385 research outputs found

    TDMA frame design for a prototype underwater RF communication network

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    This document is the Accepted Manuscript version of the following article: Xianhui Che, Ian Wells, Gordon Dickers, and Paul Kear, ‘TDMA frame design for a prototype underwater RF communication network’, Ad Hoc Networks, Vol. 10 (3): 317-327, first available online 23 July 2011. The version of record is available online at doi: http://dx.doi.org/10.1016/j.adhoc.2011.07.002 © 2011 Elsevier B. V. All rights reserved.Very low frequency electromagnetic communication system is used in a small scale underwater wireless sensor network for coastal monitoring purposes, as recent research has demonstrated distinct advantages of radio waves compared to acoustic and optical waves in shallow water conditions. This paper describes the detailed TDMA and packet design process for the prototype sensor system. The lightweight protocol is time division based in order to fit the unique characteristics and specifications of the network. Evaluations are based on initial beach trial as well as modeling and simulations.Peer reviewe

    Underwater Wireless Communications for Cooperative Robotics with UWSim-NET

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    The increasing number of autonomous underwater vehicles (AUVs) cooperating in underwater operations has motivated the use of wireless communications. Their modeling can minimize the impact of their limited performance in real-time robotic interventions. However, robotic frameworks hardly ever consider the communications, and network simulators are not suitable for HIL experiments. In this work, the UWSim-NET is presented, an open source tool to simulate the impact of communications in underwater robotics. It gathers the benefits of NS3 in modeling communication networks with those of the underwater robot simulator (UWSim) and the robot operating system (ROS) in modeling robotic systems. This article also shows the results of three experiments that demonstrate the capabilities of UWSim-NET in modeling radio frequency (RF) and acoustic links in underwater scenarios. It also permits evaluating several MAC protocols such as additive links online Hawaii area (ALOHA), slotted floor acquisition multiple access (S-FAMA) and user defined protocols. A third experiment demonstrated the excellent capabilities of UWSim-NET in conducting hardware in the loop (HIL) experiments

    A distributed approach to underwater acoustic communications

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    Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2003A novel distributed underwater acoustic networking (UAN) protocol suitable for ad-hoc deployments of both stationary and mobile nodes dispersed across a relatively wide coverage area is presented. Nodes are dynamically clustered in a distributed manner based on the estimated position of one-hop neighbor nodes within a shallow water environment. The spatial dynamic cellular clustering scheme allows scalable communication resource allocation and channel reuse similar in design to land-based cellular architectures, except devoid of the need for a centralized controlling infrastructure. Simulation results demonstrate that relatively high degrees of interference immunity, network connectivity, and network stability can be achieved despite the severe limitations of the underwater acoustic channel

    Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

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    The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa

    Underwater Wireless Sensor Communications in the 2.4 GHz ISM Frequency Band

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    One of the main problems in underwater communications is the low data rate available due to the use of low frequencies. Moreover, there are many problems inherent to the medium such as reflections, refraction, energy dispersion, etc., that greatly degrade communication between devices. In some cases, wireless sensors must be placed quite close to each other in order to take more accurate measurements from the water while having high communication bandwidth. In these cases, while most researchers focus their efforts on increasing the data rate for low frequencies, we propose the use of the 2.4 GHz ISM frequency band in these special cases. In this paper, we show our wireless sensor node deployment and its performance obtained from a real scenario and measures taken for different frequencies, modulations and data transfer rates. The performed tests show the maximum distance between sensors, the number of lost packets and the average round trip time. Based on our measurements, we provide some experimental models of underwater communication in fresh water using EM waves in the 2.4 GHz ISM frequency band. Finally, we compare our communication system proposal with the existing systems. Although our proposal provides short communication distances, it provides high data transfer rates. It can be used for precision monitoring in applications such as contaminated ecosystems or for device communicate at high depth

    Magneto inductive communication system for underwater wireless sensor networks

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    Underwater wireless sensor networks have found a number of applications in underwater environment monitoring, infrastructure monitoring, military applications and ocean exploration. Among the four possible means of underwater wireless communication, namely acoustic, electromagnetic (EM), magneto-inductive (MI) and optics communication, MI communication enjoys the advantages of being low cost and robust equally in air, water and soil. This dissertation presents design and implementation of a low-power and low-cost MI sensor network node that is suited for long-term deployment of underwater and underground infrastructure monitoring, such as bridge scour and levee scour monitoring. The designed MI sensor node combat the directionality of the single coil MI communication by utilizing 3D coil to both transmit and receive. The presented MI sensor node is tested in air and underwater to show robustness and reliability. The sensor node is designed after thorough analysis and evaluation of various MI challenges such as directionality, short range, decoupling due to mis-alignment of coils, and effect of metal structure. A communication range of 40 m has been achieved by the prototype sensor node. The prototyping cost of a sensor node is less than US$100 and will be drastically reduced at volume production. A novel and an energy efficient medium access control (MAC) protocol based on the carrier sense medium access (CSMA) has also been implemented for the designed sensor node to improve throughput in a dense network --Abstract, page iv

    Underwater localization and node mobility estimation

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    In this paper, localizing a moving node in the context of underwater wireless sensor networks (UWSNs) is considered. Most existing algorithms have had designed to work with a static node in the networks. However, in practical case, the node is dynamic due to relative motion between the transmitter and receiver. The main idea is to record the time of arrival message (ToA) stamp and estimating the drift in the sampling frequency accordingly. It should be emphasized that, the channel conditions such as multipath and delay spread, and ambient noise is considered to make the system pragmatic. A joint prediction of the node mobility and speed are estimated based on the sampling frequency offset estimation. This sampling frequency offset drift is detected based on correlating an anticipated window in the orthogonal frequency division multiplexing (OFDM) of the received packet. The range and the distance of the mobile node is predicted from estimating the speed at the received packet and reused in the position estimation algorithm. The underwater acoustic channel is considered in this paper with 8 paths and maximum delay spread of 48 ms to simulate a pragmatic case. The performance is evaluated by adopting different nodes speeds in the simulation in two scenarios of expansion and compression. The results show that the proposed algorithm has a stable profile in the presence of severe channel conditions. Also, the result shows that the maximum speed that can be adopted in this algorithm is 9 km/h and the expansion case profile is more stable than the compression scenario. In addition, a comparison with a dynamic triangular algorithm (DTN) is presented in order to evaluate the proposed system
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