Статті в журналах: "Dynamics, Distributed Computing"

1

Alistarh, Dan. "Distributed Computing Column 77 Consensus Dynamics." ACM SIGACT News 51, no. 1 (March 12, 2020): 57. http://dx.doi.org/10.1145/3388392.3388402.

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2

Duggan, Jim. "A distributed computing approach to system dynamics." System Dynamics Review 18, no. 1 (2002): 87–98. http://dx.doi.org/10.1002/sdr.228.

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3

Tang, Gang, Wei Jian Mi, Dao Fang Chang, Cheng Tao Wang, and Xue Ling Bai. "Distributed Computing for Mechanical Virtual Human." Advanced Materials Research 341-342 (September 2011): 695–99. http://dx.doi.org/10.4028/www.scientific.net/amr.341-342.695.

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To improve the efficiencies in kinematics, dynamics analysis and finite element (FE) calculation, distributed computing is used in the project of Chinese mechanical virtual human (CMVH). A three-dimensional (3D) musculoskeletal model of a male human and its finite element model have been constructed according to the male dataset of Chinese visible human (CVH). Many servers and software have been architected by using the method of distributed computing. Finally, a distributed computing platform by using these models to solving the parameters has been established. This distributed computing platform will provide wide applications in the areas such as medical engineering, robot design, physical and art education, sport, ergonomics and traffic accident analysis etc.

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4

Alnasir, Jamie. "Distributed Computing in a Pandemic." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 11, no. 1 (June 6, 2022): 19–43. http://dx.doi.org/10.14201/adcaij.27337.

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The current COVID-19 global pandemic caused by the SARS-CoV-2 betacoronavirus has resulted in over a million deaths and is having a grave socio-economic impact, hence there is an urgency to find solutions to key research challenges. Much of this COVID-19 research depends on distributed computing. In this article, I review distributed architectures -- various types of clusters, grids and clouds -- that can be leveraged to perform these tasks at scale, at high-throughput, with a high degree of parallelism, and which can also be used to work collaboratively. High-performance computing (HPC) clusters will be used to carry out much of this work. Several bigdata processing tasks used in reducing the spread of SARS-CoV-2 require high-throughput approaches, and a variety of tools, which Hadoop and Spark offer, even using commodity hardware. Extremely large-scale COVID-19 research has also utilised some of the world's fastest supercomputers, such as IBM's SUMMIT -- for ensemble docking high-throughput screening against SARS-CoV-2 targets for drug-repurposing, and high-throughput gene analysis -- and Sentinel, an XPE-Cray based system used to explore natural products. Grid computing has facilitated the formation of the world's first Exascale grid computer. This has accelerated COVID-19 research in molecular dynamics simulations of SARS-CoV-2 spike protein interactions through massively-parallel computation and was performed with over 1 million volunteer computing devices using the Folding@home platform. Grids and clouds both can also be used for international collaboration by enabling access to important datasets and providing services that allow researchers to focus on research rather than on time-consuming data-management tasks.

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SCHEININE, ALAN LOUIS. "PARALLEL COMPUTING AT CRS4." International Journal of Modern Physics C 04, no. 06 (December 1993): 1315–21. http://dx.doi.org/10.1142/s0129183193001038.

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An overview is given of parallel computing work being done at CRS4 (Centro di Ricerca, Sviluppo e Studi Superiori in Sardegna). Parallel computation projects include: parallelization of a simulation of the interaction of high energy particles with matter (GEANT), domain decomposition for numerical solution of partial differential equations, seismic migration for oil prospecting, finite-element structural analysis, parallel molecular dynamics, a C++ library for distributed processing of specific functions, and real-time visualization of a computer simulation that runs as distributed processes.

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6

Buch, I., M. J. Harvey, T. Giorgino, D. P. Anderson, and G. De Fabritiis. "High-Throughput All-Atom Molecular Dynamics Simulations Using Distributed Computing." Journal of Chemical Information and Modeling 50, no. 3 (March 3, 2010): 397–403. http://dx.doi.org/10.1021/ci900455r.

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7

Borgese, Gianluca, Calogero Pace, Pietro Pantano, and Eleonora Bilotta. "FPGA-Based Distributed Computing Microarchitecture for Complex Physical Dynamics Investigation." IEEE Transactions on Neural Networks and Learning Systems 24, no. 9 (September 2013): 1390–99. http://dx.doi.org/10.1109/tnnls.2013.2252924.

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8

Jaggard, Aaron D., Neil Lutz, Michael Schapira, and Rebecca N. Wright. "Dynamics at the Boundary of Game Theory and Distributed Computing." ACM Transactions on Economics and Computation 5, no. 3 (August 9, 2017): 1–20. http://dx.doi.org/10.1145/3107182.

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9

Wiredu, Gamel O., and Carsten Sørensen. "The dynamics of control and mobile computing in distributed activities." European Journal of Information Systems 15, no. 3 (June 2006): 307–19. http://dx.doi.org/10.1057/palgrave.ejis.3000577.

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10

Starostin, Igor, Sergey Khalyutin, Victoria Pavlova, and Elena Punt. "Distributed computing system for creating digital portraits of complex systems." MATEC Web of Conferences 341 (2021): 00046. http://dx.doi.org/10.1051/matecconf/202134100046.

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Various methods of operation of complex transport systems imply knowledge of mathematical models of their components. To obtain adequate models of such components, it is necessary to take into account the physical and chemical processes occurring in them. Previously, the authors developed a potential-flow method within the framework of modern nonequilibrium thermodynamics – a unified approach to the analysis and modeling of processes of various physical and chemical nature. In accordance with this approach, as well as with the methods of mechanics, the theory of electric and magnetic circuits, electrodynamics, etc., state functions for the properties of substances and the processes under consideration are set up to the experimentally studied constant coefficients. The system of equations of the considered processes dynamics is obtained from the given state functions. The desired model (digital portrait) of the considered component is constructed by numerical-analytical transformation of the dynamic equations system based on the use of experimental data. The need to automate the proposed method of obtaining digital portraits is due to its complexity and the need to process a large amount of data. An information and computing system is proposed, which implies the construction of a block diagram of the processes in the component under consideration (model-oriented approach). Modeling these processes using a block diagram at different values of unknown parameters allows us to approximate the model (digital portrait) a component based on the resulting set of output characteristic dynamics using machine learning libraries. Process modeling and further approximation of the model is parallelized. This paper is devoted to a distributed information-computing system that implements the creation of various complex systems digital portraits.

