The DESERT Underwater emulation system (http://nautilus.dei.unipd.it/desert-underwater), originally designed for testing underwater acoustic networks, has been recently extended. The new framework now includes multi-modal communication functionalities encompassing low rate and high rate acoustics as well as optics, the capability of testing wireless telemetry for underwater equipment, a connection to the most recent version of the World Ocean Simulation System (WOSS), a modification to the RECORDS system for sea trial remote control, and an interface between external tools, e.g., Matlab, and the EvoLogics modem. In addition, experimental activities are now supported by an accurate real-time event scheduler which has been shown to support, among others, long experiments involving time-division multiple-access (TDMA)-based MAC protocols. These additional protocol schemes from the MAC to the application layer (most of which have been tested in controlled environments and sea trials) now make DESERT Underwater a comprehensive tool for underwater network simulation and experimentation. In this paper, we present the new functionalities developed over the last two years.
In this paper, we explore the possibility of controlling a Remotely Operated Vehicle (ROV) via a fully wireless control channel. As a first step, we review the expected bit rate offered by optical, acoustic as well as radio-frequency underwater communication technologies, as a function of the distance between the transmitter and the receiver. We then discuss the ROV data transfer requirements and discuss which ones can be supported by a given technology at a given distance. Finally, we simulate the performance of the system during missions of interest, and conclude by discussing the effectiveness of wireless control methods for ROVs
While acoustic communications are still considered the most prominent technology to communicate under water, other technologies are being developed based, e.g., on optical and radio-frequency electromagnetic waves. Each technology has its own advantages and drawbacks: for example, acoustic signals achieve long communication ranges at order-of-kbit/s rates, whereas optical signals offer order-of-Mbit/s transmission rates, but only over short ranges. Such a diversity can be leveraged by multimodal systems, which integrate different technologies and provide the intelligence required to decide which one should be used at any given time. In this paper, we address a fundamental part of this intelligence by proposing Optimal Multimodal Routing (OMR), a novel routing protocol for underwater networks of multimodal nodes. OMR makes distributed decisions about the flow in each link and over each technology at any given time, in order to advance a packet towards its destination; in doing so, it prevents bottlenecks and allocates resources fairly to different nodes. We analyze the performance of OMR via simulations and in a field experiment. The results show that OMR successfully leverages all technologies to deliver data, even in the presence of imperfect topology information. To permit the reproduction of our results, we share our simulation code.
In this paper, we consider data muling over a network of fixed sensors by employing a mobile Autonomous Underwater Vehicle (AUV). We approach the problem using both acoustic and optical communications together in a multi-modal hybrid network: the most appropriate physical layer is chosen according to the quality of the transmissions that take place over time. We consider three distinct cases of water type: clear, coastal and turbid water, in order to test the system behavior under different conditions. The ambient light noise is realistically reproduced via the Hydrolight software and taken into account, due to its important contribution to the optical SNR in shallow waters. Finally, we simulate the performance of the system using the DESERT Underwater framework during missions of interest in different channel conditions and network depth. Our results show the effectiveness of a multi-modal underwater network in the cases of clear and coastal waters
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