Journal articles: 'Real-Time Computing System'

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Malgaonkar, Saurabh, Paulami Shah, Rishabh Jhaveri, and Tejas Hirave. "Real Time e-Learning System using Cloud Computing." International Journal of Computer Applications 123, no. 3 (August 18, 2015): 19–23. http://dx.doi.org/10.5120/ijca2015905271.

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Mellichamp, Duncan, Dave Bedworth, Odd Pettersen, Peter Rony, Lew Bezanson, Walter Higgins, and Granino Korn. "Real-Time Computing And the Engineering Support System." IEEE Micro 5, no. 5 (October 1985): 27–35. http://dx.doi.org/10.1109/mm.1985.304601.

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Liou Chu, and ShihJung Wu. "A Real-time Fire Evacuation System with Cloud Computing." Journal of Convergence Information Technology 7, no. 7 (April 30, 2012): 208–15. http://dx.doi.org/10.4156/jcit.vol7.issue7.26.

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Christini, David J., Kenneth M. Stein, Steven M. Markowitz, and Bruce B. Lerman. "Practical Real-Time Computing System for Biomedical Experiment Interface." Annals of Biomedical Engineering 27, no. 2 (March 1999): 180–86. http://dx.doi.org/10.1114/1.185.

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Zhang, Bingda, Xianglong Jin, Sijia Tu, Zhao Jin, and Jie Zhang. "A New FPGA-Based Real-Time Digital Solver for Power System Simulation." Energies 12, no. 24 (December 8, 2019): 4666. http://dx.doi.org/10.3390/en12244666.

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Considering the rational use of field programmable gate array (FPGA) resources, this paper proposes a new FPGA-based real-time digital solver (FRTDS) for power system simulation. Based on the relationship between the number of computing components, the operating frequency, and the pipeline length, the best selection principle is given. By analyzing the implementation method of the Multi-Port Read/Write Circuit, the computing formula of the Look-Up-Table (LUT) consumption was derived. Given the excessive use of LUTs in the original computing components, the computing components were assembled in a single typical arithmetic expression of the power system simulation program, as the basic computing formula was characterized by a subset of the typical computing formula and multiple uses of the same variable. Data communication between different computing components was realized by using Multi-Port Input Circuits that share some outputs of read controller, and Multi-Port Output Circuits, which share some outputs of computing cores. According to the test results of original FRTDS and new FRTDS, it was found that the solution proposed in this paper had a shorter ideal simulation time and a higher parallel computing capability, which was very suitable for real-time digital simulation of power systems.

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Kimura, Mitsutaka, Mitsuhiro Imaizumi, and Toshio Nakagawa. "Replication Policy of Real-Time Distributed System for Cloud Computing." International Journal of Reliability, Quality and Safety Engineering 22, no. 05 (October 2015): 1550024. http://dx.doi.org/10.1142/s0218539315500242.

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Recently, cloud computing has been widely used for the purpose of protecting client data on the Internet [A. Weiss, Computing in the clouds, netWorker11 (2007) 16–25; M. Armbrust et al., Above the clouds: A Berkeley view of cloud computing, Technical Report UCV/EECS-2009-28, University of California at Berkeley (2009)]. But when a client receives network service, response time may be slow because the data center is located in a remote place. In order to solve the problem, real-time distributed systems for cloud computing has been proposed [M. Okuno, D. Ito, H. Miyamoto, H. Aoki, Y. Tsushima and T. Yazaki, A study on distributed information and communication processing architecture for next generation cloud system, IEICE Tech. Report109(A48) (2010) 241–246; M. Okuno, S. Tsutsumi and T. Yazaki, A study of high available distributed network processing technique for next generation cloud system, IEICE Tech. Report111(8) (2011) 25–30; S. Yamada, J. Marukawa, D. Ishii, S. Okamoto and N. Yamanaka, A study of parallel transmission technique with GMPLS in intelligent cloud network, IEICE Tech. Report109(455) (2010) 51–56]. The cloud computing system consists of some intelligent nodes as well as a data center. The data center manages all client data. The intelligent node provides client service near clients. It enables to provide client service at short response time [M. Okuno, D. Ito, H. Miyamoto, H. Aoki, Y. Tsushima and T. Yazaki, A study on distributed information and communication processing architecture for next generation cloud system, IEICE Tech. Report109(448) (2010) 241–246]. We considered the reliability model of distributed information processing for cloud computing, derived cost effectiveness and discussed the optimal replication interval to minimize it [M. Kimura, M. Imaizumi and T. Nakagawa, Reliability modeling of distributed information processing for cloud computing, in Proc. 20th ISSAT Int. Conf. Reliability and Quality in Design (2014), pp. 183–187]. Authors had dealt with the server system with one failure mode. In this paper, we consider the reliability model of a real-time distributed system with n intelligent nodes and formulate a stochastic model of the server system with n intelligent nodes for changing the other normal intelligent node at failure. We derive the expected numbers of the replication and of updating the client data. Further, we derive the expected cost and discuss an optimal replication interval to minimize it. Next, we derive the cost effectiveness and discuss an optimal number of intelligent nodes to minimize it.

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Lee, Seung-Wook, Jong-Tae Kim, Bong-Ki Sohn, Keon-Myung Lee, Jun-Dong Keon-Myung, Jee-Hyung Lee, and Jae-Wook Jeon. "Real-Time Rule-Based System Architecture for Context-Aware Computing." Journal of Korean Institute of Intelligent Systems 14, no. 5 (August 1, 2004): 587–92. http://dx.doi.org/10.5391/jkiis.2004.14.5.587.

