Minimizing End-to-End Delay and Maximizing Reliability using Multilayer Neural Network-based Hamming Back Propagation for Efficient Communication in WSN

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A. Pagalavan
B. Senthilkumar
R. Senthilnathan

Abstract

Wireless sensor network (WSN) comprises number of spatially distributed sensor nodes for monitoring the physical environment conditions and arranging the gathered data at central location. WSN gained large attention in medical field, industry, military, etc. However, congestion control mechanism for communication between sensor nodes failed to consider the end-to-end delay features. In addition, it failed to handle reliability and not achieved the data concurrency. In order to address the above mentioned problems, Multilayer Neural Network-based Hamming Back Propagation (MNN-HBP) technique is introduced for efficient communication in WSN. In MNN-HBP technique, Amorphous View Point Algorithm is introduced for sensor node initialization for efficient communication in WSN. Amorphous View Point Algorithm used time of arrival to measure the time distance between the sender node and receiver node. After that Hamming Back Propagation Algorithm is used to identify the current location of the sensor nodes for minimizing the end-to end delay and improving the reliability. Each sensor node compares their distance with the neighbouring sensor nodes distance to identify the associated error. When the distance is higher, the associated error is higher and propagates error back to other sensor nodes in the previous layers. The process gets repeated until the communication established between source sensor and lower associated error nodes. By this way, efficient communication is carried out with higher reliability and minimum end-to end delay. Extensive simulation are conducted to illustrate the efficiency of proposed technique as well as the impacts of network parameters on end-to-end delay, reliability and data packets successful rate with respect to data packet size and number of data packets.

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