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Journal articles on the topic 'Event Driven Simulation'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

González, Daniel Huertas, and Alfonso Rojas Espinosa. "Simulation of Cell Signaling Communications Using Event-Driven Algorithms." International Journal of Computer Theory and Engineering 6, no. 4 (2014): 307–12. http://dx.doi.org/10.7763/ijcte.2014.v6.880.

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2

Phillips, C. I., and L. G. Cuthbert. "Concurrent discrete event-driven simulation tools." IEEE Journal on Selected Areas in Communications 9, no. 3 (1991): 477–85. http://dx.doi.org/10.1109/49.76647.

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3

Kesaraju, V. S., and F. W. Ciarallo. "Integrated simulation combining process-driven and event-driven models." Journal of Simulation 6, no. 1 (2012): 9–20. http://dx.doi.org/10.1057/jos.2010.27.

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4

Reutimann, Jan, Michele Giugliano, and Stefano Fusi. "Event-Driven Simulation of Spiking Neurons with Stochastic Dynamics." Neural Computation 15, no. 4 (2003): 811–30. http://dx.doi.org/10.1162/08997660360581912.

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We present a new technique, based on a proposed event-based strategy (Mattia & Del Giudice, 2000), for efficiently simulating large networks of simple model neurons. The strategy was based on the fact that interactions among neurons occur by means of events that are well localized in time (the action potentials) and relatively rare. In the interval between two of these events, the state variables associated with a model neuron or a synapse evolved deterministically and in a predictable way. Here, we extend the event-driven simulation strategy to the case in which the dynamics of the state

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5

Kim, Seongseop, Jeonghun Cho, and Daejin Park. "Accelerated DEVS Simulation Using Collaborative Computation on Multi-Cores and GPUs for Fire-Spreading IoT Sensing Applications." Applied Sciences 8, no. 9 (2018): 1466. http://dx.doi.org/10.3390/app8091466.

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Discrete event system specification (DEVS) has been widely used in event-driven simulations for sensor-driven Internet of things (IoT) applications, such as monitoring the spread of fire disaster. Event-driven models for IoT sensor nodes and their communication is described in DEVS and they have to be integrated with continuous models of fire-spreading dynamics so that the hybrid system modeling and simulation approach have to be considered for both continuous behavior of fire-spreading and event-driven communications by large-scale IoT sensor devices. The hybrid-integrated modelling and simul

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6

Ros, Eduardo, Richard Carrillo, Eva M. Ortigosa, Boris Barbour, and Rodrigo Agís. "Event-Driven Simulation Scheme for Spiking Neural Networks Using Lookup Tables to Characterize Neuronal Dynamics." Neural Computation 18, no. 12 (2006): 2959–93. http://dx.doi.org/10.1162/neco.2006.18.12.2959.

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Nearly all neuronal information processing and interneuronal communication in the brain involves action potentials, or spikes, which drive the short-term synaptic dynamics of neurons, but also their long-term dynamics, via synaptic plasticity. In many brain structures, action potential activity is considered to be sparse. This sparseness of activity has been exploited to reduce the computational cost of large-scale network simulations, through the development of event-driven simulation schemes. However, existing event-driven simulations schemes use extremely simplified neuronal models. Here, w

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7

Dusung Kim, M. Ciesielski, and Seiyang Yang. "MULTES: Multilevel Temporal-Parallel Event-Driven Simulation." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 32, no. 6 (2013): 845–57. http://dx.doi.org/10.1109/tcad.2013.2237769.

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8

Rapaport, Dennis C. "The Event-Driven Approach toN-Body Simulation." Progress of Theoretical Physics Supplement 178 (2009): 5–14. http://dx.doi.org/10.1143/ptps.178.5.

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9

Tsoi, Kuen Hung, Tobias Becker, and Wayne Luk. "Modelling reconfigurable systems in event driven simulation." ACM SIGARCH Computer Architecture News 40, no. 5 (2012): 34–39. http://dx.doi.org/10.1145/2460216.2460223.

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10

Carrillo, Richard R., Eduardo Ros, Silvia Tolu, Thierry Nieus, and Egidio D’Angelo. "Event-driven simulation of cerebellar granule cells." Biosystems 94, no. 1-2 (2008): 10–17. http://dx.doi.org/10.1016/j.biosystems.2008.05.007.

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11

Zhou, Bo, Xinwei Sun, Yongkang Wang, Yunyang Xu, and Shaowei Huang. "Event-driven based simulation method for security and stability control strategies of power system." Journal of Physics: Conference Series 2703, no. 1 (2024): 012041. http://dx.doi.org/10.1088/1742-6596/2703/1/012041.