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11

Rasul A. AL WAILI, L. A. Abdul. "Effectual Approach for Cloud Data Center Security using Metaheuristic based Global Optimization." Journal of Education College Wasit University 1, no. 29 (January 16, 2018): 490–97. http://dx.doi.org/10.31185/eduj.vol1.iss29.166.

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Cloud Computing is emerging as one of the high performance and integrity aware area in the distributed and grid based computing environment. Enormous computing and technology based services are delivered and disseminated throughout the globe using cloud implementations because of increasing usage of technology products. As these products and devices are quite costly to purchase, cloud computing gives the option to hire the computing infrastructure with per usage base. As cloud computing is escalating by number of services, there are lots of issues regarding vulnerability and integrity in the data centers from where these cloud services are disseminated. This research manuscript presents and implements a unique and effectual approach for security of data centers using dynamic approach for encryption during communication and accessing the cloud services. The results in the projected novel approach are effective in terms of cost, complexity and overall performance. The projected novel approach is using nature inspired approach River formation dynamics Metaheuristic Approach for the enhancement of results and performance. Keywords – Cloud Computing, Cloud of Things, Nature Inspired Approach, Network Security, River formation dynamics Metaheuristic Approach

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12

Villanueva-Oller, J., L. Acedo, J. A. Moraño, and A. Sánchez-Sánchez. "Epidemic Random Network Simulations in a Distributed Computing Environment." Abstract and Applied Analysis 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/462801.

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We discuss a computational system following the paradigm of distributed computing, which will allow us to simulate the epidemic propagation in random networks with large number of nodes up to one million. This paradigm consists of a server that delivers tasks to be carried out by client computers. When the task is finished, the client sends the obtained results to the server to be stored until all tasks are finished and then ready to be analysed. Finally, we show that this technique allows us to disclose the emergence of seasonal patterns in the respiratory syncytial virus transmission dynamics which do not appear neither in smaller systems nor in continuous systems.

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13

Feoktistov, Alexander Gennadevich, Roman Olegovich Kostromin, Sergei Alexeevich Gorsky, Igor Vyacheslavovich Bychkov, Andrei Nikolaevitch Tchernykh, and Olga Yurevna Basharina. "Redundancy and Uncertainty-Based Algorithms for Computation Planning." Proceedings of the Institute for System Programming of the RAS 34, no. 1 (2022): 123–40. http://dx.doi.org/10.15514/ispras-2022-34(1)-9.

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Nowadays, the development and use of workflow-based applications (distributed applied software packages) are some of the key challenges in terms of preparing and carrying out large-scale scientific experiments in distributed environments with heterogeneous computing resources. The environment resources can be represented by clusters of personal computers, supercomputers, and private or public cloud platforms and differ in their computational characteristics. Moreover, the composition and characteristics of resources change in dynamics. Therefore, computations planning and resource allocation in the considered environments are important problems. In this regard, we propose new algorithms for computation planning taking into account redundancy and uncertainty in such distributed applied software packages. Compared to other algorithms of a similar purpose, the proposed algorithms use evaluations of workflow execution makespan obtained in the process of continuous integration, delivery, and deployment of applied software. The proposed algorithms provide the construction of redundant problem-solving schemes that allow us to adapt them to the dynamic characteristics of computational resources and improve distributed computing reliability. The algorithms are based on a theory of conceptual modeling computational processes. We demonstrate the process of constructing problem-solving schemes on model examples. In addition, we show the utility in using redundancy for increasing the distributed computing reliability In comparison with some traditional meta-schedulers.

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14

ANNA LÁZÁR, KATALIN. "A FORMAL LANGUAGE THEORETIC APPROACH TO DISTRIBUTED COMPUTING ON DYNAMIC NETWORKS." Advances in Complex Systems 13, no. 03 (June 2010): 253–80. http://dx.doi.org/10.1142/s0219525910002608.

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In this paper, we present a formal language theoretic approach to the behavior of complex systems of cooperating and communicating agents performing distributed computation on dynamic networks. In particular, we model peer-to-peer networks and the information harvest of Internet crawlers on the World Wide Web, employing grammar systems theoretical constructions. In grammar systems theory, the grammars can be interpreted as agents, whilst the generated language describes the behavior of the system. To characterize the various phenomena that may arise in peer-to-peer networks, we apply networks of parallel multiset string processors. The multiset string processors form teams, send and receive information through collective and individual filters. We deal with the dynamics of the string collections. To describe the information harvest of the crawlers, we employ certain regulated rewriting devices in eco-grammar systems. We illustrate the wide range of applicability of the regulated rewriting devices in the field of web crawling techniques. We demonstrate that these eco-grammar systems with rather simple component grammars suffice to identify any recursively enumerable language.

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15

Al Themairi, Asma, and Ahmed Farghaly. "The Dynamics Behavior of Coupled Generalized van der Pol Oscillator with Distributed Order." Mathematical Problems in Engineering 2020 (July 28, 2020): 1–10. http://dx.doi.org/10.1155/2020/5670652.

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In this paper, we presented different behaviors such as chaotic and hyperchaotic of the generalized van der Pol oscillator with distributed order. We introduced the parameter intervals of these behaviors by computing the Lyapunov exponents of the oscillator, which is a good test for classifying the dynamical systems’ solutions. The active control approach with the Laplace transform technique was used to realize the antisynchronization and control of the proposed oscillator. Finally, numerical investigations have been carried out on the dynamics of the proposed oscillator to verify the reliability of our analytical results.

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16

Thomas, Mathew, Malachi Schram, Kevin Fox, Jan Strube, Noah S. Oblath, Robert Rallo, Zachary C. Kennedy, Tamas Varga, Anil K. Battu, and Christopher A. Barrett. "Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems." MRS Advances 5, no. 29-30 (2020): 1547–55. http://dx.doi.org/10.1557/adv.2020.103.

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ABSTRACTWe present the current status of a scalable computing framework to address the need of the multidisciplinary effort to study chemical dynamics. Specifically, we are enabling scientists to process and store experimental data, run large-scale computationally expensive high-fidelity physical simulations, and analyze these results using state-of-the-art data analytics, machine learning, and uncertainty quantification methods using heterogeneous computing resources. We present the results of this framework on a single metadata-driven workflow to accelerate an additive manufacturing use-case.