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Bychkov, V., and N. Dembitsky. "Real-time distributed computing system for modeling of physical processes." Journal of Physics: Conference Series 1560 (June 2020): 012069. http://dx.doi.org/10.1088/1742-6596/1560/1/012069.

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Lukoyanov, E. V., and A. M. Gruzlikov. "Hierarchical diagnostic model synthesis for dataflow real-time computing system." Scientific and Technical Journal of Information Technologies, Mechanics and Optics 20, no. 5 (October 1, 2020): 677–82. http://dx.doi.org/10.17586/2226-1494-2020-20-5-677-682.

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Gradolewski, Dawid, Dawid Maslowski, Damian Dziak, Bartosz Jachimczyk, Siva Teja Mundlamuri, Chandran G. Prakash, and Wlodek J. Kulesza. "A Distributed Computing Real-Time Safety System of Collaborative Robot." Elektronika ir Elektrotechnika 26, no. 2 (April 25, 2020): 4–14. http://dx.doi.org/10.5755/j01.eie.26.2.25757.

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Robotization has become common in modern factories due to its efficiency and cost-effectiveness. Lots of robots and manipulators share their workspaces with humans what could lead to hazardous situations causing health damage or even death. This article presents a real-time safety system applying the distributed computing paradigm for a collaborative robot. The system consists of detection/sensing modules connected with a server working as decision-making system. Each configurable sensing module pre-processes vision information and then sends to the server the images cropped to new objects extracted from a background. After identifying persons from the images, the decision-making system sends a request to the robot to perform pre-defined action. In the proposed solution, there are indicated three safety zones defined by three different actions on a robot motion. As identification method, state-of-the-art of Machine Learning algorithms, the Histogram of Oriented Gradients (HOG), Viola-Jones, and You Only Look Once (YOLO), have been examined and presented. The industrial environment tests indicated that YOLOv3 algorithm outperformed other solutions in terms of identification capabilities, false positive rate and maximum latency.

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KIM, K. H. (KANE). "REAL-TIME OBJECT-ORIENTED DISTRIBUTED SOFTWARE ENGINEERING AND THE TMO SCHEME." International Journal of Software Engineering and Knowledge Engineering 09, no. 02 (April 1999): 251–76. http://dx.doi.org/10.1142/s0218194099000164.

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Real-time (RT) object-oriented (OO) distributed computing is a form of RT distributed computing realized with a distributed computer system structured in the form of an object network. Several approaches proposed in recent years for extending the conventional object structuring scheme to suit RT applications, are briefly reviewed. Then the approach to RT OO distributed computing which the author and his collaborators have been establishing in recent years will be reviewed in more detail. The approach named the TMO (Time-triggered Message-triggered Object) structuring scheme was formulated with the goal of instigating a quantum productivity jump in the design of complex real-time computing systems (RTCS's). The TMO scheme is intended to facilitate the pursuit of a new paradigm in designing RTCS's which is to realize real-time computing with a common and general design style that does not alienate the main-stream computing industry and yet to allow system engineers to confidently produce certifiable RTCS's for safety-critical applications. The TMO structuring scheme is a syntactically simple but semantically powerful extension of the conventional object structuring approaches and as such, its support tools can be based on various well-established OO programming languages such as C++ and JAVA and on ubiquitous commercial RT operating system kernels. The scheme enables a great reduction of the designer's efforts in guaranteeing timely service capabilities of application systems. Also, the scheme is applicable to structuring of not only complex distributed RTCS's but also application environment descriptors/simulators and requirement specifications.

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Guo, Jiang, Jun Cheng, Yu Guo, and Jian Xin Pang. "A Real-Time Dynamic Gesture Recognition System." Applied Mechanics and Materials 333-335 (July 2013): 849–55. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.849.

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In this paper, we present a dynamic gesture recognition system. We focus on the visual sensory information to recognize human activity in form of hand movements from a small, predefined vocabulary. A fast and effective method is presented for hand detection and tracking at first for the trajectory extraction. A novel trajectory correction method is applied for simply but effectively trajectory correction. Gesture recognition is achieved by means of a matching technique by determining the distance between the unknown input direction code sequence and a set of previously defined templates. A dynamic time warping (DTW) algorithm is used to perform the time alignment and normalization by computing a temporal transformation allowing the two signals to be matched. Experiment results show our proposed gesture recognition system achieve well result in real time.

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Sun, Qi Qiang, Wei Zhou, Li Xin Li, Jing Huai Lin, Fang Chun Di, and Qiao Yun Xie. "Design of Distributed Parallel Real-Time Database for Power Grid Dispatching System." Advanced Materials Research 816-817 (September 2013): 557–61. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.557.

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In order to make the real time database more suitable for the computing features in power system, this paper will study the design and architecture of distributed and parallel real-time database. A mapping table from table file to machine nodes is established, and meta-data management system is used to store and manage the mapping table to meet the characteristics of high concurrent access. The whole network computation can access the unified interface provided by the real-time database. The data is retrieved and collected through each node. Experimental results show that the systems designed can meet the computing requirements of a unified whole network.

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Bin, Qi, Sun Xiao Ming, Pei Eujin, and Liu Bing Jian. "Virtual Clay Prototyping System – A Framework for Real-Time Modeling." International Journal of Online Engineering (iJOE) 11, no. 5 (September 24, 2015): 24. http://dx.doi.org/10.3991/ijoe.v11i5.4798.

