NaNet: a Low-Latency, Real-Time, Multi-Standard Network Interface Card with GPUDirect Features

While the GPGPU paradigm is widely recognized as an effective approach to high performance computing, its adoption in low-latency, real-time systems is still in its early stages. Although GPUs typically show deterministic behaviour in terms of latency in executing computational kernels as soon as data is available in their internal memories, assessment of real-time features of a standard GPGPU system needs careful characterization of all subsystems along data stream path. The networking subsystem results in being the most critical one in terms of absolute value and fluctuations of its response latency. Our envisioned solution to this issue is NaNet, a FPGA-based PCIe Network Interface Card (NIC) design featuring a configurable and extensible set of network channels with direct access through GPUDirect to NVIDIA Fermi/Kepler GPU memories. NaNet design currently supports both standard - GbE (1000BASE-T) and 10GbE (10Base-R) - and custom - 34~Gbps APElink and 2.5~Gbps deterministic latency KM3link - channels, but its modularity allows for a straightforward inclusion of other link technologies. To avoid host OS intervention on data stream and remove a possible source of jitter, the design includes a network/transport layer offload module with cycle-accurate, upper-bound latency, supporting UDP, KM3link Time Division Multiplexing and APElink protocols. After NaNet architecture description and its latency/bandwidth characterization for all supported links, two real world use cases will be presented: the GPU-based low level trigger for the RICH detector in the NA62 experiment at CERN and the on-/off-shore data link for KM3 underwater neutrino telescope

Development of an underwater camera system for inland freshwater aquaculture

Computer vision and image processing technologies are applied towards aquatic research to understand fish and its interaction with other fishes and their environment. The understanding of vision-based data acquisition and processing aids in developing predictive frameworks and decision support systems for efficient aquaculture monitoring and management. However, this emerging field is confronted by a lack of high-quality underwater visual data, whether from public or local setups. An accessible underwater camera system that intensively obtains underwater visual data periodically and in real-time is the most desired system for such emerging studies. In this regard, an underwater camera system that captures underwater images from an inland freshwater aquaculture setup was proposed. The components of the underwater camera system are primarily based on Raspberry Pi, an open-source computing platform. The underwater camera continuously provides a real-time video streaming link of underwater scenes, and the local processor periodically acquires and stores data from this link in the form of images. These data are stored locally and remotely. Also, the local processor initiates a connection to a remote processor to allow the remote view of the real-time video streaming link. Aside from accessing the data and streaming link remotely, the remote processor analyzes the statistics of the underwater images to motivate the application of color balance and fusion, a state-of-the-art underwater image enhancement method. The applications of the proposed system and the enhancement to the captures are objectively evaluated. The proposed system captured around 1.2 Gb worth of 8 MP underwater images during daytime every day and stored these images in cloud storage. Also, the system captured subjects within 10-35 cm of turbid fishpond water. The statistical analysis of the gathered data revealed that underwater images from turbid fishpond setups have low quality in terms of inaccurate color representations (i.e., dominant green intensities and mostly submissive blue intensities) and low contrast. These observations appropriated the application of color balance and fusion to the locally acquired data. Furthermore, the objective evaluation revealed that color balance and fusion is the most effective method of improving information content and edge details, as quantified by high color information entropies and high average gradients. These metrics revealed the effectiveness of the proposed data acquisition and preprocessing system

TS-MUWSN: Time synchronization for mobile underwater sensor networks

Time synchronization is an important, yet challenging, problem in underwater sensor networks (UWSNs). This challenge can be attributed to: 1) messaging timestamping; 2) node mobility; and 3) Doppler scale effect. To mitigate these problems, we present an acoustic-based time-synchronization algorithm for UWSN, where we compare several message time-stamping algorithms in addition to different Doppler scale estimators. A synchronization system is based on a bidirectional message exchange between a reference node and a slave one, which has to be synchronized. Therefore, we take as reference the DA-Sync-like protocol (Liu et al., 2014), which takes into account node's movement by using first-order kinematic equations, which refine Doppler scale factor estimation accuracy, and result in better synchronization performance. In our study, we propose to modify both time-stamping and Doppler scale estimation procedures. Besides simulation, we also perform real tests in controlled underwater communication in a water test tank and a shallow-water test in the Mediterranean Sea.Peer ReviewedPostprint (author's final draft

The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version

Efficient Approach for OS-CFAR 2D Technique Using Distributive Histograms and Breakdown Point Optimal Concept applied to Acoustic Images

In this work, a new approach to improve the algorithmic efficiency of the Order Statistic-Constant False Alarm Rate (OS-CFAR) applied in two dimensions (2D) is presented. OS-CFAR is widely used in radar technology for detecting moving objects as well as in sonar technology for the relevant areas of segmentation and multi-target detection on the seafloor. OS-CFAR rank orders the samples obtained from a sliding window around a test cell to select a representative sample that is used to calculate an adaptive detection threshold maintaining a false alarm probability. Then, the test cell is evaluated to determine the presence or absence of a target based on the calculated threshold. The rank orders allows that OS-CFAR technique to be more robust in multi-target situations and less sensitive than other methods to the presence of the speckle noise, but requires higher computational effort. This is the bottleneck of the technique. Consequently, the contribution of this work is to improve the OS-CFAR 2D with the distributive histograms and the optimal breakdown point optimal concept, mainly from the standpoint of efficient computation. In this way, the OS-CFAR 2D on-line computation was improved, by means of speeding up the samples sorting problem through the improvement in the calculus of the statistics order. The theoretical algorithm analysis is presented to demonstrate the improvement of this approach. Also, this novel efficient OS-CFAR 2D was contrasted experimentally on acoustic images.Fil: Villar, Sebastian Aldo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ingeniería Olavarría. Departamento de Electromecánica. Grupo INTELYMEC; ArgentinaFil: Menna, Bruno Victorio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ingeniería Olavarría. Departamento de Electromecánica. Grupo INTELYMEC; ArgentinaFil: Torcida, Sebastián. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Departamento de Matemática; ArgentinaFil: Acosta, Gerardo Gabriel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ingeniería Olavarría. Departamento de Electromecánica. Grupo INTELYMEC; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentin