In underwater sensor network(UWSN) research, it is highly expensive to deploy a complete test bed involving complex network structure and data links to validate a network protocol or an algorithm. This practical challenge points to the need of a simulation environment which can reproduce the actual underwater scenario without the loss of generality. Since so many simulators are proposed for UWSN simulation, the selection of an appropriate tool based on the research requirement is very important in validation and interpretation of results. This paper provides an in-depth survey of different simulation tools available for UWSN simulation. We compared the features offered by each tool, pre-requirements, and provide the run time experiences of some of the open source tools. We conducted simulation of sample scenarios in some of the open source tools and compared the results. This survey helps a researcher to identify a simulation tool satisfying their specific research requirements.
Underwater sensor networks (UWSN) provide a promising solution for several aquatic applications. Mobile UWSNs are vulnerable to various threats because of their harsh environment, acoustic communication channel, bandwidth limitation, high propagation delay, multipath effect, and mobility. Therefore, appropriate security mechanisms should be included in networking services, such as localization, to facilitate time critical applications. In this paper, we discuss various Denial-of-Service attacks in mobile UWSNs. We simulated a flooding attack and an out-of-coverage problem caused by mobility by using Aqua-Sim, and analyzed their impact on UWSN performance. In addition, we surveyed UWSN localization techniques and secure localization schemes of terrestrial wireless sensor networks (WSN). Simulation experiments were conducted to analyze the performance variation between mobile UWSNs and mobile WSNs. The study concluded that the variation in the network performance of mobile UWSNs varies from that of WSNs. Therefore, the security mechanisms proposed for terrestrial WSNs are unsuitable for UWSNs.
Underwater acoustic sensor network (UASN) offers a promising solution for exploring underwater resources remotely. For getting a better understanding of sensed data, accurate localization is essential. As the UASN acoustic channel is open and the environment is hostile, the risk of malicious activities is very high, particularly in time-critical military applications. Since the location estimation with false data ends up in wrong positioning, it is necessary to identify and ignore such data to ensure data integrity. Therefore, in this paper, we propose a novel anomaly detection system for UASN localization. To minimize computational power and storage, we designed separate anomaly detection schemes for sensor nodes and anchor nodes. We propose an auto-regressive prediction-based scheme for detecting anomalies at sensor nodes. For anchor nodes, a fuzzy inference system is designed to identify the presence of anomalous behavior. The detection schemes are implemented at every node for enabling identification of multiple and duplicate anomalies at its origin. We simulated the network, modeled anomalies and analyzed the performance of detection schemes at anchor nodes and sensor nodes. The results indicate that anomaly detection systems offer an acceptable accuracy with high true positive rate and F-Score.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.