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17

Klimenko, А. B. "Choosing Methodology of How to Manage Distributed Information Systems under Conditions of High Dynamics of Network Infrastructure." Proceedings of the Southwest State University 25, no. 3 (January 29, 2022): 136–51. http://dx.doi.org/10.21869/2223-1560-2021-25-3-136-151.

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Purpose of research. is to identify a distributed system control method that, based on known parameters, would reduce the resource consumption of computing devices. An information system resource is probability of failure-free operation (FFO), which decreases over time for each node, the faster the higher its load.Methods. Frequency of system reconfiguration becomes relatively high with high dynamics of edge layer of a network and the need for reconfiguration is unpredictable. Reducing the total time spent on reconfiguration allows to increase time spent on solving functional computing tasks of the system and thereby reducing nodes load. Reconfiguration time can be reduced both by reducing failure detection time in distributed system and by reducing searching time for new configuration. A method for reducing failure detection time is described. The applicability analysis of system management methods (centralized, distributed leader, decentralized) is carried out on the basis of obtained analytical evaluations of failure detection time by the system in control conditions through one or another method. A numerical experiment allows to distinguish areas of system parameters, where it is preferable to use the method with a distingods. Frequency of system reconfiguration becomes relatively high with high dynamics of edge layer of a network and the need for reconfiguration is unpredictable. Reducing the total time spent on reconfiguration allows to increase time spent on solving functional computing tasks of the system and thereby reducing nodes load. Reconfiguration time can be reduced both by reducing failure detection time in distributed system and by reducing searching time for new configuration. A method for reducing failure detection time is described. The applicability analysis of system management methods (centralized, distributed leader, decentralized) is carried out on the basis of obtained analytical evaluations of failure detection time by the system in control conditions through one or another method. A numerical experiment allows to distinguish areas of system parameters, where it is preferable to use the method with a distinuished leader.Results. The main result of this work is a method of choosing how to manage distributed information systems in conditions of high dynamics of network infrastructure, focused on reducing of resource consumption in computing devices.Conclusion. The system reconfiguration time could be reduced by selecting the most appropriate control method. In this case, the time for solving functional tasks of application is increased, the workload of computing nodes is reduced, and therefore FFO values are increased over the planning horizon.

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18

Baciu, George, Yungzhe Wang, and Chenhui Li. "Cognitive Visual Analytics of Multi-Dimensional Cloud System Monitoring Data." International Journal of Software Science and Computational Intelligence 9, no. 1 (January 2017): 20–34. http://dx.doi.org/10.4018/ijssci.2017010102.

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Hardware virtualization has enabled large scale computational service delivery models with high cost leverage and improved resource utilization on cloud computing platforms. This has completely changed the landscape of computing in the last decade. It has also enabled large–scale data analytics through distributed high performance computing. Due to the infrastructure complexity, end–users and administrators of cloud platforms can rarely obtain a full picture of the state of cloud computing systems and data centers. Recent monitoring tools enable users to obtain large amounts of data with respect to many utilization parameters of cloud platforms. However, they fail to get the maximal overall insight into the resource utilization dynamics of cloud platforms. Furthermore, existing tools make it difficult to observe large-scale patterns, making it difficult to learn from the past behavior of cloud system dynamics. In this work, the authors describe a perceptual-based interactive visualization platform that gives users and administrators a cognitive view of cloud computing system dynamics.

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19

Seoane, Luís F. "Evolutionary aspects of reservoir computing." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1774 (April 22, 2019): 20180377. http://dx.doi.org/10.1098/rstb.2018.0377.

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Reservoir computing (RC) is a powerful computational paradigm that allows high versatility with cheap learning. While other artificial intelligence approaches need exhaustive resources to specify their inner workings, RC is based on a reservoir with highly nonlinear dynamics that does not require a fine tuning of its parts. These dynamics project input signals into high-dimensional spaces, where training linear readouts to extract input features is vastly simplified. Thus, inexpensive learning provides very powerful tools for decision-making, controlling dynamical systems, classification, etc. RC also facilitates solving multiple tasks in parallel, resulting in a high throughput. Existing literature focuses on applications in artificial intelligence and neuroscience. We review this literature from an evolutionary perspective. RC’s versatility makes it a great candidate to solve outstanding problems in biology, which raises relevant questions. Is RC as abundant in nature as its advantages should imply? Has it evolved? Once evolved, can it be easily sustained? Under what circumstances? (In other words, is RC an evolutionarily stable computing paradigm?) To tackle these issues, we introduce a conceptual morphospace that would map computational selective pressures that could select for or against RC and other computing paradigms. This guides a speculative discussion about the questions above and allows us to propose a solid research line that brings together computation and evolution with RC as test model of the proposed hypotheses. This article is part of the theme issue ‘Liquid brains, solid brains: How distributed cognitive architectures process information’.

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20

Zhou, Jianshan, Daxin Tian, Zhengguo Sheng, Xuting Duan, and Xuemin Shen. "Distributed Task Offloading Optimization With Queueing Dynamics in Multiagent Mobile-Edge Computing Networks." IEEE Internet of Things Journal 8, no. 15 (August 1, 2021): 12311–28. http://dx.doi.org/10.1109/jiot.2021.3063509.

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21

Skulysh, Mariia, José Luis Pastrana Brincones, and Dmytro Parhomenko. "DEVELOPMENT OF THE CONCEPT FOR THE COMPUTATIONAL RESOURCES MANAGEMENT SOFTWARE IN THE CUSTOMER SERVICE SYSTEMS." Information and Telecommunication Sciences, no. 2 (December 19, 2022): 26–33. http://dx.doi.org/10.20535/2411-2976.22022.26-33.

