Abstract

The Internet of Things (IoT) is a network of devices that interact with the physical environment and communicate with each other over the Internet, requiring little or no human interaction. IoT applications are present in many fields ranging from mining and exploration to security and surveillance. This arguably, is the second Internet revolution. For traditional internet applications, the wireless channel is the main communication medium. IoT networked applications, however, can be deployed in different environments such as underwater and subterranean. In these environments, the wireless communication medium is obviously not air. Radio signal suffers severe attenuation in water. In contrast, acoustic signal performs much better. For this reason acoustic signal is often considered in underwater IoT networks. Several factors affect the propagation of acoustic signal in water including frequency, distance, temperature, shipping activity, wind, salinity, depth and density. Given the many variables affecting the channel, simple mathematical modeling is not adequate and comprehensive models get very complex very quickly. Simulation modeling then becomes the only viable alternative for the modeling and analysis of underwater networks. Aside from a basic model in ns-2 & ns-3, there aren't any other simulators that model signal propagation for underwater environments. In this work, we develop a module for the acoustic channel in JiST/SWANS (Java in Simulation Time / Scalable Wireless Ad hoc Network Simulator). JiST/SWANS is a high-performance discrete event simulator written in Java, and it is very efficient in its memory usage. This makes it ideal for modeling and simulation of a large number of nodes, a typical scenario in IoT networks. We perfomed several simulation scenarios to validate our module. Our contribution is providing a scalable platform to study the performance of large-scale acoustic underwater IoT networks using the JiST/SWANS simulator.

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