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Relevant bibliographies by topics / Distributed systems simulation

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Academic literature on the topic 'Distributed systems simulation'

Author: Grafiati

Published: 28 June 2021

Last updated: 2 February 2022

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Journal articles on the topic "Distributed systems simulation"

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Karatza, Helen D., and Georgios K. Theodoropoulos. "Distributed Systems Simulation." Simulation Modelling Practice and Theory 14, no. 6 (August 2006): 677–78. http://dx.doi.org/10.1016/j.simpat.2005.10.001.

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Vasileva, Svetlana, and Aleksandar Milev. "Simulation Studies of Distributed Two-phase Locking in Distributed Database Management Systems." Information Technologies and Control 13, no. 1-2 (June 1, 2015): 46–55. http://dx.doi.org/10.1515/itc-2016-0010.

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Abstract This paper considers algorithms simulating the implementation of distributed two-phase locking (2PL) protocols in distributed database systems and simulation results. It describes specifically the simulations of two-version 2PL and 2PL with integrated timestamp ordering mechanism. Integrated modelling algorithms for deadlock avoiding are suggested in the paper: twoversion architecture of database and timestamp ordering strategy “wait-die”. The results of the simulations of these two variants of the 2PL method at different scales of the networks for data transmission and at different intensities of inflow transactions are also presented. Modelling algorithms are developed by means of the system for simulation modelling GPSS World Personal Version.

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Reed, Morton W. "Distributed simulation using distributed control systems." ACM SIGSIM Simulation Digest 20, no. 4 (April 1990): 143–51. http://dx.doi.org/10.1145/99637.99656.

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Logan, B., and G. Theodoropoulos. "The distributed simulation of multiagent systems." Proceedings of the IEEE 89, no. 2 (2001): 174–85. http://dx.doi.org/10.1109/5.910853.

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Bley, Helmut, Claas Christian Wuttke, and Wolfgang Massberg. "Distributed Simulation Applied to Production Systems." CIRP Annals 46, no. 1 (1997): 361–64. http://dx.doi.org/10.1016/s0007-8506(07)60843-9.

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Righter, R., and J. C. Walrand. "Distributed simulation of discrete event systems." Proceedings of the IEEE 77, no. 1 (1989): 99–113. http://dx.doi.org/10.1109/5.21073.

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Kumar, D. "Systems with low distributed simulation overhead." IEEE Transactions on Parallel and Distributed Systems 3, no. 2 (March 1992): 155–65. http://dx.doi.org/10.1109/71.127257.

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Kumar, Devendra. "Efficient distributed simulation of acyclic systems." Information Sciences 66, no. 1-2 (December 1992): 167–90. http://dx.doi.org/10.1016/0020-0255(92)90092-m.

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INUKAI, Toshihiro, Hironori HIBINO, and Yoshiro FUKUDA. "Efficient Design and Evaluation for Manufacturing Systems Using Distributed Real Simulation(Manufacturing systems and Scheduling)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.2 (2005): 397–402. http://dx.doi.org/10.1299/jsmelem.2005.2.397.

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Çakmak, Hüseyin, Anselm Erdmann, Michael Kyesswa, Uwe Kühnapfel, and Veit Hagenmeyer. "A new distributed co-simulation architecture for multi-physics based energy systems integration." at - Automatisierungstechnik 67, no. 11 (November 26, 2019): 972–83. http://dx.doi.org/10.1515/auto-2019-0081.

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Abstract Simulating energy systems integration scenarios enables a comprehensive consideration of interdependencies between multimodal energy grids. It is an important part of the planning for the redesign of the current energy system infrastructure, which is essential for the foreseen drastic reduction of carbon emissions. In contrast to the complex implementation of monolithic simulation architectures, emerging distributed co-simulation technologies enable the combination of several existing single-domain simulations into one large energy systems integration simulation. Accompanying disadvantages of coupling simulators have to be minimized by an appropriate co-simulation architecture. Hence, in the present paper, a new simulation architecture for energy systems integration co-simulation is introduced, which enables an easy and fast handling of the therefore required simulation setup. The performance of the new distributed co-simulation architecture for energy systems integration is shown by a campus grid scenario with a focus on the effects of power to gas and the reversal process onto the electricity grid. The implemented control strategy enables a successful co-simulation of electrolysis coupled with photovoltaics, a hydrogen storage with a combined heat and power plant and a variable power consumption.