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Abstract Since the security and stability control strategies (SSCSs) play a pivotal role in maintaining system stability, devising the strategies accurately and reliably is of great significance. Currently, SSCSs are typically formulated according to the ‘offline simulation and online matching’ approach. However, existing commercial simulation software is difficult to simulate the dynamic triggering mechanisms and intricate control logic of SSCSs. To simulate the set of SSCSs systematically and comprehensively, this paper has proposed an event-driven approach for simulations. Firstly, the SSCS

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12

Salehian, Solmaz, and Rozita Salehian. "An event-driven simulation for WSN clustering algorithm." Indian Journal of Science and Technology 11, no. 13 (2018): 1–11. http://dx.doi.org/10.17485/ijst/2018/v11i13/115861.

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13

Hu, Zhifeng, Zhiping Yuan, Huimin Hou, Fuqiang Chu, and X. M. Wu. "Event-driven Simulation of Multi-scale Dropwise Condensation." International Journal of Heat and Mass Transfer 167 (March 2021): 120819. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2020.120819.

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14

Georgescu, Serban, and Hiroshi Okuda. "1411 Event-driven Framework for Agent-Based Simulation." Proceedings of Design & Systems Conference 2005.15 (2005): 190–91. http://dx.doi.org/10.1299/jsmedsd.2005.15.190.

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15

Krishnaswamy, V., G. Hasteer, and P. Banerjee. "Automatic parallelization of compiled event driven VHDL simulation." IEEE Transactions on Computers 51, no. 4 (2002): 380–94. http://dx.doi.org/10.1109/12.995448.

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16

Agarwal, Aayushya, Amritanshu Pandey, and Larry Pileggi. "Robust event-driven dynamic simulation using power flow." Electric Power Systems Research 189 (December 2020): 106752. http://dx.doi.org/10.1016/j.epsr.2020.106752.

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17

Kaabi, Mohamed Ghaith, Arnaud Tonnelier, and Dominique Martinez. "On the Performance of Voltage Stepping for the Simulation of Adaptive, Nonlinear Integrate-and-Fire Neuronal Networks." Neural Computation 23, no. 5 (2011): 1187–204. http://dx.doi.org/10.1162/neco_a_00112.

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In traditional event-driven strategies, spike timings are analytically given or calculated with arbitrary precision (up to machine precision). Exact computation is possible only for simplified neuron models, mainly the leaky integrate-and-fire model. In a recent paper, Zheng, Tonnelier, and Martinez ( 2009 ) introduced an approximate event-driven strategy, named voltage stepping, that allows the generic simulation of nonlinear spiking neurons. Promising results were achieved in the simulation of single quadratic integrate-and-fire neurons. Here, we assess the performance of voltage stepping in

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18

GRASSMANN, CYPRIAN, and JOACHIM K. ANLAUF. "FAST DIGITAL SIMULATION OF SPIKING NEURAL NETWORKS AND NEUROMORPHIC INTEGRATION WITH SPIKELAB." International Journal of Neural Systems 09, no. 05 (1999): 473–78. http://dx.doi.org/10.1142/s0129065799000502.

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We present a simulation environment called SPIKELAB which incorporates a simulator that is able to simulate large networks of spiking neurons using a distributed event driven simulation. Contrary to a time driven simulation, which is usually used to simulate spiking neural networks, our simulation needs less computational resources because of the low average activity of typical networks. The paper addresses the speed up using an event driven versus a time driven simulation and how large networks can be simulated by a distribution of the simulation using already available computing resources. I

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19

GAVRILOVA, MARINA L., and JON ROKNE. "COLLISION DETECTION OPTIMIZATION IN A MULTI-PARTICLE SYSTEM." International Journal of Computational Geometry & Applications 13, no. 04 (2003): 279–301. http://dx.doi.org/10.1142/s0218195903001189.

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Collision detection optimization in an event-driven simulation of a multi-particle system is one of the crucial tasks, determining the efficiency of the simulation. We present the event-driven simulation algorithm that employs dynamic computational geometry data structures as a tool for collision detection optimization (CDO). The first successful application of the dynamic generalized Voronoi diagram method for collision detection optimization in a system of moving particles is discussed. A comprehensive comparision of four kinetic data structures in d-dimensional space, performed in a framewo

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20

Diao, Guangzhou, Jing Rao, and Jun Zhao. "Event-driven Modelling Method for Sub-assembly Intelligent Production Line." MATEC Web of Conferences 175 (2018): 03035. http://dx.doi.org/10.1051/matecconf/201817503035.