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In order to provide users a real-time force-feedback immersive virtual modelling environment, powerful computing capabilities are often needed. As this potentially results in a calculation bottleneck, virtual modelling scenes are often delayed and resulting in a poor user experience. In this paper, the authors present a novel approach to improve the calculation speed for the volume pixel (voxel) amount of force feedback generated based on the amount of pressure exerted on the ‘virtual material’ per unit time. Results from the experiments reveal that this approach required less computing power, thereby offering a better user experience. This has been confirmed through a series of trials that investigated the amount of time students spent during sketching, physical modelling and virtual prototyping. Results found that the remapped virtual prototyping method was more effective than physical model in productivity in terms of time, and efficiency in terms of data conversion.

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Umek, Anton, and Anton Kos. "The Role of High Performance Computing and Communication for Real-Time Biofeedback in Sport." Mathematical Problems in Engineering 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/4829452.

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This paper studies the main technological challenges of real-time biofeedback in sport. We identified communication and processing as two main possible obstacles for high performance real-time biofeedback systems. We give special attention to the role of high performance computing with some details on possible usage of DataFlow computing paradigm. Motion tracking systems, in connection with the biomechanical biofeedback, help in accelerating motor learning. Requirements about various parameters important in real-time biofeedback applications are discussed. Inertial sensor tracking system accuracy is tested in comparison with a high performance optical tracking system. Special focus is given on feedback loop delays. Real-time sensor signal acquisitions and real-time processing challenges, in connection with biomechanical biofeedback, are presented. Despite the fact that local processing requires less energy consumption than remote processing, many other limitations, most often the insufficient local processing power, can lead to distributed system as the only possible option. A multiuser signal processing in football match is recognised as an example for high performance application that needs high-speed communication and high performance remote computing. DataFlow computing is found as a good choice for real-time biofeedback systems with large data streams.

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Zhang, Yangan, Guichen Chen, Hang Du, Xueguang Yuan, Michel Kadoch, and Mohamed Cheriet. "Real-Time Remote Health Monitoring System Driven by 5G MEC-IoT." Electronics 9, no. 11 (October 22, 2020): 1753. http://dx.doi.org/10.3390/electronics9111753.

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Telemedicine over Internet of Things (IoT) generates an unprecedented amount of data, which further requires transmission, analysis, and storage. Deploying cloud computing to handle data of this magnitude will introduce unacceptable data analysis latency and high storage costs. Thus, mobile edge computing (MEC) deployed between the cloud and users, which is close to the nodes of data generation, can tackle these problems in 5G scenarios with the help of artificial intelligence. This paper proposes a telemedicine system based on MEC and artificial intelligence for remote health monitoring and automatic disease diagnosis. The integration of different technologies such as computers, medicine, and telecommunications will significantly improve the efficiency of patient treatment and reduce the cost of health care.

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Koloba Malubaya, Brian William. "Real-time Parking Information System with Cloud Computing Open Architecture Approach." International Journal of Emerging Trends in Engineering Research 8, no. 1 (January 15, 2020): 18–22. http://dx.doi.org/10.30534/ijeter/2020/04812020.

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Aiello, S., A. Anzalone, M. Bartolucci, G. Cardella, S. Cavallaro, E. DeFilippo, S. Feminò, et al. "Data acquisition and real-time computing by a DSP-based system." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 136-138 (March 1998): 1172–76. http://dx.doi.org/10.1016/s0168-583x(97)00810-0.

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Fawwaz, Dzaky Zakiyal, and Sang-Hwa Chung. "Real-Time and Robust Hydraulic System Fault Detection via Edge Computing." Applied Sciences 10, no. 17 (August 27, 2020): 5933. http://dx.doi.org/10.3390/app10175933.

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We consider fault detection in a hydraulic system that maintains multivariate time-series sensor data. Such a real-world industrial environment could suffer from noisy data resulting from inaccuracies in hardware sensing or external interference. Thus, we propose a real-time and robust fault detection method for hydraulic systems that leverages cooperation between cloud and edge servers. The cloud server employs a new approach that includes a genetic algorithm (GA)-based feature selection that identifies feature-to-label correlations and feature-to-feature redundancies. A GA can efficiently process large search spaces, such as solving a combinatorial optimization problem to identify the optimal feature subset. By using fewer important features that require transmission and processing, this approach reduces detection time and improves model performance. We propose a long short-term memory autoencoder for a robust fault detection model that leverages temporal information on time-series sensor data and effectively handles noisy data. This detection model is then deployed at edge servers that provide computing resources near the data source to reduce latency. Our experimental results suggest that this method outperforms prior approaches by demonstrating lower detection times, higher accuracy, and increased robustness to noisy data. While we have a 63% reduction of features, our model obtains a high accuracy of approximately 98% and is robust to noisy data with a signal-to-noise ratio near 0 dB. Our method also performs at an average detection time of only 9.42 ms with a reduced average packet size of 179.98 KB from the maximum of 343.78 KB.

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Nairz, A., L. Goossens, M. Branco, D. Cameron, P. Salgado, D. Barberis, K. Bos, and G. Poulard. "ATLAS computing system commissioning: real-time data processing and distribution tests." Journal of Physics: Conference Series 110, no. 9 (May 1, 2008): 092019. http://dx.doi.org/10.1088/1742-6596/110/9/092019.

