The paper describes the Dual Channel Acoustic Communication Protocol (DCAP) and the results of its experimental trials. This open protocol has been developed as an extension of the SWiGacoustic standard proposed by the SWiG Working Group considering requirements and use cases. It enables networking capabilities, simultaneous low and high rate data transfer among acoustic nodes, and frequency division multiple access to the underwater channel. First, the protocol specification and the details of its implementation are described. Then, the methodology for the feasibility testing is presented, followed by the experimental trials at sea in two different environments: confined and open water. The results achieved show the feasibility of using this protocol to allow a network composed of acoustic nodes to simultaneously use low and high rate channels to exchange heterogeneous data through TDMA and FDMA.

The Internet of Underwater Things (IoUT) is a novel paradigm for the Blue Economy sector bringing the ability to sense, actuate, exchange information, through low cost technologies, typical of the terrestrial IoT and personal devices, to marine and ocean environments. It requires novel underwater networking concepts that are at the core of the described developed system. While IoUT has already been proposed by the authors for sake of environmental monitoring and marine exploration, in this demo we focus on how IoUT can bring novel opportunities in the field of underwater sport, leisure and tourism. In particular, the demo demonstrates FunDive, a novel wearable system for divers, developed in EC EASME ARCHEOSUb, that supports real-time monitoring of the divers positions and health conditions, at the same time allowing unprecedented enhanced visits of the sites. The system is composed of the following elements: a miniaturized underwater sensor node and an underwater tablet. The miniaturized underwater sensor node hosts an acoustics modem, the underwater networking and information compression logic, as well as a battery pack. The tablet is connected to the node and runs a dedicated APP. The system allows divers to communicate underwater, localize themselves/be localized, navigate to points of interest, and get displayed contents based on their position. A dedicated network protocol provides secure and reliable communication among divers and supports their localization. Our system has been developed by leveraging on the SUNSET Software Defined Communication Stack (S-SDCS) framework and its modular architecture and networking capabilities. In our demonstration we show, through an emulated underwater network environment, the flexibility and effectiveness of our system in allowing divers and surface operators to securely and reliably communicate using underwater tablets and acoustic networking. The navigation and acoustic tracking of divers will be also shown through a novel application interface.

This paper concerns the design and implementation of a novel system for diving operations based on an efficient underwater acoustic network. The proposed system is composed of both static underwater nodes and divers that are equipped with acoustic modems and underwater tablets. The SUNSET Software Defined Communication Stack (S-SDCS) has been used to provide multi-hop networking capabilities. Novel image compression and transmission modules have been designed and implemented in S-SDCS. In addition, the localization module has been enhanced to increase the safety of the divers whose positions can be locally and remotely monitored. These modules interact with an innovative mobile application running on the underwater tablet thus enabling divers communication and remote position estimation and monitoring. In addition, divers can acquire and share pictures with other operators in real-time. The user interface of the application has been designed according to diver needs and feedback thus making it perfectly suitable for several diving scenarios. The system has been tested in several at-sea campaigns considering different application scenarios. The achieved results confirm that the proposed system is suitable for several diving experiences, enabling novel application scenarios while increasing divers safety.

Routing solutions for multi-hop underwater wireless sensor networks suffer significant performance degradation as they fail to adapt to the overwhelming dynamics of underwater environments. To respond to this challenge, we propose a new data forwarding scheme where relay selection swiftly adapts to the varying conditions of the underwater channel. Our protocol, termed CARMA for Channel-aware Reinforcement learning-based Multi-path Adaptive routing, adaptively switches between single-path and multi-path routing guided by a distributed reinforcement learning framework that jointly optimizes route-long energy consumption and packet delivery ratio. We compare the performance of CARMA with that of three other routing solutions, namely, CARP, QELAR and EFlood, through SUNSET-based simulations and experiments at sea. Our results show that CARMA obtains a packet delivery ratio that is up to 40% higher than that of all other protocols. CARMA also delivers packets significantly faster than CARP, QELAR and EFlood, while keeping network energy consumption at bay.

This poster describes the main features provided by the Sapienza University Networking framework for underwater Simulation Emulation and real-life Testing (SUNSET) [1]. Particularly, we focus on the innovations and improvements introduced in SUNSET v2 after several years of in field experimentation. All the results collected during the different sea trials (considering sea, fjord, lake and river scenarios) have shown how SUNSET represents a robust, reliable and flexible solutions for in field tests where a network of heterogeneous devices is considered, with different acoustic modems, sensing devices and underwater vehicles.

We demonstrate the use of a novel cross layer protocol for routing in Underwater Acoustic Sensor Networks (UASNs). Our protocol, named CARP [1] for Channel-Aware Routing Protocol, is able to dynamically adapt to channel dynamics and to the changes occurring in the network topology and link quality over time. CARP is implemented and tested using the Sapienza University Networking framework for underwater Simulation Emulation and real-life Testing (SUNSET) [2] in different network scenarios. Our demonstration shows that CARP is able to find the suitable routes and to deliver data to the sink node independently of prevailing packet error rates and of nodes/links addition and removal.