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Focusing on the design of sub-assemble intelligent production line, an event-driven design method for production line was proposed. With the method, the manufacturing activity was defined as event, and then the relationships among events are analysed to define the input-output and execution behaviours digitally in each stage. Furthermore, the event-driven execution mechanism for multi-stage process was built to describe the production line in digital. The digital model of production line was conducted to explore the event behaviours, which will support the research about data-driven production

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21

Subramanian, K., and M. Zargham. "Distributed and Parallel Demand Driven Logic Simulation Algorithms." VLSI Design 1, no. 2 (1994): 169–79. http://dx.doi.org/10.1155/1994/12503.

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Based on the demand-driven approach, distributed and parallel simulation algorithms are proposed. Demand-driven simulation ties to minimize the number of component evaluations by restricting to only those component computations required for the watched output requests. For a specific output value request, the input line values that are required are requested to the respective component. The process continues until known signal values are needed (system input signal values). We present a distributed demand-driven algorithm with infinite memory requirement (but still the memory required at each

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22

Giles, Christopher E., Christina L. Peterson, and Mark A. Heinrich. "KnightSim: A Fast Discrete Event-Driven Simulation Methodology for Computer Architectural Simulation." IEEE Transactions on Computers 69, no. 1 (2020): 65–71. http://dx.doi.org/10.1109/tc.2019.2938507.

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23

Denisova, Ludmila. "EVENT-DRIVEN SIMULATION OF CONTROL SYSTEMS WITH VARIABLE PARAMETERS." IFAC Proceedings Volumes 46, no. 9 (2013): 2179–84. http://dx.doi.org/10.3182/20130619-3-ru-3018.00254.

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24

Yang, Seiyang, and Kyuho Shim. "A Practical Approach to Incremental Event-driven HDL Simulation." KIPS Transactions on Computer and Communication Systems 3, no. 3 (2014): 73–80. http://dx.doi.org/10.3745/ktccs.2014.3.3.73.

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25

Yang, Seiyang. "A New Prediction-Based Parallel Event-Driven Logic Simulation." KIPS Transactions on Computer and Communication Systems 4, no. 3 (2015): 85–90. http://dx.doi.org/10.3745/ktccs.2015.4.3.85.

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26

Stojadinovic, Bozidar, Gilberto Mosqueda, and Stephen A. Mahin. "Event-Driven Control System for Geographically Distributed Hybrid Simulation." Journal of Structural Engineering 132, no. 1 (2006): 68–77. http://dx.doi.org/10.1061/(asce)0733-9445(2006)132:1(68).

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27

Gai, S., and P. L. Montessoro. "The fault dropping problem in concurrent event-driven simulation." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 10, no. 8 (1991): 968–71. http://dx.doi.org/10.1109/43.85734.

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28

Harrington, Brian E., and Paul A. Fishwick. "A Portable Process-Oriented Compiler For Event Driven Simulation." SIMULATION 60, no. 6 (1993): 393–403. http://dx.doi.org/10.1177/003754979306000604.

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29

Agís, R., E. Ros, J. Díaz, R. Carrillo, and E. M. Ortigosa. "Hardware event-driven simulation engine for spiking neural networks." International Journal of Electronics 94, no. 5 (2007): 469–80. http://dx.doi.org/10.1080/00207210701308625.

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30

Werner, Timothy M., and Robert H. Kadlec. "Stochastic simulation of partially-mixed, event-driven treatment wetlands." Ecological Engineering 14, no. 3 (2000): 253–67. http://dx.doi.org/10.1016/s0925-8574(99)00003-8.

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31

Holliday, Mary Robin. "Methodology of an event-driven Monte Carlo missile simulation." Mathematical and Computer Modelling 14 (1990): 1123–28. http://dx.doi.org/10.1016/0895-7177(90)90352-n.

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32

Liu, Yadong, Wei Li, Kazuo Yamazaki, Keizo Kashihara, and Makoto Fujishima. "An event-driven simulation method for motor driver in virtual machine tool system." Journal of Intelligent Manufacturing 19, no. 2 (2008): 241–48. http://dx.doi.org/10.1007/s10845-008-0077-5.

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33

Rudolph, Michelle, and Alain Destexhe. "Analytical Integrate-and-Fire Neuron Models with Conductance-Based Dynamics for Event-Driven Simulation Strategies." Neural Computation 18, no. 9 (2006): 2146–210. http://dx.doi.org/10.1162/neco.2006.18.9.2146.