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Lin, Hua Yi, Jiann Gwo Doong, Meng Yen Hsieh, and Kuan Ching Li. "A real time vehicle management system implementation on cloud computing platform." International Journal of High Performance Computing and Networking 10, no. 3 (2017): 168. http://dx.doi.org/10.1504/ijhpcn.2017.084245.

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Li, Kuan Ching, Jiann Gwo Doong, Meng Yen Hsieh, and Hua Yi Lin. "A real time vehicle management system implementation on cloud computing platform." International Journal of High Performance Computing and Networking 10, no. 3 (2017): 168. http://dx.doi.org/10.1504/ijhpcn.2017.10005139.

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Zhuang, Yu Feng, and Yang Yang. "3G-Based Specialty Vehicles Real-Time Monitoring System." Applied Mechanics and Materials 513-517 (February 2014): 871–75. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.871.

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At present, the wireless communications and mobile computing technology are relatively well developed. This article proposes a new special vehicle monitoring system in order to meet the needs of intelligent transportation industry. The monitoring system for special transport vehicles is designed to pass a full range of real-time monitoring to safeguard the vehicle transport of dangerous or valuable goods in transit security. The system has two main subsystems, including vehicle terminal subsystem and server-side subsystem. Wherein, the main function of the vehicle terminal subsystem is to all-round monitoring the specialty vehicles, including video, vehicle status, goods status and environment status etc. The terminal ensures the effectiveness of monitoring by using a 3G-based hybrid network access. The server-side subsystem is primarily responsible for information collection/processing/storage, providing monitoring display and publishing the WEB services which supported logistics information management systems and real-time traffic information. In practice, this article designs and implements a prototype system based on a natural gas transport fleet.

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Wu, Yao, Long Zheng, Brian Heilig, and Guang R. Gao. "HAMR: A dataflow-based real-time in-memory cluster computing engine." International Journal of High Performance Computing Applications 31, no. 5 (October 10, 2016): 361–74. http://dx.doi.org/10.1177/1094342016672080.

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As the attention given to big data grows, cluster computing systems for distributed processing of large data sets become the mainstream and critical requirement in high performance distributed system research. One of the most successful systems is Hadoop, which uses MapReduce as a programming/execution model and takes disks as intermedia to process huge volumes of data. Spark, as an in-memory computing engine, can solve the iterative and interactive problems more efficiently. However, currently it is a consensus that they are not the final solutions to big data due to a MapReduce-like programming model, synchronous execution model and the constraint that only supports batch processing, and so on. A new solution, especially, a fundamental evolution is needed to bring big data solutions into a new era. In this paper, we introduce a new cluster computing system called HAMR which supports both batch and streaming processing. To achieve better performance, HAMR integrates high performance computing approaches, i.e. dataflow fundamental into a big data solution. With more specifications, HAMR is fully designed based on in-memory computing to reduce the unnecessary disk access overhead; task scheduling and memory management are in fine-grain manner to explore more parallelism; asynchronous execution improves efficiency of computation resource usage, and also makes workload balance across the whole cluster better. The experimental results show that HAMR can outperform Hadoop MapReduce and Spark by up to 19x and 7x respectively, in the same cluster environment. Furthermore, HAMR can handle scaling data size well beyond the capabilities of Spark.

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Kulkarni, Nachiket, S. V. N. L. Lalitha, and Sanjay A. Deokar. "Real time control and monitoring of grid power systems using cloud computing." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 2 (April 1, 2019): 941. http://dx.doi.org/10.11591/ijece.v9i2.pp941-949.

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The use of grid power systems based on the combinations of various electrical networks, information technology, and communication layers called as Smart Grid systems. The technique of smart grid suppressed the problems faced by conventional grid systems such as inefficient energy management, improper control actions, grid faults, human errors, etc. The recent research on smart grid provides the approach for the real-time control and monitoring of grid power systems based on bidirectional communications. However, the smart grid is yet to improve regarding efficiency, energy management, reliability, and cost-effectiveness by considering its real-time implementation. In this paper, we present the real-time design of efficient monitoring and control of grid power system using the remote cloud server. We utilized the remote cloud server to fetch, monitor and control the real-time power system data to improve the universal control and response time. The proper hardware panel designed and fabricated to establish the connection with the grid as well as remote cloud users. The authenticated cloud users are provisioned to access and control the grid power system from anywhere securely. For the user authentication, we proposed the novel approach to secure the complete smart grid system. Finally, we demonstrated the effectiveness of real-time monitoring and control of the grid power method with the use of structure of practical framework.

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Li, Li Xin, Wei Zhou, Qi Qiang Sun, Jiao Dai, Ji Zhong Han, and Yang Liu. "Applications of Distributed Parallel Real Time Database on Power Grid." Advanced Materials Research 816-817 (September 2013): 488–92. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.488.

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In order to make the real time database more suitable for the computing features, this article points to the distributed and parallel real time database design and architecture. First, a mapping table from table file to machine nodes is established, and then can use meta-data management system to store and manage the mapping table to meet the characteristics of high concurrent access. The whole network computation can access the unified interface provided by the real-time database, retrive data from each node, then collect the data. Experimental results show that this study and the systems designed can meet the computing requirements of a unified whole network.

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Kumar, Anish, and Thangadurai N. "Laser Based Real Time Antenna Pointing Measurement System." International Journal of Engineering & Technology 7, no. 3.12 (July 20, 2018): 28. http://dx.doi.org/10.14419/ijet.v7i3.12.15857.

