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SmartData: an IoT-ready API for sensor networks

INTERNATIONAL JOURNAL OF SENSOR NETWORKS 2018年第3期28卷 202-210页

作者： Frohlich, Antonio Augusto Univ Fed Santa Catarina Software Hardware Integrat Lab BR-88040900 Florianopolis SC Brazil

Despite intense research on wireless sensor networks (WSN) in the last two decades, programmers still do not have a cohesive and expressive application programming interface (API) to model their applications and to connect them to the internet of things (IoT). In this paper, we introduced SmartData, a high-level API for WSN aiming at leveraging the myriad of features available on such networks while delivering a common abstraction for sensed data that facilitates application development without incurring significant overhead. SmartData is enriched with enough metadata to become self-contained regarding semantics, spatial location, timing, and trustfulness. It is meant to be the only application-visible construct in the platform and therefore implicitly mediates all system services, including communication, synchronisation, and the interaction with transducers and actuators, local or remote. Reading a SmartData implies in sensing. Writing to it defines a new setpoint for actuators. We demonstrate the concept through the automation of a solar building with a set of SmartData in C++.

关键词： WSN wireless sensor network IoT internet of things sensing API application programming interface sensing data management

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Automated performance measurement for 3D building modeling decisions

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AUTOMATION IN CONSTRUCTION 2018年第Sep.期93卷 91-111页

作者： Yarmohammadi, Saman Castro-Lacouture, Daniel Georgia Inst Technol Sch Bldg Construct Atlanta GA 30332 USA

Building information modeling (BIM) is instrumental in documenting design, enhancing customer experience, and improving product functionality in capital projects. However, high-quality building models do not happen by accident, but rather because of a managed process that involves several participants from different disciplines and backgrounds. Throughout this process, the different priorities of design modelers often result in conflicts that can negatively impact project outcomes. To prevent such unwanted outcomes from occurring, the modeling process needs to be effectively managed. This effective management requires an ability to closely monitor the modeling process and correctly measure the modelers' performance. Nevertheless, existing methods of performance monitoring in building design practices lack an objective measurement system to quantify modeling progress. The widespread utilization of BIM tools presents a unique opportunity to retrieve granular design process data and conduct accurate performance measurements. This research improves upon previous efforts by presenting a novel application programming interface (API)-enabled approach to (a) automatically collect detailed model development data directly from BIM software packages in real-time, and (b) efficiently calculate several modeling performance measures during schematic and design development phases of building projects. These indicators can be used to properly arrange modeling teams in the quest for high-quality building models. The specific objectives of this study to examine the feasibility of a proposed automated design performance measurement framework, and to identify optimal modeling team configurations using empirical performance information. A passive data recording approach allows for the real-time capture of comprehensive user interface (UI) interaction and model element modification events. The proposed framework is implemented as an Autodesk Revit plugin. Next, an experiment is conducted

关键词： BIM Data analytics application programming interface Modeling team Performance measurement

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Variable-Magnification Optical Stimulator for Training and Validation of Spaceborne Vision-Based Navigation

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JOURNAL OF SPACECRAFT AND ROCKETS 2019年第4期56卷 1060-1072页

作者： Beierle, Connor D'Amico, Simone Stanford Univ Dept Aeronaut & Astronaut Space Rendezvous Lab Durand Bldg496 Lomita Mall Stanford CA 94305 USA

This paper addresses the design, calibration, and utilization of a hardware-in-the loop optical stimulator for the training and validation of vision-based sensors and algorithms used for spaceborne navigation. This testbed overcomes deficiencies of existing approaches in literature, which mainly focus on emulating single operational zones such as inertial, far-range, or close-range relative navigation. Consequently, the behavior of vision-based sensors and algorithms operating in mixed or transitioning navigation regimes have remained poorly assessed before launch. To address these issues, this novel optical stimulator reproduces the large geometric and radiometric dynamic range of the space environment with a pair of lenses to achieve variable magnification of an organic light emitting diode monitor. This approach is shown to support vision-based sensors of both narrow and wide field of view, increase the radiometric dynamic range of the testbed, and emulate close-range scenarios when light from an object is not collimated. A calibration procedure is presented that places sources of light at the intended angular location over the magnification range in the presence of varying distortions. The calibrated testbed is then used to simulate dynamic inertial and relative navigation scenarios of operational relevance. These hardware-in-the-loop simulations allow for the training and validation of optical hardware, software, and algorithms for future distributed space systems.