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Dissertations / Theses on the topic "Distributed systems simulation"

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Gubba, Ravikumar Krishnanjan. "Distributed simulation of power systems using real time digital simulator." Master's thesis, Mississippi State : Mississippi State University, 2009. http://library.msstate.edu/etd/show.asp?etd=etd-06152009-222641.

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Kim, Song Hun. "Distributed Reconfigurable Simulation for Communication Systems." Diss., Virginia Tech, 2002. http://hdl.handle.net/10919/29700.

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The simulation of physical-layer communication systems often requires long execution times. This is due to the nature of the Monte Carlo simulation. To obtain a valid result by producing enough errors, the number of bits or symbols being simulated must significantly exceed the inverse of the bit error rate of interest. This often results in hours or even days of execution using a personal computer or a workstation. Reconfigurable devices can perform certain functions faster than general-purpose processors. In addition, they are more flexible than Application Specific Integrated Circuit (ASIC) devices. This fast yet flexible property of reconfigurable devices can be used for the simulation of communication systems. However, although reconfigurable devices are more flexible than ASIC devices, they are often not compatible with each other. Programs are usually written in hardware description languages such as Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL). A program written for one device often cannot be used for another device because these devices all have different architectures, and programs are architecture-specific. Distributed computing, which is not a new concept, refers to interconnecting a number of computing elements, often heterogeneous, to perform a given task. By applying distributed computing, reconfigurable devices and digital signal processors can be connected to form a distributed reconfigurable simulator. In this paper, it is shown that using reconfigurable devices can greatly increase the speed of simulation. A simple physical-layer communication system model has been created using a WildForce board, a reconfigurable device, and the performance is compared to a traditional software simulation of the same system. Using the reconfigurable device, the performance was increased by approximately one hundred times. This demonstrates the possibility of using reconfigurable devices for simulation of physical-layer communication systems. Also, an middleware architecture for distributed reconfigurable simulation is proposed and implemented. Using the middleware, reconfigurable devices and various computing elements can be integrated. The proposed middleware has several components. The master works as the server for the system. An object is any device that has computing capability. A resource is an algorithm or function implemented for a certain object. An object and its resources are connected to the system through an agent. This middleware system is tested with three different objects and six resources, and the performance is analyzed. The results shows that it is possible to interconnect various objects to perform a distributed simulation using reconfigurable devices. Possible future research to enhance the architecture is also discussed.
Ph. D.

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Khan, Izhar Ahmed. "A Distributed Context Simulation Component." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-32576.

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Mobile devices with access to large numbers of sensors with internet access move forwards the development of intelligent applications towards new shape of ubiquitous applications. In order to create such applications we need to be able to do simulations to test and deploy. Current simulators do not permit this since they are centralized and the information is not shared globally. Therefore we cannot use them to test application built on distributed sensor information. I selected Siafu as the simulator component. In the next step, the simulator was customized according to the requirements of the project. There are different possibilities to achieve this task, but a simple GUI is made to control the simulator.The end result is a complete architecture for simulating context aware scenarios. The implementation is tested by running the simulator and dumping the context data into the PGRID overlay. For future work, implementing proximity estimation between the agents will be a good idea and can be interesting as well.

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Jeon, Dae Kyung. "Methodologies for developing distributed systems in Ada with a simulation of a distributed Ada system." Virtual Press, 1989. http://liblink.bsu.edu/uhtbin/catkey/722459.

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In recent years, the field of distributed processing, distributed systems, has undergone great change, and has been an area attracting tremendous research and development efforts. This thesis explores the various current methodologies for designing, developing and implementing distributed systems using the Ada programming language, and goes on to implement a simulation of a distributed store system using the "virtual node" design approach. After a brief introduction on distributed systems in general, an investigation of the basic issues and problems involved in distributing Ada programs coupled with an analysis and comparison of various approaches to developing distributed Ada systems is carried out. It is shown that one of the critical problems of Ada in a distributed environment is its implicit assumption of a single memory processor. A simulation of a distributed system (store system) is carried out using the virtual node method of developing distributed Ada systems. The various stages of this design method including interface task specification are stepped through. A sample run of the. system is given, including the customer file, stock file data and the monitored output of the system.
Department of Computer Science

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Dawson, Jeffrey. "A HOLISTIC USABILITY FRAMEWORK FOR DISTRIBUTED SIMULATION SYSTEMS." Doctoral diss., University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2346.