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The antenna pointing system is very important to obtain an optimum received signal level. To achieve it, presenting the implication of laser beam radiated emission requirements and how they state for pointing measurement system, its impact on design, verification and testing for the antenna pointing system. The antenna pointing system is developed by using array of linear light sensors, crosshair laser weapon, where the light sensors are mounted on the board and laser weapon putted on the antenna mechanism. On the rotator system, composed by using 2 gears and 2 DC motors with customized frames. For collecting the sensors data using ProASIC3 FPGA fabric and finding the numbers and which sensors has been active during the emitting period and 32-bit ARM Cortex-M3 processor take account into the pointing measurement system to computing the pointing and pointing error. At the end, the final step is building a User Graphical Interface on PC to show the output of the antenna pointing.

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Li, Jie, Rui Feng Guo, and Zhi Xiang Shao. "Real-Time Model Building of CNC System and its Schedulable Analysis." Advanced Materials Research 179-180 (January 2011): 220–25. http://dx.doi.org/10.4028/www.scientific.net/amr.179-180.220.

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Task scheduling is an important research topic of real-time systems. Compared with the common real-time systems, CNC system has its own features. In this paper, we propose an adaptive task scheduling model for CNC system and analyze its schedulability. The model is suitable to the uncertainty of open computing environment and can accept the running of different types of tasks. It can compute band changes according to the latest changes of system resources and task requirements. It adjusts tasks’ priorities adaptively and makes the system run in optimal real-time performance. On the basis of CNC system, we will further optimize the model by studying the characteristics of periodic tasks and scheduling time overhead. Finally, this model will be used in practical CNC system.

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Matsuo, K., Y. Tanaka, L. F. G. Sarmenta, T. Nakai, and E. Bagarinao. "Enabling On-demand Real-time Functional MRI Analysis Using Grid Technology." Methods of Information in Medicine 44, no. 05 (2005): 665–73. http://dx.doi.org/10.1055/s-0038-1634023.

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Summary Objectives: The analysis of brain imaging data such as functional MRI often requires considerable computing resources, which in most cases are not readily available in many medical imaging facilities. This lack of computing power makes it difficult for researchers and medical practitioners alike to perform on-site analysis of the generated data. This paper presents a system that is capable of analyzing functional MRI data in real time with results available within seconds after data acquisition. Methods: The system employs remote computational servers to provide the necessary computing power. System integration is accomplished by an accompanying software package, which includes fMRI analysis tools, data transfer routines, and an easy-to-use graphical user interface. The remote analysis is transparent to the user as if all computations are performed locally. Results: The use of PC clusters in the analysis of fMRI data significantly improved the performance of the system. Simulation runs fully achieved real-time performance with a total processing time of 1.089 s per image volume (64 x 64 x 30 in size), much less than the per volume acquisition time set to 3.0 s. Conclusions: The results show the feasibility of using remote computational resources to enable on-demand real-time fMRI capabilities to imaging sites. It also offers the possibility of doing more intensive analysis even if the imaging site doesn’t have the necessary computing resources.

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Zheng, Junjun, Hiroyuki Okamura, and Tadashi Dohi. "Reliability Importance of Components in a Real-Time Computing System with Standby Redundancy Schemes." International Journal of Mathematical, Engineering and Management Sciences 3, no. 2 (June 1, 2018): 64–89. http://dx.doi.org/10.33889/ijmems.2018.3.2-007.

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Component importance analysis is to measure the effect on system reliability of component reliabilities, and is used to the system design from the reliability point of view. On the other hand, to guarantee high reliability of real-time computing systems, redundancy has been widely applied, which plays an important role in enhancing system reliability. One of commonly used type of redundancy is the standby redundancy. However, redundancy increases not only the complexity of a system but also the complexity of associated problems such as common-mode error. In this paper, we consider the component importance analysis of a real-time computing system with warm standby redundancy in the presence of Common-Cause Failures (CCFs). Although the CCFs are known as a risk factor of degradation of system reliability, it is difficult to evaluate the component importance measures in the presence of CCFs analytically. This paper introduces a Continuous-Time Markov Chain (CTMC) model for real-time computing system, and applies the CTMC-based component-wise sensitivity analysis which can evaluate the component importance measures without any structure function of system. In numerical experiments, we evaluate the effect of CCFs by the comparison of system performance measure and component importance in the case of system without CCF with those in the case of system with CCFs. Also, we compare the effect of CCFs on the system in warm and hot standby configurations.

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Zhong, Wei Zhu, Ya Ping Wang, and Rong Sheng Lv. "With DGPS-RTK Terminal Yard Cranes Real-Time Operating System." Advanced Materials Research 748 (August 2013): 815–19. http://dx.doi.org/10.4028/www.scientific.net/amr.748.815.

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This paper introduces the intelligent controlling solution of Yard Cranes (YCs, RTG) in the container terminal production process. The Computing, Communication and Controlling Technology (CCCT) play the important role in this port equipment rebuilding. The Terminal Yard Cranes Real-time Operating System (CYCROS) is able to solve the running trail yaw and working loose problems etc. The framework of Real-time Operating System and DGPS-RTK work principle in the solution as well as application case in Tianjin port are showed in this article.

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Monroy, Carmen, Ricardo Campa, and Rafael Kelly. "An application of real-time control systems to robotics." Robotica 19, no. 3 (April 25, 2001): 323–29. http://dx.doi.org/10.1017/s0263574700003167.

