Abstract
A wireless sensor network (WSN) consists of sensor nodes and base stations which are connected via wireless medium. A key functionality of WSNs consists in collecting information from sensor nodes & transporting the information of interest to the base stations required by the applications. Wireless connectivity, size and low cost of sensors in WSNs are its advantages which enable it to be deployed in hostile or inaccessible environments at a very low cost. However, WSNs suffer from high data loss due to error prone wireless transmission medium, transmission problems in hostile environments and node failures due to limited energy of sensor nodes. Hence reliable data transportation i.e. ensuring data delivery with minimum loss becomes the key issue in WSNs. The amount of loss tolerated is application dependent. This paper presents an artificial neural network based model for reliable data transportation in Wireless Sensor Networks (WSNs). This work increases the reliability of information transportation despite of corrupted signal sensed at the sensors and thus is an attempt to design a fault tolerant WSN.
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