关键词： Vision Based Navigation Horizon Sensors Space Environment Hardware in the Loop Simulation Distributed Space Systems Satellites Attitude Dynamics Earth Cathode Ray Tubes application programming interface

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JDap: Supporting in-memory data persistence in javascript using Intel's PMDK

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JOURNAL OF SYSTEMS ARCHITECTURE 2019年第0期101卷 101662-000页

作者： You, Litong Xu, Hao Zhang, Qipeng Li, Tianyou Li, Chen Chen, Yuting Huang, Linpeng Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Peoples R China Intel Asia Pacific R&D Co LTD Shanghai Peoples R China Aalborg Univ Dept Mat & Prod Aalborg Denmark

Data persistence is a feature that the data needs to live longer than its creator. The state-of-the-art is in-memory data persistence, requiring data in the memory to be persistent even when the application crashes. So far in-memory data persistence has been supported in many programming languages such as C, C++, and Java. However, it has not yet been well supported in JavaScript, a popular scripting language for software development. To solve this problem, we introduce JDap, an extension to JavaScript's runtime and execution engine, to support in-memory data persistence in JavaScript using Intel's Persistent Memory Development Kit (PMDK). JDap consists of (1) a JavaScript persistent object pool that serves as a heap in which persistent objects can be created, managed, and accessed safely and consistently. In particular, this pool supports shared memory parallelism, allowing persistent data to be accessed in parallel;(2) a set of JavaScript APIs that provides programmers with supports in managing and accessing persistent data in an easy-to-use and safe manner. We have implemented JDap and evaluated it against two database-supported data persistence styles (MongoDB's object store and indexedDB's binary store) on micro-benchmarks and real-world applications. Our evaluation shows that JDap outperforms object store by 1.6 x and outperforms binary store by 24.6 x. We have also evaluated JDap against Extended Memory Semantics (EMS) on data-intensive tasks. The results show that JDap outperforms EMS by 2 x.

关键词： Persistent memory development kit Javascript In-Memory data persistence Object pool application programming interface

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Benchmarking Analysis and Characterization of Hypervisors for Space Multicore Systems

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2019年第11期16卷 500-511页

作者： Muttillo, Vittoriano Tiberi, Luca Pomante, Luigi Serri, Paolo Univ Aquila Ctr Excellence DEWS Via Vetoio I-67100 Laquila Italy Thales Alenia Space Thales Alenia Space Italia Via Campo Pile I-67100 Laquila Italy

Multicore systems are becoming widely diffused in the space domain, mainly because of the opportunities to improve performance and, at the same time, to optimize orthogonal metrics (e.g., cost, power consumption). However, the need to consider safety integrity levels, dictated by the relevant standards (i.e., ECSS-Q-ST-80C, ECSSQ-ST-30, ECSSQ-ST-40C, NPD 8700.1E, NPR 8715.3D, JMR-001, OST 134-1021-99), into space applications adds further challenges. In fact, in a multicore system, multiple processing cores share various resources;therefore, the implementation of modern and complex integrated modular avionics systems is problematic. Actually, integrated modular avionics systems are inherently mixed-critical ones where spatial and temporal isolation in the shared resources access is essential. As a way to mitigate such a problem, the exploitation of virtualization technologies allows to guarantee isolation and certification requirements but, at the same time, introduces scheduling overhead and new issues. The selection of the best virtualization technology is just one part of the solution. Then, further benchmarking and validation activities should help developers to certify virtualized environments running on multicore architectures. In such a context, this work proposes a methodology for characterization of hypervisor technologies in the space domain. Experimental results obtained by applying the proposed methodology in order to characterize some reference hypervisors features close the paper.