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Event-driven simulation strategies were proposed recently to simulate integrate-and-fire (IF) type neuronal models. These strategies can lead to computationally efficient algorithms for simulating large-scale networks of neurons; most important, such approaches are more precise than traditional clock-driven numerical integration approaches because the timing of spikes is treated exactly. The drawback of such event-driven methods is that in order to be efficient, the membrane equations must be solvable analytically, or at least provide simple analytic approximations for the state variables desc

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34

Hu, Li Ping, Dong Mei Wang, and Lei Zuo. "Event Step Method on Computer Simulation of Discrete Event System." Applied Mechanics and Materials 543-547 (March 2014): 1848–51. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1848.

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Discrete event system is driven by event, and system status is discrete on time and space, so it is difficult to solve by using equation model and theoretical analysis method. Computer simulation technique provides an effective mean in order to solve these problems. Contents of this study provide technical and methodological support for computer simulation of discrete event. Firstly, the paper illustrated the basic concept of discrete event system; then, time step method mechanism described by mathematical model and graphical method; finally, we can research on the control flow of event step m

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35

Tsai, Wei-Chang, and C. Bernard Shung. "Event-Driven Power Estimation of CMOS Circuits." Journal of Circuits, Systems and Computers 07, no. 05 (1997): 471–82. http://dx.doi.org/10.1142/s0218126697000358.

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Fast and accurate power estimation has become an important topic with the increasing need for low power electronics. In this paper we address the problem of using event-driven simulation tools for power estimation. We identify and compare two approaches: input-driven and output-driven, and propose several ways of improvement. The estimation accuracy is degraded in event-driven power estimators due to superfluous and partial glitches. We described glitch filtering and estimation techniques pertaining to input-driven and output-driven power estimators. An output-driven power estimator, Peony, wa

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36

Donev, Aleksandar. "Asynchronous Event-Driven Particle Algorithms." SIMULATION 85, no. 4 (2009): 229–42. http://dx.doi.org/10.1177/0037549708097881.

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37

Akkaya, Volkan Ramazan, and Ilyas Kandemir. "Event-Driven Molecular Dynamics Simulation of Hard-Sphere Gas Flows in Microchannels." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/842837.

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Classical solution of Navier-Stokes equations with nonslip boundary condition leads to inaccurate predictions of flow characteristics of rarefied gases confined in micro/nanochannels. Therefore, molecular interaction based simulations are often used to properly express velocity and temperature slips at high Knudsen numbers (Kn) seen at dilute gases or narrow channels. In this study, an event-driven molecular dynamics (EDMD) simulation is proposed to estimate properties of hard-sphere gas flows. Considering molecules as hard-spheres, trajectories of the molecules, collision partners, correspond

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38

Iannino, Vincenzo, Claudio Mocci, Marco Vannocci, Valentina Colla, Andrea Caputo, and Francesco Ferraris. "An Event-Driven Agent-Based Simulation Model for Industrial Processes." Applied Sciences 10, no. 12 (2020): 4343. http://dx.doi.org/10.3390/app10124343.

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Process manufacturing industries are complex and dynamic systems composed of several processes, subject to many operations and unexpected events that can compromise overall system performance. Therefore, the use of technologies and methods that can transform traditional process industries into smart factories is necessary. In this paper, a smart industrial process based on intelligent software agents is presented with the aim of providing a technological solution to the specific needs of the process industry. An event-driven agent-based simulation model composed of eight reactive agents was de

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39

Maffezzoni, P., L. Codecasa, and D. D'Amore. "Event-Driven Time-Domain Simulation of Closed-Loop Switched Circuits." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 25, no. 11 (2006): 2413–26. http://dx.doi.org/10.1109/tcad.2006.882121.

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40

Jennings, Glenn. "A case against event-driven simulation for digital system design." ACM SIGSIM Simulation Digest 21, no. 3 (1991): 170–76. http://dx.doi.org/10.1145/106073.106117.

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41

Jennings, Glenn. "A case against event-driven simulation for digital system design." ACM SIGSIM Simulation Digest 21, no. 3 (1991): 170–76. http://dx.doi.org/10.1145/106073.306855.

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42

Baker, W. I., A. Mahmood, and B. S. Carlson. "Parallel event-driven logic simulation algorithms: tutorial and comparative evaluation." IEE Proceedings - Circuits, Devices and Systems 143, no. 4 (1996): 177. http://dx.doi.org/10.1049/ip-cds:19960477.

