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Optimized Path Selection in Oceanographic Environment

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Innovations in Bio-Inspired Computing and Applications (IBICA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 939))

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Abstract

Wireless sensor networks (WSN) react to events in specified circumstances by sensing, computing and communicating with thousands of sensors arranged at different locations operating in different modes. Typical applications include, but are not limited to, data collection, military operations, surveillance, and medical telemetry. The sensors are battery powered devices and hence their lifetime is very limited. It may not be possible to recharge or replace the battery depending upon the application environment. Communication overhead has to be reduced because energy is a very valuable resource for these sensor nodes. Long distance communication among sensors will cause large amount of energy drain which may reduce the lifetime of the network. In this work we propose Genetic Algorithm (GA) and Gravitational Search based methods to address sensor network optimization problem. The GA, GSA and PSO based clustering of WSN can greatly minimize the total communication distance, thus lengthening the network lifespan. Kerala, on the west coast of India, holds a vital role in India’s fishing industry that gives a sustainable steady income. A new technique based on WSN technology using GA, GSA and PSO methods has been presented in this paper which helps to provide protection to the fishermen while they are in the deep sea. The results obtained from the proposed work shows that the network optimization based on cluster head using GSA has better performance and less energy consumption than the network without clustering.

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Correspondence to N. V. Sobhana .

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Sobhana, N.V., Rahul Raj, M., Gayatri Menon, B., Sherly, E. (2019). Optimized Path Selection in Oceanographic Environment. In: Abraham, A., Gandhi, N., Pant, M. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2018. Advances in Intelligent Systems and Computing, vol 939. Springer, Cham. https://doi.org/10.1007/978-3-030-16681-6_50

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