关键词： Integrated Modular Avionics System European Cooperation for Space Standardization Real Time Operating System application programming interface ESA Software Architecture Microprocessors Embedded Systems System on a Chip Commercial Aircraft

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Modeling and Simulation Speed-Up of Plasma Actuators Implementing Reconfigurable Hardware

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AIAA JOURNAL 2018年第8期56卷 3035-3046页

作者： Ebrahimi, Abbas Zandsalimy, Mohammad Sharif Univ Technol Dept Aerosp Engn Tehran 111551639 Iran

The objective of the present study is to investigate the capability of field-programmable gate array hardware in numerical simulation of a model of a dielectric barrier discharge plasma actuator to accelerate the calculations. The reconfigurable hardware is designed such that it is possible to reprogram its architecture after manufacturing. This provides the capability to design and implement various architectures for several applications. Two reconfigurable chips are used in the present study, one of which consists of a programmable logic unit and a typical microprocessor. This hybrid architecture makes the high performance of the reconfigurable hardware in custom computing and the efficiency of the microprocessor in data flow control accessible. An automated design procedure is used for the design of the reconfigurable hardware. Further, a finite difference representation of a phenomenological model of a plasma actuator is derived and implemented on the field-programmable gate array hardware. The results are validated against other numerical data, and the computational time is compared to different conventional processors. Using the reconfigurable hardware results in up to 96% computational time reduction compared to a recent Core i7 processor.

关键词： Plasma Actuator application Specific Integrated Circuits Numerical Simulation Dielectric Barrier Discharge High Performance Computing Systems Digital Computers Graphics Processing Unit Electric Potential application programming interface Discontinuous Galerkin Method

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Macrostrat: A Platform for Geological Data Integration and Deep-Time Earth Crust Research

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GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS 2018年第4期19卷 1393-1409页

作者： Peters, Shanan E. Husson, Jon M. Czaplewski, John Univ Wisconsin Dept Geosci Madison WI 53706 USA Univ Victoria Sch Earth & Ocean Sci Victoria BC Canada

Characterizing the lithology, age, and physical-chemical properties of rocks and sediments in the Earth's upper crust is necessary to fully assess energy, water, and mineral resources and to address many fundamental questions. Although a large number of geological maps, regional geological syntheses, and sample-based measurements have been produced, there is no openly available database that integrates rock record-derived data, while also facilitating large-scale, quantitative characterization of the volume, age, and material properties of the upper crust. Here we describe Macrostrat, a relational geospatial database and supporting cyberinfrastructure that is designed to enable quantitative spatial and geochronological analyses of the entire assemblage of surface and subsurface sedimentary, igneous, and metamorphic rocks. Macrostrat contains general, comprehensive summaries of the age and properties of 33,903 lithologically and chronologically defined geological units distributed across 1,474 regions in North and South America, the Caribbean, New Zealand, and the deep sea. Sample-derived data, including fossil occurrences in the Paleobiology Database, more than 180,000 geochemical and outcrop-derived measurements, and more than 2.3 million bedrock geologic map units from over 200 map sources, are linked to specific Macrostrat units and/or lithologies. Macrostrat has generated numerous quantitative results and its infrastructure is used as a data platform in several independently developed mobile applications. It is necessary to expand geographic coverage and to refine age models and material properties to arrive at a more precise characterization of the upper crust globally and test fundamental hypotheses about the long-term evolution of Earth systems.

关键词： stratigraphy geology geochronology geologic map geoinformatics database application programming interface

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Worst-Case Execution-Time-Aware Parallelization of Model-Based Avionics applications

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2019年第11期16卷 521-533页

作者： Reder, Simon Kempf, Fabian Bucher, Harald Becker, Juergen Alefragis, Panayiotis Voros, Nikolaos Skalistis, Stefanos Derrien, Steven Puaut, Isabelle Oey, Oliver Stripf, Timo Ferdinand, Christian David, Clement Ulbig, Peer Mueller, David Durak, Umut Karlsruhe Inst Technol ITIV Engesserstr 5 D-76131 Karlsruhe Germany Univ Peloponnese Elect & Comp Engn Dept Megalou Alexandrou 1 Patras 26334 Greece Univ Rennes 1 IRISA Ave Gen Leclerc F-35042 Rennes France Emmtrix Technol GmbH Haid & Neu Str 7 D-76131 Karlsruhe Germany AbsInt Angew Informat GmbH Sci Pk 1 D-66123 Saarbrucken Germany ESI Grp F-75015 Paris France German Aerosp Ctr DLR Inst Flight Syst Lilienthalpl 7 D-38108 Braunschweig Germany Scilab Enterprises 143 Bis Rue Yves Le Coz F-78000 Versailles France

