Underwater wireless communications can be carried out through acoustic, radio frequency (RF), and optical waves. Compared to its bandwidth limited acoustic and RF counterparts, underwater optical wireless communications (UOWCs) can support higher data rates at low latency levels. However, the severe aquatic channel conditions (e.g., absorption, scattering, turbulence, etc.) pose great challenges for UOWCs and significantly reduce the attainable communication ranges, which necessitates efficient networking and localization solutions. Therefore, we provide a comprehensive survey on the challenges, advances, and prospects of underwater optical wireless networks (UOWNs) from a layer by layer perspective which includes: (1) Physical layer issues including propagation characteristics, channel modeling, and modulation techniques (2) Data link layer problems covering link configurations, link budgets, performance metrics, and multiple access schemes; (3) Network layer topics containing relaying techniques and potential routing algorithms; (4) Transport layer subjects such as connectivity, reliability, flow and congestion control; (5) Application layer goals, and (6) Localization and its impacts on UOWN layers. Finally, we outline the open research challenges and point out the prospective directions for underwater optical wireless communications, networking, and localization studies.

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Underwater Optical Wireless Communications, Networking, and Localization: A Survey

Internet of Things (IoT), mobile cloud, cloudlet, mobile IoT, IoT cloud, fog, mobile edge, and edge emerging computing paradigms: Disambiguation and research directions

This chapter contains sections titled: Introduction Communication Architecture Basics of Underwater Communications Physical Layer Medium Access Control Layer Network Layer Cross-Layer Design Experimental Platforms UW-Buffalo: An Underwater Acoustic Testbed at the University at Buffalo Conclusions References

https://www.eng.buffalo.edu/wnesl/papers/Wiley_AdvancesUWAN_2013.pdf

Advances in Underwater Acoustic Networking

The Internet of Underwater Things (IoUT) is a novel class of Internet of Things (IoT), and is defined as the network of smart interconnected underwater objects. IoUT is expected to enable various practical applications, such as environmental monitoring, underwater exploration, and disaster prevention. With these applications, IoUT is regarded as one of the potential technologies toward developing smart cities. To support the concept of IoUT, Underwater Wireless Sensor Networks (UWSNs) have emerged as a promising network system. UWSNs are different from the traditional Territorial Wireless Sensor Networks (TWSNs), and have several unique properties, such as long propagation delay, narrow bandwidth, and low reliability. These unique properties would be great challenges for IoUT. In this paper, we provide a comprehensive study of IoUT, and the main contributions of this paper are threefold: (1) we introduce and classify the practical underwater applications that can highlight the importance of IoUT; (2) we point out the differences between UWSNs and traditional TWSNs, and these differences are the main challenges for IoUT; and (3) we investigate and evaluate the channel models, which are the technical core for designing reliable communication protocols on IoUT.

https://ir.nctu.edu.tw:443/bitstream/11536/145904/1/6e62f04f95711ec31f1c7143d47fd8cd.pdf

A Comprehensive Study on the Internet of Underwater Things: Applications, Challenges, and Channel Models

The paper concerns the definition and performance evaluation of a new multi-hop routing protocol for underwater wireless sensor networks Our solution, termed CARP for Channel-aware Routing Protocol, exploits link quality information for data forwarding, in that nodes are selected as relays if they exhibit recent history of successful transmissions to their neighbors CARP avoids loops and can successfully route around connectivity voids and shadow zones by using simple topology information, such as hop count The protocol is also designed to take advantage of power control for selecting robust links The performance of CARP has been compared with that of two other protocols for underwater routing, namely, the Focused Beam Routing (FBR) and a flooding-based solution (EFlood) Metrics of interest include packet delivery ratio, end-to-end packet latency and energy consumption, which have been investigated through ns2-based simulations and experiments at sea The in-field trials have been conducted at two European locations, namely, a Norwegian fjord and the Mediterranean Sea The tests in the Mediterranean Sea have been performed jointly with the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (STO CMRE), under a collaboration agreement between the University of Roma and CMRE 1 Our results show that CARP robust mechanism for relay selection doubles the packet delivery

http://senseslab.di.uniroma1.it/administrator/components/com_jresearch/files/publications/CARP_A_Channel_aware_Routing_P.pdf