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This paper illustrates basic concepts of real-time control systems through the application of a real-time single-processor computing environment for the control of a robotic arm. The paper describes elements for the selection of the real-time architecture, the control algorithm and the graphical user interface. The system provides an opportunity for users to verify the robot performance by changing on-line the controller parameters and the shape of the desired motion.

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Liu, Xin, Da Jun Sun, Ting Ting Teng, and Yuan Tian. "FPGA Implement of Multi-Channel Real-Time Correlation Processing System." Applied Mechanics and Materials 303-306 (February 2013): 1925–29. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.1925.

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The traditional real-time correlation processing system in FPGA is implemented in parallel mode. It has disadvantages such as high FPGA resource-consuming, low efficiency and poor flexibility. A time-multiplexed processing architecture takes NIOS processor as system controller, connected with preprocessing module, sliding-correlation processor and memories by Avalon data bus. The transmission of large data block out of sliding-correlation processor employs DMA method for its controlling flexibility, the data transmission between computing units and memory units within the processor employs directly memory access to minimum time delay.

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Patra, Prasenjit Kumar, Harshpreet Singh, Rajwinder Singh, Saptarshi Das, Nilanjan Dey, and Anghel Drugarin Cornelia Victoria. "Replication and Resubmission Based Adaptive Decision for Fault Tolerance in Real Time Cloud Computing." International Journal of Service Science, Management, Engineering, and Technology 7, no. 2 (April 2016): 46–60. http://dx.doi.org/10.4018/ijssmet.2016040104.

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Cloud computing an adoptable technology is the upshot evolution of on demand service in the computing epitome of immense scale distributed computing. With the raising asks and welfares of cloud computing infrastructure, society can take leverage of intensive computing capability services and scalable, virtualized vicinity of cloud computing to carry out real time tasks executed on a remote cloud computing node. Due to the indeterminate latency and minimal control over computing node, sway the reliability factor. Therefore, there is a raise of requisite for fault tolerance to achieve reliability in the real time cloud infrastructure. In this paper, a model which provides fault tolerance named “Replication and resubmission based adaptive decision for fault tolerance in real-time cloud computing (RRADFTRC)” for real time cloud computing is projected with result. In the projected model, the system endure the faults and makes the adaptive decision on the basis of proper resource allocation of tasks with a new style of approach in real time cloud vicinity.

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Dubey, Jigyasu. "Identification of Efficient Peers in P2P Computing System for Real Time Applications." International Journal of Peer to Peer Networks 3, no. 6 (November 30, 2012): 1–11. http://dx.doi.org/10.5121/ijp2p.2012.3601.

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Teng, Yunhao, Jiapo Cui, and Wenrong Jiang. "Research on Application of Edge Computing in Real-time Environmental Monitoring System." Journal of Physics: Conference Series 2010, no. 1 (September 1, 2021): 012157. http://dx.doi.org/10.1088/1742-6596/2010/1/012157.

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Perneel, L., H. Fayyad-Kazan, L. Peng, F. Guan, and M. Timmerman. "Business Hypervisors for Real-time Applications." Engineering, Technology & Applied Science Research 5, no. 4 (August 17, 2015): 832–40. http://dx.doi.org/10.48084/etasr.568.

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System virtualization is one of the hottest trends in information technology today. It is not just another nice to use technology but has become fundamental across the business world. It is successfully used with many business application classes where cloud computing is the most visual one. Recently, it started to be used for soft Real-Time (RT) applications such as IP telephony, media servers, audio and video streaming servers, automotive and communication systems in general. Running these applications on a traditional system (Hardware + Operating System) guarantee their Quality of Service (QoS); virtualizing them means inserting a new layer between the hardware and the (virtual) Operating System (OS), and thus adding extra overhead. Although these applications’ areas do not always demand hard time guarantees, they require the underlying virtualization layer supports low latency and provide adequate computational resources for completion within a reasonable or predictable timeframe. These aspects are intimately intertwined with the logic of the hypervisor scheduler. In this paper, a series of tests are conducted on three hypervisors (VMware ESXi, Hyper-V server and Xen) to provide a benchmark of the latencies added to the applications running on top of them. These tests are conducted for different scenarios (use cases) to take into consideration all the parameters and configurations of the hypervisors’ schedulers. Finally, this benchmark can be used as a reference for choosing the best hypervisor-application combination.

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Chen, Liang, Yang Wang, Shi Wang Yang, Xue Ping Gu, and Yan Xu. "The Real-Time Interactive Smart Energy System Based on the Internet of Things and Cloud Computing." Advanced Materials Research 705 (June 2013): 584–89. http://dx.doi.org/10.4028/www.scientific.net/amr.705.584.

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A real-time interactive smart energy system is designed based on the internet of things and cloud computing, which is composed of Smart Meters, Smart Terminals, Smart Power Plugs and Cloud computing service system. Combining with Smart Gird property and the internet of things technology, the smart energy system provides the full range interaction of Power companies-Internet of things equipments-cooperation between the equipments. Meanwhile, the offline decision mode is supported by the expert system and the online decision mode is provided by the Cloud computing service system, making it both reliable and real-time in transaction processing. Eventually, the smart energy system can achieve real-time visualization, diversified interaction, smart interaction and scientific decision-making.

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Jiang, Chun Feng, and Wei Xu. "Research of Trust Model for File-Sharing System." Advanced Materials Research 989-994 (July 2014): 4755–58. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4755.

