In recent years industry’s pursuit of Underwater Wireless Sensor Networks (UWSN) has surged because of UWSN’s advancements in commercial and military applications as well as monitoring marine life. Owing to its capabilities, open acoustic channel, and hostile undersea environment, additionally, it is susceptible to many different types of malicious attacks and threats. Although secure interaction and communication is necessary for many UWSN-based applications, attackers can readily exploit vulnerabilities to steal data while the application is in use. However, most of UWSN research to date has not taken security into account. Due to these factors, the objective of this research is to present a thorough review of UWSN security by going over security requirements as well as the primary UWSN security threats according to layered classification. This paper discusses different security concerns and examines countermeasure schemes against UWSN security attacks and strategies created specifically for UWSNs that discuss several security issues. The aim of this study is to discusses several security challenges and examines countermeasure schemes against UWSN security attacks and strategies created specifically for UWSNs that discuss several security issues. The goal of this study is to recommend future lines of inquiry for UWSN research. The proposed study discusses different strategies that had already addressed the security issues. However, how these schemes are still lacking in the performance and what countermeasures can be considered by different techniques in order to fulfill the security issues in under water sensors networks. The goal of this study is to recommend future lines of inquiry for UWSN research. Comparisons of different techniques in terms of energy efficiency, latency, and detection accuracy with other major factors have also done as a guide line for new researchers.

In this study, an effort to synchronize and localize the underwater sensors simultaneously in a multi-hop environment is considered. Underwater Sensor Networks (UWSNs) has limited range and connectivity due to propagation delay and limited bandwidth. By using a multi-hop environment, we can extend the range and enhancing the network connectivity for providing more accurate localization and synchronization technique. We have established a connection between sensors point to point directed links and then analytically construct the model for the synchronization as a function of range, delay, and timestamps. Secondly, we have formulated the unconstrained optimization problem for localization by using a gradient technique. The proposed research scheme first synchronizes and then localizes the unknown nodes with known depth by using the single anchor node in a multi-hop scenario. According to the literature survey, this joint effort has never been addressed before; both localization and time synchronization for multi-hop scenarios are addressed separately. The proposed algorithm will also calculate the propagation delay that will be generated during message propagation for both localization and time synchronization. The numerical results are compared with some well-known techniques in terms of the number of nodes, localization error, synchronization error, total processing time up to four hops. Experimental results show that the proposed model outperforms in terms of localization and synchronization accuracy, but since this work has never been done before therefore, we compare our results with the techniques that had separately address this problem having some constraints.

In underwater wireless sensor networks (UWSNs), localization and time synchronization are vital services that have been tackled independently. By combining localization and time synchronization, could save nodes energy and improve accuracy jointly. Therefore, it is of great significance to study joint synchronization and localization of underwater sensors with low energy consumption. In this paper, we propose the energy-efficient joint framework of localization and time synchronization, in which the stratification effect is considered by using a ray-tracing approach. Based on Snell’s law, ray tracing is applied to compensate for the variation of sound speed, this is one of the contributions of this article. Another contribution of this article is the iteration process which is used to improve the accuracy of localization and time synchronization. Simulation results show that the proposed joint approach outperforms the existing approaches in both energy efficiency and accuracy. This study also calculates Cramer-Rao lower bound to prove the convergence of the proposed technique along with the calculation of complexity of the proposed algorithm to show that the provided study takes less running time compared to the existing techniques.

Wireless Sensor Networks (WSNs) are commonly used in various pervasive applications. Wireless communication is the fastest growing segment of the communication industry that has captured attention of the media and imagination of the public. The purpose of this study is to develop a Genetic algorithm that provides a proper deployment of sensors in order to optimize the coverage problem. The genetic algorithm optimizes the operational modes of sensors nodes for transmitting signals. In this paper we will present the optimum method for the mobile sensors nodes placement, so that transmission of signals and the field coverage can be improved. One of the critical issues of today’s world is to ensure that the quality of services requirement is at an acceptable level and genetic algorithm give the best solution for the above discussed problem. The algorithm has been implemented in MATLAB using its genetic algorithm tool box along with the custom code.

Wireless Sensor Networks (WSNs) are commonly used in various pervasive applications. Wireless communication is the fastest growing segment of the communication industry that has captured attention of the media and imagination of the public. The purpose of this study is to develop a Genetic algorithm that provides a proper deployment of sensors in order to optimize the coverage problem. The genetic algorithm optimizes the operational modes of sensors nodes for transmitting signals. In this paper we will present the optimum method for the mobile sensors nodes placement, so that transmission of signals and the field coverage can be improved. One of the critical issues of today’s world is to ensure that the quality of services requirement is at an acceptable level and genetic algorithm give the best solution for the above discussed problem. The algorithm has been implemented in MATLAB using its genetic algorithm tool box along with the custom code.