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Background. To date, there is no customer service system that does not involve information and computer systems. One of the most important issues in ensuring the reliability and reliability of such systems is the task of dynamic scaling and providing the required amount of computing resources at any time. This study was focused on the planning and deployment of computing infrastructure that is able to respond to significantly increased volumes of request flows, changes in the dynamics of load intensity, strict requirements for the quality of their service, etc. Objective. The purpose of the paper is to create a concept of virtual computing space to meet the needs of distributed customer service system, which takes into account the peculiarities of service, the computing node load nature, service quality requirements, and provides energy efficient. Developed models, methods will control the performance of distributed computing infrastructure and flow maintenance processes, reduce downtime of computing resources and provide services to end users at a given level of quality. Methods. Analysis of the operation of the node load assessment mechanism, which consists in a dynamic change in the intensity of control of the state of function nodes, showed the effectiveness of planning for a group of computing nodes.. Results. The proposed approach to managing a heterogeneous computation environment to improve the efficiency of the service maintenance process in new generation systems is a unified solution for highly loaded distributed systems. The developed concept made it possible to avoid a decrease in the quality of service during surges of congestion and to maintain the indicators of the quality of service at a given level, provided that the resource utilization ratio is kept within the given limits Conclusions. In summary, a mathematical model of the problem of determining the maximum allowable load volume with a QoS level guarantee for a service node in a heterogeneous telecommunications environment was proposed.

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22

Woods, Christopher J., Muan Hong Ng, Steven Johnston, Stuart E. Murdock, Bing Wu, Kaihsu Tai, Hans Fangohr, et al. "Grid computing and biomolecular simulation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 363, no. 1833 (July 26, 2005): 2017–35. http://dx.doi.org/10.1098/rsta.2005.1626.

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Biomolecular computer simulations are now widely used not only in an academic setting to understand the fundamental role of molecular dynamics on biological function, but also in the industrial context to assist in drug design. In this paper, two applications of Grid computing to this area will be outlined. The first, involving the coupling of distributed computing resources to dedicated Beowulf clusters, is targeted at simulating protein conformational change using the Replica Exchange methodology. In the second, the rationale and design of a database of biomolecular simulation trajectories is described. Both applications illustrate the increasingly important role modern computational methods are playing in the life sciences.

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23

Petrenko, Sergei. "Self-Healing Cloud Computing." Voprosy kiberbezopasnosti, no. 1(41) (2021): 80–89. http://dx.doi.org/10.21681/2311-3456-2021-1-80-89.

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Purpose of the article: development of tools for building a cyber-stable private cloud. The relevance of building a cyber-resilient private cloud is confirmed by the dynamics of growth in the market volume of relevant solutions. According to PRnewswire, the market for private cloud solutions will reach 183 billion USD by 2025. At the same time, the average annual growth rate of the CAGR will be 29.4% during the forecast period. According to the analytical company Grand view research, the global market for private cloud solutions in 2018 was estimated at 30.24 billion US dollars, and it is expected that in the period from 2019 to 2025, the CAGR will be 29.6%. Research methods: It uses a set of open-source solutions that applies the advanced cloud technologies, including distributed data processing models and methods, container orchestration technologies, softwaredefined data storage architecture, and a universal database. Results: Developed tools for building a cyber-stable private cloud. Considered a possible approach to building a cyber-resilient private cloud based on the well-known and proprietary models and methods of the artificial immune systems (AIS), as well as technologies for distributed data processing, container orchestration, and others. In addition, the unique centralized fault-tolerant logging and monitoring subsystem has been developed for the described platform, as well as an innovative cybersecurity subsystem based on the following original technologies.

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Guyeux, Christophe. "Convergence versus Divergence Behaviors of Asynchronous Iterations, and Their Applications in Concrete Situations." Mathematical and Computational Applications 25, no. 4 (October 16, 2020): 69. http://dx.doi.org/10.3390/mca25040069.

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Asynchronous iterations have long been used in distributed computing algorithms to produce calculation methods that are potentially faster than a serial or parallel approach, but whose convergence is more difficult to demonstrate. Conversely, over the past decade, the study of the complex dynamics of asynchronous iterations has been initiated and deepened, as well as their use in computer security and bioinformatics. The first work of these studies focused on chaotic discrete dynamical systems, and links were established between these dynamics on the one hand, and between random or complex behaviours in the sense of the theory of the same name. Computer security applications have focused on pseudo-random number generation, hash functions, hidden information, and various security aspects of wireless sensor networks. At the bioinformatics level, this study of complex systems has allowed an original approach to understanding the evolution of genomes and protein folding. These various contributions are detailed in this review article, which is an extension of the paper “An update on the topological properties of asynchronous iterations” presented during the Sixth International Conference on Parallel, Distributed, GPU and Cloud Computing (Pareng 2019).

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Acedo, Luis, Clara Burgos, José-Ignacio Hidalgo, Victor Sánchez-Alonso, Rafael-Jacinto Villanueva, and Javier Villanueva-Oller. "Calibrating a large network model describing the transmission dynamics of the human papillomavirus using a particle swarm optimization algorithm in a distributed computing environment." International Journal of High Performance Computing Applications 32, no. 5 (April 7, 2017): 721–28. http://dx.doi.org/10.1177/1094342017697862.

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Working in large networks applied to epidemiological-type models has led us to design a simple but effective computed distributed environment to perform a large amount of model simulations in a reasonable time in order to study the behavior of these models and to calibrate them. Finding the model parameters that best fit the available data in the designed distributed computing environment becomes a challenge and it is necessary to implement reliable algorithms for model calibration. In this article, we have adapted the random particle swarm optimization algorithm to our distributed computing environment to be applied to the calibration of a papillomavirus transmission dynamics model on a lifetime sexual partners network. And we have obtained a good fitting saving time and calculations compared with the exhaustive searching strategy we have been using so far.

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Narayan, Devika. "Monopolization and competition under platform capitalism: Analyzing transformations in the computing industry." New Media & Society 25, no. 2 (February 2023): 287–306. http://dx.doi.org/10.1177/14614448221149939.

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Cross-disciplinary scholarship on platform-mediated transformations is growing rapidly. Large-scale data centers that aggregate hardware resources are an important element shaping the expansion of platform economies. The impact of this configuration of hardware on the dynamics of software development is still unclear. Data centers aggregate and centralize computing capacity and in turn enable the growth of globally distributed and organizationally decentralized corporate ecosystems. Scholarship in this area is beginning to examine the relations between dominant technology corporations and their networks of users and third-party companies. I contribute to literature on platform ecosystems by examining changing organizational and market dynamics introduced by cloud computing within the corporate computing sector. Drawing on qualitative interviews with managers of software startups in India, I focus on falling barriers to entry, new organizational forms, and emergent transnational dimensions. Using this case, I theorize monopolization as being embedded in competitive ecosystem dynamics.

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Tanaka, Hirokazu, and Terrence J. Sejnowski. "Computing reaching dynamics in motor cortex with Cartesian spatial coordinates." Journal of Neurophysiology 109, no. 4 (February 15, 2013): 1182–201. http://dx.doi.org/10.1152/jn.00279.2012.