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In this paper, a trust model based on real-time behavior detection scheme was proposed in P2P file-sharing system. It solved the problems in computing trust value only by past performances and choosing service nodes improperly. It took real-time behavior detection both in trust computing and service choosing, improving the accuracy of the trust value and the rationality in service nodes choosing. The experimental results proved the advantage of this scheme.

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Zheng, S. Y., L. Gui, X. N. Wang, and D. Ma. "A real-time photogrammetry system based on embedded architecture." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5 (June 6, 2014): 633–38. http://dx.doi.org/10.5194/isprsarchives-xl-5-633-2014.

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In order to meet the demand of real-time spatial data processing and improve the online processing capability of photogrammetric system, a kind of real-time photogrammetry method is proposed in this paper. According to the proposed method, system based on embedded architecture is then designed: using FPGA, ARM+DSP and other embedded computing technology to build specialized hardware operating environment, transplanting and optimizing the existing photogrammetric algorithm to the embedded system, and finally real-time photogrammetric data processing is realized. At last, aerial photogrammetric experiment shows that the method can achieve high-speed and stable on-line processing of photogrammetric data. And the experiment also verifies the feasibility of the proposed real-time photogrammetric system based on embedded architecture. It is the first time to realize real-time aerial photogrammetric system, which can improve the online processing efficiency of photogrammetry to a higher level and broaden the application field of photogrammetry.

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Wu, Huifeng, Junjie Hu, Jiexiang Sun, and Danfeng Sun. "Edge Computing in an IoT Base Station System: Reprogramming and Real-Time Tasks." Complexity 2019 (March 5, 2019): 1–10. http://dx.doi.org/10.1155/2019/4027638.

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There are millions of base stations distributed across China, each containing many support devices and monitoring sensors. Conventional base station management systems tend to be hosted in the cloud, but cloud-based systems are difficult to reprogram and performing tasks in real-time is sometimes problematic, for example, sounding a combination of alarms or executing linked tasks. To overcome these drawbacks, we propose a hybrid edge-cloud IoT base station system, called BSIS. This paper includes a theoretical mathematical model that demonstrates the dynamic characteristics of BSIS along with a formulation for implementing BSIS in practice. Embedded programmable logic controllers serve as the edge nodes; a dynamic programming method creates a seamless integration between the edge nodes and the cloud. The paper concludes with a series of comprehensive analyses on scalability, responsiveness, and reliability. These analyses indicate a possible 60% reduction in the number of alarms, an edge response time of less than 0.1s, and an average downtime ratio of 0.66%.

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Saoudi, El Mehdi, Abderrahmane Adoui El Ouadrhiri, Said Jai Andaloussi, Othmane El Warrak, and Abderrahim Sekkaki. "Content Based Video Retrieval by Using Distributed Real-Time System Based on Storm." International Journal of Embedded and Real-Time Communication Systems 10, no. 4 (October 2019): 60–80. http://dx.doi.org/10.4018/ijertcs.2019100104.

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Time processing is a challenging issue for content-based video retrieval systems, especially when the process of indexing, classifying and retrieving desired and relevant videos is from a huge database. A CBVR system called bounded coordinate of motion histogram (BCMH) has been implemented as a case study. The BCMH offline step requires a long time to complete the learning phase, and the online step falls short in addressing the real-time video processing. To overcome these drawbacks, this article presents a batch-oriented computing based on Apache Hadoop to improve the time processing for the offline step, and a real-time oriented computing based on Apache Storm topologies to achieve a real-time response for the online step. The proposed approach is tested on the HOLLYWOOD2 dataset and the obtained results demonstrate reliability and efficiency of the proposed method.

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Rhodes, Oliver, Luca Peres, Andrew G. D. Rowley, Andrew Gait, Luis A. Plana, Christian Brenninkmeijer, and Steve B. Furber. "Real-time cortical simulation on neuromorphic hardware." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2164 (December 23, 2019): 20190160. http://dx.doi.org/10.1098/rsta.2019.0160.

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Real-time simulation of a large-scale biologically representative spiking neural network is presented, through the use of a heterogeneous parallelization scheme and SpiNNaker neuromorphic hardware. A published cortical microcircuit model is used as a benchmark test case, representing ≈1 mm 2 of early sensory cortex, containing 77 k neurons and 0.3 billion synapses. This is the first hard real-time simulation of this model, with 10 s of biological simulation time executed in 10 s wall-clock time. This surpasses best-published efforts on HPC neural simulators (3 × slowdown) and GPUs running optimized spiking neural network (SNN) libraries (2 × slowdown). Furthermore, the presented approach indicates that real-time processing can be maintained with increasing SNN size, breaking the communication barrier incurred by traditional computing machinery. Model results are compared to an established HPC simulator baseline to verify simulation correctness, comparing well across a range of statistical measures. Energy to solution and energy per synaptic event are also reported, demonstrating that the relatively low-tech SpiNNaker processors achieve a 10 × reduction in energy relative to modern HPC systems, and comparable energy consumption to modern GPUs. Finally, system robustness is demonstrated through multiple 12 h simulations of the cortical microcircuit, each simulating 12 h of biological time, and demonstrating the potential of neuromorphic hardware as a neuroscience research tool for studying complex spiking neural networks over extended time periods. This article is part of the theme issue ‘Harmonizing energy-autonomous computing and intelligence’.

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Mora Mora, Higinio, David Gil, José Francisco Colom López, and María Teresa Signes Pont. "Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm." Mobile Information Systems 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/652462.

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The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.

