TDA-MAC : TDMA without clock synchronization in underwater acoustic networks

This paper investigates the application of underwater acoustic sensor networks for large scale monitoring of the ocean environment. The low propagation speed of acoustic signals presents a fundamental challenge in coordinating the access to the shared communication medium in such networks. In this paper, we propose two medium access control (MAC) protocols, namely, Transmit Delay Allocation MAC (TDA-MAC) and Accelerated TDA-MAC, that are capable of providing time division multiple access (TDMA) to sensor nodes without the need for centralized clock synchronization. A comprehensive simulation study of a network deployed on the sea bed shows that the proposed protocols are capable of closely matching the throughput and packet delay performance of ideal synchronized TDMA. The TDA-MAC protocols also significantly outperform T-Lohi, a classical contention-based MAC protocol for underwater acoustic networks, in terms of network throughput and, in many cases, end-To-end packet delay. Furthermore, the assumption of no clock synchronization among different devices in the network is a major advantage of TDA-MAC over other TDMA-based MAC protocols in the literature. Therefore, it is a feasible networking solution for real-world underwater sensor network deployments

Data Gathering in UWA Sensor Networks : Practical Considerations and Lessons from Sea Trials

Underwater acoustic (UWA) network protocol design is a challenging task due to several factors, such as slow propagation of acoustic waves, low frequency bandwidth and high bit error and frame error rates often encountered in real UWA environments. In this paper, we consider the design of a robust and scalable data gathering protocol for UWA sensor networks (UASNs), focusing on practical considerations and lessons learnt from multiple lake and sea trials. A cross-layer protocol is presented that integrates a network discovery process, intelligent routing, scheduling via Transmit Delay Allocation MAC (TDA-MAC) and multi-node Automatic Repeat Request (ARQ), to facilitate reliable data gathering in practical UASN deployments. Furthermore, this paper presents the details of a novel experimental testbed and underwater sensor node prototype that were used for the trials reported in this study. Based on the results of the trials, important conclusions are drawn on the protocol features required to achieve reliable networked communication in realistic UWA environments. The insights gained from the trials are valuable both for further development of the proposed data gathering protocol, and for the wider UWA networking research community concerned with developing practical solutions for real-world UASN deployments

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Algorithms for propagation-aware underwater ranging and localization

Mención Internacional en el título de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of the crucial research problems of modern time. Underwater localization stands among the key issues on the way to the proper inspection and monitoring of this significant part of our world. In this thesis, we investigate and tackle different challenges related to underwater ranging and localization. In particular, we focus on algorithms that consider underwater acoustic channel properties. This group of algorithms utilizes additional information about the environment and its impact on acoustic signal propagation, in order to improve the accuracy of location estimates, or to achieve a reduced complexity, or a reduced amount of resources (e.g., anchor nodes) compared to traditional algorithms. First, we tackle the problem of passive range estimation using the differences in the times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand energy- effective algorithm that can be used for the localization of autonomous underwater vehicles (AUVs), and utilizes information about signal propagation. We study the accuracy of this method in the simplified case of constant sound speed profile (SSP) and compare it to a more realistic case with various non-constant SSP. We also propose an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic propagation via ray models, takes into account the difference between rectilinear and non-rectilinear sound ray paths. According to our evaluation, this offers improved range estimation results with respect to standard algorithms that consider the actual value of the speed of sound. We then propose an algorithm suitable for the non-invasive tracking of AUVs or vocalizing marine animals, using only a single receiver. This algorithm evaluates the underwater acoustic channel impulse response differences induced by a diverse sea bottom profile, and proposes a computationally- and energy-efficient solution for passive localization. Finally, we propose another algorithm to solve the issue of 3D acoustic localization and tracking of marine fauna. To reach the expected degree of accuracy, more sensors are often required than are available in typical commercial off-the-shelf (COTS) phased arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We propose a solution for passive 3D localization and tracking using a wideband acoustic array of arbitrary shape, and validate the algorithm in multiple experiments, involving both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio Fernández Anta.- Vocal: Santiago Zazo Bell

Deep learning for internet of underwater things and ocean data analytics

The Internet of Underwater Things (IoUT) is an emerging technological ecosystem developed for connecting objects in maritime and underwater environments. IoUT technologies are empowered by an extreme number of deployed sensors and actuators. In this thesis, multiple IoUT sensory data are augmented with machine intelligence for forecasting purposes

Energy Efficient Cooperative Mobile Sensor Network

Ph.DDOCTOR OF PHILOSOPH