1,106 research outputs found

    A Hierarchical Communication Architecture for Oceanic Survelliance Applications

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    The interest in monitoring applications using underwater sensor networks has been growing in recent years. The severe communication restrictions imposed by underwater channels make that efficient monitoring be a challenging task. Though a lot of research has been conducted on underwater sensor networks, there are only few concrete applications to a real-world case study. In this work, hence, we propose a general three tier architecture leveraging low cost wireless technologies for acoustic communications between underwater sensors and standard technologies, Zigbee and Wireless Fidelity (WiFi), for water surface communications. We have selected a suitable Medium Access Control (MAC) layer, after making a comparison with some common MAC protocols. Thus the performance of the overall system in terms of Signals Discarding Rate (SDR), signalling delay at the surface gateway as well as the percentage of true detection have been evaluated by simulation, pointing out good results which give evidence in applicability’s favour

    A cluster-based mobile data-gathering scheme for underwater sensor networks

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    Design and implementation of heterogeneous surface gateway for underwater acoustic sensor network

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    Underwater Acoustic Sensor Networks (UASNs) are used for diverse purposes such as pollution monitoring, disaster prevention and industrial sensing in the oceans. Especially, UASNs are mainly focusing on monitoring various underwater environmental data and delivering the data to a monitoring center where nearby or far from the deployed area. To reliably deliver the data, a surface gateway should convert acoustic signal to RF (Radio Frequency) signal. In this paper, we devise a multiple interfaces-based surface gateway that can connect both a cellular network and a Zigbee network. Depends on the service requirement, the surface gateway can easily adopt each wireless interface and relay the data to a low power ZigBee network or a long range CDMA network

    Proteus II: design and evaluation of an integrated power-efficient underwater sensor node

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    We describe the design and evaluation of an integrated low-cost underwater sensor node designed for reconfigurability, allowing continuous operation on a relatively small rechargeable battery for one month. The node uses a host CPU for the network protocols and processing sensor data and a separate CPU performs signal processing for the ultrasonic acoustic software-defined Modulator/Demodulator (MODEM). A Frequency Shift Keying- (FSK-) based modulation scheme with configurable symbol rates, Hamming error correction, and Time-of-Arrival (ToA) estimation for underwater positioning is implemented. The onboard sensors, an accelerometer and a temperature sensor, can be used to measure basic environmental parameters; additional internal and external sensors are supported through industry-standard interfaces (I2C, SPI, and RS232) and an Analog to Digital Converter (ADC) for analog peripherals. A 433 MHz radio can be used when the node is deployed at the surface. Tests were performed to validate the low-power operation. Moreover the acoustic communication range and performance and ToA capabilities were evaluated. Results show that the node achieves the one-month lifetime, is able to perform communication in highly reflective environments, and performs ToA estimation with an accuracy of about 1-2 meters

    Self-organizing Fast Routing Protocols for Underwater Acoustic Communications Networks

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    To address this problem, in this thesis we propose a cross-layer proactive routing initialization mechanism that does not require additional measurements and, at the same time, is energy efficient. Two routing protocols are proposed: Self-Organized Fast Routing Protocol for Radial Underwater Networks (SOFRP) for radial topology and Self-organized Proactive Routing Protocol for Non-uniformly Deployed Underwater Networks (SPRINT) for a randomly deployed network. SOFRP is based on the algorithm to recreate a radial topology with a gateway node, such that packets always use the shortest possible path from source to sink, thus minimizing consumed energy. Collisions are avoided as much as possible during the path initialization. The algorithm is suitable for 2D or 3D areas, and automatically adapts to a varying number of nodes. In SPRINT the routing path to the gateway is formed on the basis of the distance, measured by the signal strength received. The data sending node prefers to choose the neighbor node which is closest to it. It is designed to achieve high data throughput and low energy consumption of the nodes. There is a tradeoff between the throughput and the energy consumption: more distance needs more transmission energy, and more relay nodes (hops) to the destination node affects the throughput. Each hop increases the packet delay and decreases the throughput. Hence, energy consumption requires nearest nodes to be chosen as forwarding node whereas the throughput requires farthest node to be selected to minimize the number of hops. Fecha de lectura de Tesis Doctoral: 11 mayo 2020Underwater Wireless Sensor Networks (UWSNs) constitute an emerging technology for marine surveillance, natural disaster alert and environmental monitoring. Unlike terrestrial Wireless Sensor Networks (WSNs), electromagnetic waves cannot propagate more than few meters in water (high absorption rate). However, acoustic waves can travel long distances in underwater. Therefore, acoustic waves are preferred for underwater communications, but they travel very slow compare to EM waves (typical speed in water is 1500 m/s against 2x10^8 m/s for EM waves). This physical effect makes a high propagation delay and cannot be avoided, but the end-to-end packet delay it can be reduced. Routing delay is one of the major factors in end-to-end packet delay. In reactive routing protocols, when a packet arrives to a node, the node takes some time to select the node to which the data packet would be forwarded. We may reduce the routing delay for time-critical applications by using proactive routing protocols. Other two critical issues in UWSNs are determining the position of the nodes and time synchronization. Wireless sensor nodes need to determine the position of the surrounding nodes to select the next node in the path to reach the sink node. A Global Navigation Satellite System (GNSS) cannot be used because of the very short underwater range of the GNSS signal. Timestamping to estimate the distance is possible but the limited mobility of the UWSN nodes and variation in the propagation speed of the acoustic waves make the time synchronization a challenging task. For these reasons, terrestrial WSN protocols cannot be readily used for underwater acoustic networks

    An efficient AUV-aided data collection in underwater sensor networks

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    Underwater Wireless Sensor Networks: How Do Acoustic Propagation Models Impact the Performance of Higher-Level Protocols?

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    Several Medium Access Control (MAC) and routing protocols have been developed in the last years for Underwater Wireless Sensor Networks (UWSNs). One of the main difficulties to compare and validate the performance of different proposals is the lack of a common standard to model the acoustic propagation in the underwater environment. In this paper we analyze the evolution of underwater acoustic prediction models from a simple approach to more detailed and accurate models. Then, different high layer network protocols are tested with different acoustic propagation models in order to determine the influence of environmental parameters on the obtained results. After several experiments, we can conclude that higher-level protocols are sensitive to both: (a) physical layer parameters related to the network scenario and (b) the acoustic propagation model. Conditions like ocean surface activity, scenario location, bathymetry or floor sediment composition, may change the signal propagation behavior. So, when designing network architectures for UWSNs, the role of the physical layer should be seriously taken into account in order to assert that the obtained simulation results will be close to the ones obtained in real network scenarios
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