Multicore processing systems are the solution of choice to provide high embedded computing performance, but drawbacks in timing predictability and programmability limit their adoption in safety-critical aerospace applications. This work presents a compiler tool flow for automated parallelization of model-based real-time software, which addresses the shortcomings of multicore architectures in real-time systems. The flow is demonstrated using a model-based terrain awareness and warning systems (TAWSs) and an edge detection algorithm from the image-processing domain. Model-based applications are first transformed into real-time C code and, from there, into a well-predictable parallel C program. Tight bounds for the worst-case execution time (WCET) of the parallelized program can be determined using an integrated multicore WCET analysis. Thanks to the use of an architecture description language, the general approach is applicable to a wider range of target platforms. An experimental evaluation for a research architecture with network-on-chip interconnect shows that the parallel WCET of the TAWS application can be improved by a factor of 1.77 using the presented compiler tools.

关键词： Worst Case Execution Time Enhanced Ground Proximity Warning System High Performance Computing Real Time System Real Time Software Image Processing Model Based Design Graphical User interface application programming interface Time Division Multiple Access

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Multi-Level High Precision LBS Architecture Based on GNSS CORS Network, A Case Study of HNCORS

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IEEE ACCESS 2019年 7卷 185042-185054页

作者： Sun, Hua Dong, Mingxu Chu, Bin Ao, Minsi Chen, Chunhua Gu, Shouzhou Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430074 Peoples R China Hunan Inst Geomat Sci & Technol HNCORS Data Ctr Changsha 410007 Peoples R China Wuhan Univ GNSS Res Ctr Wuhan 430079 Peoples R China Chinese Acad Surveying & Mapping Inst Geodesy & GNSS Nav Beijing 100083 Peoples R China

With the rapid development of the ground infrastructure as CORS and mobile communication stations, the high precision LBS expand from the limited fields to the public. The comprehensive LBS platforms which meet the demands such as multi-precision level, massive user and desirable scalability, become critical for the public applications. In this paper, a new high precision LBS architecture based on GNSS CORS network is presented. The platform is deployed in the cloud computational environment. It is divided into two parts: data processing and allocation system individually. The virtual grids differential corrections are involved to optimize the real-time CORS stations data processing. Besides, the API/SDK module is introduced as a new service mode, which integrates the meter, decimeter, centimeter level LBS applications, respectively realized by the coordinates, pseudo range and carrier phase differential. With the daily needs of HNCORS network, the platform "SoBDS" is established. The experiments for decimeter level example shows that, the platform could support one million users, and it is compatible and scalable. The real-time positioning accuracy is +/- 0.425m and +/- 0.436m in east and north. The total accuracy is +/- 0.612m and +/- 0.773m in horizontal and vertical direction.

关键词： Global positioning system global navigation satellite system continuously operating reference stations location based service platform RTCM protocol application programming interface software development kit

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GPU computing performance analysis on matrix multiplication

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JOURNAL OF ENGINEERING-JOE 2019年第23期2019卷 9043-9048页

作者： Huang, Zhibin Ma, Ning Wang, Shaojun Peng, Yu Harbin Inst Technol Sch Elect & Informat Engn Harbin 150080 Peoples R China

The machine learning has been widely used in intelligent data mining. The high-computational complexity of machine learning and huge data volume present challenges to computing platforms. Graphics processor unit (GPU) provides powerful computing support for machine learning but shows different performances under different computing scales and/or different development methods. Analysing the performance of GPUs in different application scenarios helps to improve computing performance. In this study, the matrix multiplication, which is a common and time-consuming computation operation in machine learning, is performed on different data scales and different development methods to analyse the relationship between GPU computing performance with matrix scale and development methods. The experimental data shows that the performance of GPU is not much improved compared with the central processing unit in small-scale data calculation. Also, using a high-level application programming interface for GPU development is less computing-efficient than the GPU programming language computes unified device architecture C.

关键词： computational complexity application program interfaces data mining matrix multiplication parallel architectures graphics processing units learning (artificial intelligence) microprocessor chips GPU programming language GPU computing performance analysis matrix multiplication machine learning graphics processor unit data mining computational complexity time-consuming computation operation central processing unit application programming interface C architecture

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