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How neurons in the primary motor cortex control arm movements is not yet understood. Here we show that the equations of motion governing reaching simplify when expressed in spatial coordinates. In this fixed reference frame, joint torques are the sums of vector cross products between the spatial positions of limb segments and their spatial accelerations and velocities. The consequences that follow from this model explain many properties of neurons in the motor cortex, including directional broad, cosinelike tuning, nonuniformly distributed preferred directions dependent on the workspace, and the rotation of the population vector during arm movements. Remarkably, the torques can be directly computed as a linearly weighted sum of responses from cortical motoneurons, and the muscle tensions can be obtained as rectified linear sums of the joint torques. This allows the required muscle tensions to be computed rapidly from a trajectory in space with a feedforward network model.

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28

Khayrulin, Sergey. "DISTRIBUTED CALCULATIONS ON MULTIPLE INDEPENDENT DEVICES FOR PCISPH METHOD." Bulletin of the Novosibirsk Computing Center. Series: Computer Science, no. 45 (2021): 59–68. http://dx.doi.org/10.31144/bncc.cs.2542-1972.2021.n45.p59-68.

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One of the most significant drawbacks of the PCISPH algorithm (predictive corrective SPH), which is often used for the simulation of incompressible viscous liquid dynamics, is the complexity of the organization of distributed calculations on a computational cluster. At the same time, the algorithm supports the data parallelism relative to a single device. In this paper, new methods and algorithms for overcoming this drawback are suggested, based on an effective model of distributing the data between independent computing units. The resulting algorithms have been realized and tested on Novosibirsk State University’s cluster.

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Huang, Peng, Minjiang Deng, Zhiliang Kang, Qinshan Liu, and Lijia Xu. "Self-Adaptive Learning of Task Offloading in Mobile Edge Computing Systems." Entropy 23, no. 9 (August 31, 2021): 1146. http://dx.doi.org/10.3390/e23091146.

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Mobile edge computing (MEC) focuses on transferring computing resources close to the user’s device, and it provides high-performance and low-delay services for mobile devices. It is an effective method to deal with computationally intensive and delay-sensitive tasks. Given the large number of underutilized computing resources for mobile devices in urban areas, leveraging these underutilized resources offers tremendous opportunities and value. Considering the spatiotemporal dynamics of user devices, the uncertainty of rich computing resources and the state of network channels in the MEC system, computing resource allocation in mobile devices with idle computing resources will affect the response time of task requesting. To solve these problems, this paper considers the case in which a mobile device can learn from a neighboring IoT device when offloading a computing request. On this basis, a novel self-adaptive learning of task offloading algorithm (SAda) is designed to minimize the average offloading delay in the MEC system. SAda adopts a distributed working mode and has a perception function to adapt to the dynamic environment in reality; it does not require frequent access to equipment information. Extensive simulations demonstrate that SAda achieves preferable latency performance and low learning error compared to the existing upper bound algorithms.

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30

Morrison, Abigail, Carsten Mehring, Theo Geisel, Ad Aertsen, and Markus Diesmann. "Advancing the Boundaries of High-Connectivity Network Simulation with Distributed Computing." Neural Computation 17, no. 8 (August 1, 2005): 1776–801. http://dx.doi.org/10.1162/0899766054026648.

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The availability of efficient and reliable simulation tools is one of the mission-critical technologies in the fast-moving field of computational neuroscience. Research indicates that higher brain functions emerge from large and complex cortical networks and their interactions. The large number of elements (neurons) combined with the high connectivity (synapses) of the biological network and the specific type of interactions impose severe constraints on the explorable system size that previously have been hard to overcome. Here we present a collection of new techniques combined to a coherent simulation tool removing the fundamental obstacle in the computational study of biological neural networks: the enormous number of synaptic contacts per neuron. Distributing an individual simulation over multiple computers enables the investigation of networks orders of magnitude larger than previously possible. The software scales excellently on a wide range of tested hardware, so it can be used in an interactive and iterative fashion for the development of ideas, and results can be produced quickly even for very large networks. In con-trast to earlier approaches, a wide class of neuron models and synaptic dynamics can be represented.

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31

Tayar, Alexandra M., Eyal Karzbrun, Vincent Noireaux, and Roy H. Bar-Ziv. "Synchrony and pattern formation of coupled genetic oscillators on a chip of artificial cells." Proceedings of the National Academy of Sciences 114, no. 44 (October 16, 2017): 11609–14. http://dx.doi.org/10.1073/pnas.1710620114.

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Understanding how biochemical networks lead to large-scale nonequilibrium self-organization and pattern formation in life is a major challenge, with important implications for the design of programmable synthetic systems. Here, we assembled cell-free genetic oscillators in a spatially distributed system of on-chip DNA compartments as artificial cells, and measured reaction–diffusion dynamics at the single-cell level up to the multicell scale. Using a cell-free gene network we programmed molecular interactions that control the frequency of oscillations, population variability, and dynamical stability. We observed frequency entrainment, synchronized oscillatory reactions and pattern formation in space, as manifestation of collective behavior. The transition to synchrony occurs as the local coupling between compartments strengthens. Spatiotemporal oscillations are induced either by a concentration gradient of a diffusible signal, or by spontaneous symmetry breaking close to a transition from oscillatory to nonoscillatory dynamics. This work offers design principles for programmable biochemical reactions with potential applications to autonomous sensing, distributed computing, and biomedical diagnostics.

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32

Fersht, A. R. "On the simulation of protein folding by short time scale molecular dynamics and distributed computing." Proceedings of the National Academy of Sciences 99, no. 22 (October 18, 2002): 14122–25. http://dx.doi.org/10.1073/pnas.182542699.

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33

Tošic, Predrag T. "Cellular Automata Communication Models." International Journal of Natural Computing Research 1, no. 3 (July 2010): 66–84. http://dx.doi.org/10.4018/jncr.2010070105.