CARP: A Channel-aware Routing Protocol for Underwater Acoustic Wireless Networks

The Sapienza University Networking framework for underwater Simulation Emulation and real-life Testing (SUNSET) is a toolkit for the implementation and testing of protocols for underwater sensor networks. SUNSET enables a radical new way of performing experimental research on underwater communications. It allows protocol designers and implementors to easily realize their solutions and to evaluate their performance through simulation, in-lab emulation and trials at sea in a direct and transparent way, and independently of specific underwater hardware platforms. SUNSET provides a complete toolchain of pre-deployment and deployment time tools able to identify risks, malfunctioning and under-performing solutions before incurring the expense of going to sea. Novel underwater systems can therefore be rapidly and easily investigated. Heterogeneous underwater communication technologies from different vendors can be used, allowing the evaluation of the impact of different combinations of hardware and software on the overall system performance. Using SUNSET, underwater devices can be reconfigured and controlled remotely in real time, using acoustic links. This allows the performance investigation of underwater systems under different settings and configurations and significantly reduces the cost and complexity of at-sea trials. This paper describes the architectural concept of SUNSET and presents some exemplary results of its use in the field. The SUNSET framework has been extensively validated during more than fifteen at-sea experimental campaigns in the past four years. Several of these have been conducted jointly with the NATO STO Centre for Maritime Research and Experimentation (CMRE) under a collaboration between the University of Rome and CMRE.

http://senseslab.di.uniroma1.it/administrator/components/com_jresearch/files/publications/The_SUNSET_Framework_for_Simul.pdf

The SUNSET framework for simulation, emulation and at-sea testing of underwater wireless sensor networks

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.

/pdf/carma-channel-aware-reinforcement-learning-based-multi-path-3pj5nnzpbv.pdf

CARMA: Channel-Aware Reinforcement Learning-Based Multi-Path Adaptive Routing for Underwater Wireless Sensor Networks

In this paper we introduce SecFUN, a security framework for underwater acoustic sensor networks (UASNs). Despite the increasing interest on UASNs, solutions to secure protocols from the network layer up to the application layer are still overlooked. The aim of this work is therefore manyfold. We first discuss common threats and countermeasures for UASNs. Then, we select the most effective cryptographic primitives to build our security framework (SecFUN). We show that SecFUN is flexible and configurable with different features and security levels to satisfy UASN deployment security requirements. SecFUN provides data confidentiality, integrity, authentication and non-repudiation by exploiting as building blocks AES in the Galois Counter Mode (GCM) and short digital signature algorithms. As a proof of concept of the proposed approach, we extend the implementation of the Channel-Aware Routing Protocol (CARP) to support the proposed cryptographic primitives. Finally, we run a performance evaluation of our proposed secure version of CARP in terms of the overall energy consumption and latency, employing GCM and the state of the art in short digital signature schemes such as ZSS, BLS and Quartz. Results show that a flexible and full-fledged security solution tailored to meet the requirements of UASNs can be provided at reasonable costs.

http://senseslab.di.uniroma1.it/administrator/components/com_jresearch/files/publications/SecFUN_Security_Framework_for_.pdf

SecFUN: Security framework for underwater acoustic sensor networks

We describe the newest design and development of the Sapienza University Networking framework for underwater Simulation Emulation and real-life Testing (SUNSET), a powerful toolkit for implementation and testing of novel protocol solutions for underwater sensor networks. SUNSET enables testing and enhancement of underwater solutions using a controlled simulation environment. The very simulation code can be then transparently ported to various real hardware and underwater platforms for protocol emulation and actual in field testing. SUNSET was the first open source framework for seamless simulation, emulation and actual at sea testing of novel underwater systems. The first SUNSET was presented in 2011 [1], improved in 2012 [2] and freely released to the research community in May 2012. Since then, SUNSET has been significantly improved and validated through several trials at sea. New modules have been created and the functionalities of existing ones have been extended and enhanced. The new SUNSET version 2.0 has been recently released to the community (October 2013 [3]). This paper discusses in details the SUNSET 2.0 features and modules, and report about the latest in field tests where SUNSET 2.0 has been used.

http://senseslab.di.uniroma1.it/administrator/components/com_jresearch/files/publications/SUNSET_version_2_0_Enhanced_Fr.pdf

Daniele Spaccini

Papers

CARP: A Channel-aware Routing Protocol for Underwater Acoustic Wireless Networks

The SUNSET framework for simulation, emulation and at-sea testing of underwater wireless sensor networks

CARMA: Channel-Aware Reinforcement Learning-Based Multi-Path Adaptive Routing for Underwater Wireless Sensor Networks

SecFUN: Security framework for underwater acoustic sensor networks

SUNSET version 2.0: enhanced framework for simulation, emulation and real-life testing of underwater wireless sensor networks