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Shi, Peng, and Li Li. "Design of Network Analysis System Based on Stream Computing." Journal of Computational and Theoretical Nanoscience 14, no. 1 (January 1, 2017): 64–68. http://dx.doi.org/10.1166/jctn.2017.6125.

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The functions of the network analysis system include detection and analysis of network data stream. According to the results of the network analysis, we monitor the network accident and avoid the security risks. This can improve the network performance and increase the network availability. As the data flow in the network is constantly produced, the biggest characteristic of network analysis system is that it is a real-time system. Because of the high requirements of the network data analysis and network fault processing, the system requires very high processing efficiency of the real time data of network. Stream computing is a technique specifically for processing real-time data streams. Its idea is that the value of the data is reduced with the lapse of time, so as long as the data appearing, it must be processed as soon as possible. So we use the technology of stream computing to design network analysis system to meet the needs of real-time capability. Moreover, the stream computing framework has been widely welcomed in the field because of its good expansibility, ease of use and flexibility. In this paper, firstly, we introduce the characteristics of the data processing based on stream computing and the traditional data processing separately. We point out their difference and introduce the technique of stream computing. Then, we introduce the architecture of network analysis system designed base on the technique of stream computing. The architecture includes two main components that are logic processing layer and communication layer. We describe the characteristics of each component and functional characteristics in detail, and we introduce the system load balancing algorithm. Finally, by experiments, we verify the effectiveness of the system’s characteristics of dynamic expansion and load balancing.

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Juang, Jih Gau, and Ting Kai Liu. "Real Time Neural Network Control of a Twin Rotor System." Advanced Materials Research 271-273 (July 2011): 616–21. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.616.

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Real time intelligent control scheme that utilizes neural network to perform PID controller to control a twin rotor system is proposed. An experimental propeller setup called the twin rotor multi-input multi-output system (TRMS) is used in this study. The use of single neuron in PID control reduces system computing time that makes on-line learning and real time control feasible. The proposed control scheme can drive the TRMS to follow desired attitudes. The pitch angle and the azimuth angle in the condition of cross-coupled between vertical and horizontal axes is considered. Furthermore, the control scheme can overcome external disturbance. Simulation results show that the new approach can improve attitude tracking performance and the neural network-PID controller can work in real time.

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Huang, Chung Chi, Chung Lin Huang, Cong Hui Huang, and Sheng Fone Yang. "Design and Implementation of Cloud-Dust Based Intelligent System." Applied Mechanics and Materials 764-765 (May 2015): 872–76. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.872.

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In the paper, design and Implementation of cloud-dust based intelligent system is proposed. For achieving applications of intelligent system, such as records, surveillance, assessments, predictions, diagnosis, prescription, scheduling and fool-proofing checks, an architecture named Cloud-Dust is developed. The intelligent system is separated into the cloud system and the dust system. The dust system contains (1) Wireless sensors network (2) Features extraction circuits (3) Intelligent computing circuits (4) Embedded system. It can play a role as real-time preprocessor very well, just like an intelligent agent. However, the cloud system contains (1) Cloud database (2) Intelligent computing engine (3) Ubiquitous human-machine-interface. It can flexibly use computing resources and integrate information from many different dust systems. By the experiments, we can find the advantages of the cloud-dust based intelligent system. It meets the both needs of real-time and integration for intelligent systems. So it is necessary to develop the cloud-dust based system for design and implementation of the intelligent system.

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Sastry, Shivakumar, and S. S. Iyengar. "Real-Time Sensor-Actuator Networks." International Journal of Distributed Sensor Networks 1, no. 1 (February 2005): 17–34. http://dx.doi.org/10.1080/15501320490886314.

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Emerging technologies offer new paradigms for computation, control, collaboration, and communication. To realize the full potential of these technologies in industry, defense, and homeland security applications, it is necessary to exploit the real-time distributed computing capabilities of sensor-actuator networks. To reliably design and develop such networks, it is necessary to develop deeper insight into the underlying model for real-time computation and the infrastructure at the node level that supports this model. In this paper, we discuss a new node-level operating system and mechanisms necessary to deploy reliable applications. The overriding issue that guides the design of this operating system is quality of service metric called predictability. A sensor-actuator network is a distributed platform for integrated computation and control in real-time environments. The nodes in such a network are distinguished by being resource constrained. The power of the network arises from the interactions between simple nodes. Such a network extends the popular distributed sensor networks in several dimensions. After identifying a real-time model, we develop a notion of predictability for a sensor-actuator network. We discuss how the node-level operating system is designed in the resource-constrained environment. An efficient multithreading mechanism and scheduling strategy are required to ensure that local tasks are executed within jitter bounds and that end-to-end delays do not violate application constraints. Mechanisms to support communication, monitoring, safety, fault tolerance, programming, diagnosability, reconfiguration, composability, interoperability, and security are discussed.

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Kwad, A. M., D. Hanafi, R. Omar, and H. Abdul Rahman. "Development of system identification from traditional concepts to real-time soft computing based." IOP Conference Series: Materials Science and Engineering 767 (March 21, 2020): 012050. http://dx.doi.org/10.1088/1757-899x/767/1/012050.

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Tang, Jie, Shaoshan Liu, Liangkai Liu, Bo Yu, and Weisong Shi. "LoPECS: A Low-Power Edge Computing System for Real-Time Autonomous Driving Services." IEEE Access 8 (2020): 30467–79. http://dx.doi.org/10.1109/access.2020.2970728.

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Journal articles on the topic 'Real-Time Computing System'

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