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In this paper, cellular automata (CA) are viewed as an abstract model for distributed computing. The author argues that the classical CA model must be modified in several important respects to become a relevant model for large-scale MAS. The paper first proposes sequential cellular automata (SCA) and formalizes deterministic and nondeterministic versions of SCA. The author then analyzes differences in possible dynamics between classical parallel CA and various SCA models. The analysis in this paper focuses on one-dimensional parallel and sequential CA with node update rules restricted to simple threshold functions, as arguably the simplest totalistic, yet non-linear (and non-affine) update rules. The author identifies properties of asymptotic dynamics that can be proven to be entirely due to the assumption of perfect synchrony in classical, parallel CA. Finally, the paper discusses what an appropriate CA-based abstraction would be for large-scale distributed computing, insofar as the inter-agent communication models. In that context, the author proposes genuinely asynchronous CA and discusses main differences between genuinely asynchronous CA and various weakly asynchronous sequential CA models found in the literature.

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34

Klimenko, A. B. "A Technique of the Distributed Information Systems Control Method Choice under the High Network Dynamics Conditions." Proceedings of the Southwest State University 26, no. 1 (June 28, 2022): 57–72. http://dx.doi.org/10.21869/2223-1560-2022-26-1-57-72.

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Purpose of research. The purpose of this study is to select a method for managing a distributed system, which, based on known parameters, would reduce the consumption of resources of computing devices. The resource of an information system is understood as the probability of failure-free operation (reliability function), which degrades over time for each node, the faster, the higher its workload.Methods. Considering that with high dynamics of the edge layer of the network, the frequency of system reconfigurations becomes relatively high, and the need for reconfigurations is unpredictable, reducing the total time spent on reconfigurations makes it possible to increase the time spent on solving functional computational problems of the system and thereby reduce the load of nodes. The reconfiguration time can be reduced both by reducing the time for detecting a failure in a distributed system, and by reducing the new configuration forming time. In this paper, a method for reducing the time of the failure detection is considered. The analysis of the applicability of system control methods (centralized, with a distributed leader, decentralized) is based on the obtained analytical estimates of the time the system detects a failure under control conditions using one method or another. A numerical experiment makes it possible to identify areas of system parameters, where it is preferable to use the method with a distributed leader.Results. The main result of this work is a methodology for choosing a method for managing distributed information systems in conditions of high dynamics of the network infrastructure, focused on reducing the consumption of resources of computing devices.Conclusion. System reconfiguration time can be shortened by choosing the most appropriate control method. Thus, the time allotted for solving the functional tasks of the application increases, the workload of the computational nodes decreases, and, therefore, the FBG values increase over the planning horizon.

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Carroll, Noel. "Modelling the Dynamics of Trust across a Cloud Brokerage Environment." Information Resources Management Journal 28, no. 1 (January 2015): 17–37. http://dx.doi.org/10.4018/irmj.2015010102.

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The globalised nature of cloud computing presents us with new challenges towards the development of effective business relationships across a dynamic service ecosystem. While availing of additional service capabilities, organisations are tasked with managing unfamiliar relationships with unfamiliar cloud service providers to generate increased business value. This calls for more attention towards the concept of trust within a cloud service environment. Cloud computing presents new economic and flexible business and technological models which supports the co-creation nature of service quality and ultimately business value. This research examined various methods to assess service quality and service capability assessment. During the course of this work, the author has identified the need to revisit the concept of ‘trust' within a cloud computing context and prescribe a method to model its complexity. The objective of this paper is to argue that, while cloud computing allows organisations to avail of increased service capabilities; it challenges the concept of trust. To support this argument the author presents the Cloud Services Trust Model to explain the dynamics of trust. In doing so, it introduces a notion of a distributed relational structure in service value co-creation. The paper also draws on theoretical developments to highlight the fundamental changes in the nature of service provision and how they impact on the assessment of service value and service quality. The author supports the need for greater transparency in the move towards greater accountability in the cloud ecosystem. The paper applies social network analysis (SNA) to model the trust relationships of a cloud brokerage environment.

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36

GUISADO, J. L., F. JIMÉNEZ-MORALES, and F. FERNÁNDEZ DE VEGA. "CELLULAR AUTOMATA AND CLUSTER COMPUTING: AN APPLICATION TO THE SIMULATION OF LASER DYNAMICS." Advances in Complex Systems 10, supp01 (August 2007): 167–90. http://dx.doi.org/10.1142/s0219525907001100.

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Firstly, the application of a cellular automata (CA) model to simulate the dynamics of lasers is reviewed. With this kind of model, the macroscopic properties of the laser system emerge as a cooperative phenomenon from elementary components locally interacting under simple rules. Secondly, a parallel implementation of this kind of model for distributed-memory parallel computers is presented. Performance and scalability of this parallel implementation running on a computer cluster are analyzed, giving very satisfactory results. This confirms the feasibility of running large 3D simulations — unaffordable on an individual machine — on computer clusters, in order to simulate specific real laser systems.

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Wang, Song, Liangyi Pu, Xiaodong Huang, Yifan Yu, Yawei Shi, and Huiwei Wang. "Online ADMM for Distributed Optimal Power Flow via Lagrangian Duality." Energies 15, no. 24 (December 15, 2022): 9525. http://dx.doi.org/10.3390/en15249525.

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At present, the power system has the characteristics of mutual independence but interconnection, and the interconnection between the various subsystems brings certain challenges to the distributed computing of the power grid. In addition, a substantial amount of naturally uncertain renewable resources are incorporated into the power system, which will impose volatile dynamics on the grid. In this paper, an alternating direction multiplier method (ADMM) is proposed for the power system with real-time renewables to tackle the online optimal power flow (OPF) problem. Due to the adoption of the Lagrangian duality, the proposed distributed ADMM scheme utilizes consensus ADMM to solve the dual OPF problem, which only discloses boundary coupling via the Lagrangian multiplier and further reduces the amount of information communication. Given the natural uncertainty of distributed energy resources (DER), the algorithm avoids the double-loop implementation or the uncertainty of traditional distributed methods of using the boundary information as equality constraints caused by dynamic DER. It is thus capable of providing a provable performance guarantee and is inherently developed to cope with the dynamic OPF problem with renewables in an online fashion. Taking the IEEE 30-bus system as a test feeder, the simulation results verify the efficiency and robustness of the proposed algorithms in solving both the static and dynamic OPF problems; in addition, the online method can effectively avoid the violent fluctuations of the conventional generator output copying with renewables rapid variation in comparison with the offline algorithms.

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38

Lee, Suchul. "Distributed Detection of Malicious Android Apps While Preserving Privacy Using Federated Learning." Sensors 23, no. 4 (February 15, 2023): 2198. http://dx.doi.org/10.3390/s23042198.

