does the depletion time which in turn, escalates the network lifetime to a great percentage. Index Terms —Body node coordinator (BNC), energy efficiency, genetic algorithm, node deployment, neural network, wireless body area networks (WBANs).

In WBANs the sensor nodes are deployed on the human body that transmits information from the different parts of the body to the main coordinator node (BNC) that converges the information to the concerned
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