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43

Wilson, Andrew. "Parallelization of an event driven simulator for computer systems simulation." SIMULATION 49, no. 2 (1987): 72–78. http://dx.doi.org/10.1177/003754978704900204.

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44

Takashi, Sadao Hizuka, Hidehiko, and Yoshikazu. "Time-event driven scheme for distributed simulation with advance processing." Systems and Computers in Japan 21, no. 1 (1990): 1–12. http://dx.doi.org/10.1002/scj.4690210101.

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45

Xue, Xue Dong, Xu De Cheng, Bing Xu, Wei Xin Zhang, and Dong Yu Zhang. "The Designing of Missile Tail Testing Simulation Training System." Advanced Materials Research 466-467 (February 2012): 582–86. http://dx.doi.org/10.4028/www.scientific.net/amr.466-467.582.

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This paper constructs a missile tail testing simulation training system based on virtual closed-loop control technique, event driven engine technique and PCI bus technique. It expounds specifically the system design method, realization of system hardware as well as simulation software system design, and puts forward the idea to apply the event driven technique in MCU system, which improves the programming efficiency and has guidance and reference significance for the research and development of similar simulation training equipments.

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46

Mattia, Maurizio, and Paolo Del Giudice. "Efficient Event-Driven Simulation of Large Networks of Spiking Neurons and Dynamical Synapses." Neural Computation 12, no. 10 (2000): 2305–29. http://dx.doi.org/10.1162/089976600300014953.

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A simulation procedure is described for making feasible large-scale simulations of recurrent neural networks of spiking neurons and plastic synapses. The procedure is applicable if the dynamic variables of both neurons and synapses evolve deterministically between any two successive spikes. Spikes introduce jumps in these variables, and since spike trains are typically noisy, spikes introduce stochasticity into both dynamics. Since all events in the simulation are guided by the arrival of spikes, at neurons or synapses, we name this procedure event-driven. The procedure is described in detail,

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47

Zhu, Qian, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song. "Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China." Hydrology and Earth System Sciences 28, no. 7 (2024): 1665–86. http://dx.doi.org/10.5194/hess-28-1665-2024.

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Abstract. Accurate flood event simulation and prediction, enabled by effective models and reliable data, are critical for mitigating the potential risk of flood disaster. This study aims to investigate the impacts of spatiotemporal resolutions of precipitation on flood event simulation in a large-scale catchment of China. We use high-spatiotemporal-resolution Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) products and a gauge-based product as precipitation forcing for hydrologic simulation. Three hydrological models (HBV, SWAT and DHSVM) and a data-driven mo

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48

ANDERSON, JAMES J. "AN AGENT-BASED EVENT DRIVEN FORAGING MODEL." Natural Resource Modeling 15, no. 1 (2008): 55–82. http://dx.doi.org/10.1111/j.1939-7445.2002.tb00080.x.

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49

Purificação, Carolina, Nuno Andrade, Miguel Potes, Vanda Salgueiro, Flavio T. Couto, and Rui Salgado. "Modelling the Atmospheric Environment Associated with a Wind-Driven Fire Event in Portugal." Atmosphere 13, no. 7 (2022): 1124. http://dx.doi.org/10.3390/atmos13071124.

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Increased knowledge of the meteorological conditions that lead to mega-fires is important to prevent wildfires and improve firefighting. This study analyses the atmospheric conditions that led to the largest forest fire ever observed in Portugal in 2019. The fire burned an estimated total area of around 9000 hectares in 12 h. The study is based on two simulations performed with the Meso-NH atmospheric model. The control simulation was configured in a single and large domain with 2500 m resolution, whereas a second simulation was configured using the grid nesting technique with an inner domain

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Holm, Elizabeth A., Mark A. Miodownik, and Kristopher J. Healey. "A Subgrain Growth Model for Strain-Free Grain Nucleation during Recrystallization." Materials Science Forum 467-470 (October 2004): 611–16. http://dx.doi.org/10.4028/www.scientific.net/msf.467-470.611.

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The origin of the strain-free crystallites that nucleate the recrystallization process has been debated for decades. Realistic, three-dimensional computer simulations indicate that the nucleation event is the mobility-driven abnormal growth of certain subgrains. Based on these observations, we derive a model that incorporates subgrain topology, texture, boundary distribution and boundary properties to predict the frequency of the abnormal growth events that lead to nucleation. The qualitative and quantitative agreement between theory, simulation, and experiments is excellent.

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