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Recently, deep learning has been widely used to solve existing computing problems through large-scale data mining. Conventional training of the deep learning model is performed on a central (cloud) server that is equipped with high computing power, by integrating data via high computational intensity. However, integrating raw data from multiple clients raises privacy concerns that are increasingly being focused on. In federated learning (FL), clients train deep learning models in a distributed fashion using their local data; instead of sending raw data to a central server, they send parameter values of the trained local model to a central server for integration. Because FL does not transmit raw data to the outside, it is free from privacy issues. In this paper, we perform an experimental study that explores the dynamics of the FL-based Android malicious app detection method under three data distributions across clients, i.e., (i) independent and identically distributed (IID), (ii) non-IID, (iii) non-IID and unbalanced. Our experiments demonstrate that the application of FL is feasible and efficient in detecting malicious Android apps in a distributed manner on cellular networks.

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39

Hein, Joachim, Fiona Reid, Lorna Smith, Ian Bush, Martyn Guest, and Paul Sherwood. "On the performance of molecular dynamics applications on current high-end systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 363, no. 1833 (July 20, 2005): 1987–98. http://dx.doi.org/10.1098/rsta.2005.1624.

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The effective exploitation of current high performance computing (HPC) platforms in molecular simulation relies on the ability of the present generation of parallel molecular dynamics code to make effective utilisation of these platforms and their components, including CPUs and memory. In this paper, we investigate the efficiency and scaling of a series of popular molecular dynamics codes on the UK's national HPC resources, an IBM p690+ cluster and an SGI Altix 3700. Focusing primarily on the Amber , Dl_Poly and Namd simulation codes, we demonstrate the major performance and scalability advantages that arise through a distributed, rather than a replicated data approach.

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40

Huria, Sugandha, and Kanika Pathania. "Dynamics of Food Inflation: Assessing the Role of Intermediaries." Global Business Review 19, no. 5 (August 20, 2018): 1363–78. http://dx.doi.org/10.1177/0972150918788763.

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The recent upsurge in the food prices experienced by the Indian economy since the latter half of 2000s has made it imperative for the policymakers to identify the crucial factors, which affect food prices within the economy. Against this backdrop, the present article determines the various key factors impacting the prices of food grains, specifically elucidating the role of intermediaries in this regard. By applying the autoregressive distributed lag (ARDL) approach to cointegration and quantifying the role of intermediaries by computing the price wedge between wholesale and retail prices of food grains, the study establishes the existence of both short-run and long-run relationships between price wedge and food grain inflation.

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41

Mitsis, Giorgos, Eirini Eleni Tsiropoulou, and Symeon Papavassiliou. "Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems: A Resource-Based Pricing and User Risk-Awareness Approach." Sensors 20, no. 8 (April 24, 2020): 2434. http://dx.doi.org/10.3390/s20082434.

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Unmanned Aerial Vehicle (UAV)-assisted Multi-access Edge Computing (MEC) systems have emerged recently as a flexible and dynamic computing environment, providing task offloading service to the users. In order for such a paradigm to be viable, the operator of a UAV-mounted MEC server should enjoy some form of profit by offering its computing capabilities to the end users. To deal with this issue in this paper, we apply a usage-based pricing policy for allowing the exploitation of the servers’ computing resources. The proposed pricing mechanism implicitly introduces a more social behavior to the users with respect to competing for the UAV-mounted MEC servers’ computation resources. In order to properly model the users’ risk-aware behavior within the overall data offloading decision-making process the principles of Prospect Theory are adopted, while the exploitation of the available computation resources is considered based on the theory of the Tragedy of the Commons. Initially, the user’s prospect-theoretic utility function is formulated by quantifying the user’s risk seeking and loss aversion behavior, while taking into account the pricing mechanism. Accordingly, the users’ pricing and risk-aware data offloading problem is formulated as a distributed maximization problem of each user’s expected prospect-theoretic utility function and addressed as a non-cooperative game among the users. The existence of a Pure Nash Equilibrium (PNE) for the formulated non-cooperative game is shown based on the theory of submodular games. An iterative and distributed algorithm is introduced which converges to the PNE, following the learning rule of the best response dynamics. The performance evaluation of the proposed approach is achieved via modeling and simulation, and detailed numerical results are presented highlighting its key operation features and benefits.

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42

Liu, Li, Tao Yao, Xin Hu, Chunjie Zhou, Dianli Hou, Shulin Feng, and Hongyong Yang. "Distributed State Estimation for Dynamic Positioning Systems with Uncertain Disturbances and Transmission Time Delays." Complexity 2020 (July 20, 2020): 1–15. http://dx.doi.org/10.1155/2020/7698504.

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The dynamic positioning system of unmanned underwater vehicles (UUVs) is a complex and large-scale system mainly due to the nonlinear dynamics, uncertainty in model parameters, and external disturbances. With the aid of the bio-inspired computing (BIC) method, the designed three-dimensional (3D) spatial positioning system is used for enlarging communication constraints and increasing signal coordination processing. With the growing of measurement scales, the issue of the networked high-precision positioning has been developed rapidly. Then, an information fusion estimation approach is presented for the distributed networked systems with data random transmission time delays and lost and disordered packets. To reduce the communication burden, an adaptive signal selection scheme is employed to reorganize the measurement sequence, and the parameter uncertainties as well as cross-correlated noise are used to describe the uncertain disturbances. Moreover, a reoptimal weighted fusion state estimation is designed to alleviate the information redundancy and maintain higher measurement accuracy. An illustrative example obtained from the 3D spatial positioning system is given to validate the effectiveness of the proposed method.

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43

Kari, Chadi, Alexander Russell, and Narasimha Shashidhar. "Work-Competitive Scheduling on Task Dependency Graphs." Parallel Processing Letters 25, no. 02 (June 2015): 1550001. http://dx.doi.org/10.1142/s0129626415500012.

