Journal of Ocean Engineering and Science

Volume 4, Issue 4

(3)Minimizing transmission loss using inspired ant colony optimization and Markov Chain Monte Carlo in underwater WSN environment

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Raj Priyadarshini R ^∗, Sivakumar N

Department of Computer Science and Engineering, Pondicherry Engineering College, East Coast Road, Pillaichavadi, Puducherry 605014, India

Received 22 March 2019; received in revised form 21 May 2019; accepted 21 May 2019

Available online 27 May 2019

Abstract

In Underwater Wireless Sensor Networks (UWSNs), the most important challenging issues are propagation delay, high error probability, high latency, high communication cost, limited bandwidth, limited memory, low packet delivery ratio, and transmission loss. In our proposed work, the various efforts are taken to minimize the propagation delay and transmission loss during data transmission in an underwater environment. A hybrid mechanism is implemented to improve energy efﬁciency for faster data transmission in underwater WSN. In the underwater environment of acoustic channel condition, propagation delay and transmission loss lead to high complexity in accessing the information and also it is difﬁcult to obtain the Channel Status Information (CSI). To address this problem, Ant Colony Optimization (ACO) routing with Markov Chain Monte Carlo (MCMC) algorithm is used and to capture the transmission loss in the MCMC approach, CSI Forecast Prediction (FP) algorithm is used. The experimental simulations are evaluated by utilizing the performance evaluation metrics such as Transmission Loss, Probability Density Function, Average Delay and Throughput. From the simulation results it is evident that the proposed algorithm, ACO-MCMC has recorded the minimum transmission loss, increase in probability density function, minimum average delay and maximum throughput of the network when compared to the existing algorithms.

This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Keywords: UWSN; ACO-MCMC; CSI; Markov Chain Monte Carlo; Transmission loss; Probability density function.