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A fundamental problem in distributed computing is the task of cooperatively executing a given set of [Formula: see text] tasks by [Formula: see text] asynchronous processors where the communication medium is dynamic and subject to failures. Also known as do-all, this problem been studied extensively in various distributed settings. In [2], the authors consider a partitionable network scenario and analyze the competitive performance of a randomized scheduling algorithm for the case where the tasks to be completed are independent of each other. In this paper, we study a natural extension of this problem where the tasks have dependencies among them. We present a simple randomized algorithm for [Formula: see text] processors cooperating to perform [Formula: see text] known tasks where the dependencies between them are defined by a [Formula: see text]-partite task dependency graph and additionally these processors are subject to a dynamic communication medium. By virtue of the problem setting, we pursue competitive analysis where the performance of our algorithm is measured against that of the omniscient offline algorithm which has complete knowledge of the dynamics of the communication medium. We show that the competitive ratio of our algorithm is tight and depends on the dynamics of the communication medium viz. the computational width defined in [2] and also on the number of partitions of the task dependency graph.

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44

HAMMOND, D. A., and L. G. REDEKOPP. "Global dynamics of symmetric and asymmetric wakes." Journal of Fluid Mechanics 331 (January 25, 1997): 231–60. http://dx.doi.org/10.1017/s0022112096003825.

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The two-dimensional wake–shear layer forming behind a rectangular-based forebody with independent ambient streams on either side of the forebody is examined by direct numerical simulation. Theoretical aspects of global modes and frequency selection criteria based on local and global stability arguments are tested by computing local stability properties using local, time-averaged velocity profiles obtained from the numerical simulations and making the parallel-flow approximation. The theoretical results based on the assumption of a slightly non-parallel, spatially developing flow are shown to provide a firm basis for the frequency selection of vortex shedding and for defining the conditions for its onset. Distributed suction or blowing applied at the base of the forebody is used as a means of wake flow modification. The critical suction velocity to suppress vortex shedding is calculated. It is shown that local directional control (i.e. vectoring) of the near-wake flow is possible, but only when all global modes are suppressed.

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45

CHEN, CHIEN-CHONG, CHYI HWANG, EDUARDO E. WOLF, and HSUEH-CHIA CHANG. "CHARACTERIZATION OF CHAOTIC ATTRACTORS IN EXTENDED SYSTEMS." International Journal of Bifurcation and Chaos 06, no. 07 (July 1996): 1375–82. http://dx.doi.org/10.1142/s0218127496000795.

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It is shown that the traditional delayed embedding method, which is often applied to measurements at a single spatial point, could only account for partial chaotic dynamics of an extended system. To catch the whole dynamics of an extended system, we apply in this letter the Karhunen-Loeve (K-L) procedure to construct a series of tangent maps from spatially distributed measurements. The tangent maps obtained are then used for computing certain ergodic invariants. The procedure is illustrated with the experimental data obtained from a catalytic wafer, which is a spatially extended system exhibiting complex dynamics. The computed results show clearly that the K-L procedure is more suitable than the delayed embedding method for deciphering the full chaotic behavior of an extended system.

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46

Pan, Xiao Hui. "Accelerating Network Coding on Graphics Processors." Applied Mechanics and Materials 513-517 (February 2014): 1573–76. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1573.

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Network coding has recently been widely applied in various distributed systems for throughput improvement and/or resilience to network dynamics. However, the computational overhead introduced by network coding operations is not negligible and has become the obstacle for practical deployment of network coding. In this paper, I exploit the computing power of commodity many-core Graphic Processing Units (GPUs) and multi-core CPUs to accelerate the network coding computation. With the implementation of the algorithms, significant encoding and decoding throughput can be achieved.

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47

Duan, S., and K. S. Anderson. "Parallel Implementation of a Low Order Algorithm for Dynamics of Multibody Systems on a Distributed Memory Computing System." Engineering With Computers 16, no. 2 (September 29, 2000): 96–108. http://dx.doi.org/10.1007/pl00007191.

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48

Šulc, Stanislav, Vít Šmilauer, and František Wald. "COUPLED SIMULATION FOR FIRE-EXPOSED STRUCTURES USING CFD AND THERMO-MECHANICAL MODELS." Acta Polytechnica CTU Proceedings 13 (November 13, 2017): 121. http://dx.doi.org/10.14311/app.2017.13.0121.

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Fire resistance of buildings is based on fire tests in furnaces with gas burners. However, the tests are very expensive and time consuming. This article presents a coupled simulation of an element loaded by a force and a fire loading. The simulation solves a weakly-coupled problem, consisting of fluid dynamics, heat transfer and mechanical model. The temperature field from the computational fluid dynamics simulation (CFD) creates Cauchy and radiative boundary conditions for the thermal model. Then, the temperature field from element is passed to the mechanical model, which induces thermal strain and modifies material parameters. The fluid dynamics is computed with Fire Dynamics Simulator and the thermo-mechanical task is solved in OOFEM. Both softwares are interconnected with MuPIF python library, which allows smooth data transfer across the different meshes, orchestrating simulations in particular codes, exporting results to the VTK formats and distributed computing.

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49

Zeng, Yan, Wei Wang, Yong Ding, Jilin Zhang, Yongjian Ren, and Guangzheng Yi. "Adaptive Distributed Parallel Training Method for a Deep Learning Model Based on Dynamic Critical Paths of DAG." Mathematics 10, no. 24 (December 16, 2022): 4788. http://dx.doi.org/10.3390/math10244788.

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AI provides a new method for massive simulated data calculations in molecular dynamics, materials, and other scientific computing fields. However, the complex structures and large-scale parameters of neural network models make them difficult to develop and train. The automatic parallel technology based on graph algorithms is one of the most promising methods to solve this problem, despite the low efficiency in the design, implementation, and execution of distributed parallel policies for large-scale neural network models. In this paper, we propose an adaptive distributed parallel training method based on the dynamic generation of critical DAG (directed acyclic graph) paths, called FD-DPS, to solve this efficiency problem. Firstly, the proposed model splits operators with the dimension of the tensor, which can expand the space available for model parallelism. Secondly, a dynamic critical path generation method is employed to determine node priority changes in the DAG of the neural network models. Finally, the model implements the optimal scheduling of critical paths based on the priority of the nodes, thereby improving the performance of parallel strategies. Our experiments show that FD-DPS can achieve 12.76% and 11.78% faster training on PnasNet_mobile and ResNet_200 models, respectively, compared with the MP-DPS and Fast methods.

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50

Dumitrescu, Catalin, Petrica Ciotirnae, and Constantin Vizitiu. "Fuzzy Logic for Intelligent Control System Using Soft Computing Applications." Sensors 21, no. 8 (April 8, 2021): 2617. http://dx.doi.org/10.3390/s21082617.

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When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.

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