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This dissertation develops a holistic usability framework for distributed simulation systems (DSSs). The framework is developed considering relevant research in human-computer interaction, computer science, technical writing, engineering, management, and psychology. The methodology used consists of three steps: (1) framework development, (2) surveys of users to validate and refine the framework, and to determine attribute weights, and (3) application of the framework to two real-world systems. The concept of a holistic usability framework for DSSs arose during a project to improve the usability of the Virtual Test Bed, a prototypical DSS, and the framework is partly a result of that project. In addition, DSSs at Ames Research Center were studied for additional insights. The framework has six dimensions: end user needs, end user interface(s), programming, installation, training, and documentation. The categories of participants in this study include managers, researchers, programmers, end users, trainers, and trainees. The first survey was used to obtain qualitative and quantitative data to validate and refine the framework. Attributes that failed the validation test were dropped from the framework. A second survey was used to obtain attribute weights. The refined framework was used to evaluate two existing DSSs, measuring their holistic usabilities. Ensuring that the needs of the variety of types of users who interact with the system during design, development, and use are met is important to launch a successful system. Adequate consideration of system usability along the several dimensions in the framework will not only ensure system success but also increase productivity, lower life cycle costs, and result in a more pleasurable working experience for people who work with the system.
Ph.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering and Management Systems

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Leuhusen, Joakim, and Andreas Karlsson. "Simulation and synchronization of distributed real-time systems." Thesis, Linköping University, Vehicular Systems, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-52784.

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Today we are very much dependent on diﬀerent kinds of real time systems. Usually,a real time system is a system which is interacting with a physical environmentwith sensors or activators. There are many advantages by replacing mechanicalcomponents with electrical ones. For instance, it is usually cheaper and possibleto add new functions to the device without replacing the electronic part, whichwould have been necessary with a mechanical one.The possibility of simulating a distributed system is used throughout the vehi-cle industry. With the simulation of connected sub systems, using modeled busesand real time kernels, one could increase the correctness of the behavior of the sys-tem and consequently decrease the amount of time spent later in the developingprocess.In this master thesis we used modeled CAN-buses and real time models tosimulate the connection and execution time of the systems. The simulation resultsare used to validate the functionality of the distributed system. Additionally, aworst-case response time analysis is made to set timing constraints on the systemto fulﬁll given deadlines.During the work, diﬀerent settings of the network are tested to analyze thesystem frequency needed to sustain deadlines and correctness on the network.

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Hosseinzaman, Abbas. "The parallel and distributed simulation of network systems." Thesis, Nottingham Trent University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283272.

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Hoaglund, Catharine McIntire. "Design factors for the communication architecture of distributed discrete event simulation systems." CSUSB ScholarWorks, 2006. https://scholarworks.lib.csusb.edu/etd-project/3058.

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The purpose of the thesis was to investigate the influence communication architecture decisions have on the performance of a simulation system with distributed components. In particular, the objective was to assess the relative importance of factors affecting reliability and variability of an external data interface to the performance of the simulation, as compared to factor within the simulation itself.

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Pastrana, John. "Model-Based Systems Engineering Approach to Distributed and Hybrid Simulation Systems." Doctoral diss., University of Central Florida, 2014. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6336.

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INCOSE defines Model-Based Systems Engineering (MBSE) as "the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases." One very important development is the utilization of MBSE to develop distributed and hybrid (discrete-continuous) simulation modeling systems. MBSE can help to describe the systems to be modeled and help make the right decisions and partitions to tame complexity. The ability to embrace conceptual modeling and interoperability techniques during systems specification and design presents a great advantage in distributed and hybrid simulation systems development efforts. Our research is aimed at the definition of a methodological framework that uses MBSE languages, methods and tools for the development of these simulation systems. A model-based composition approach is defined at the initial steps to identify distributed systems interoperability requirements and hybrid simulation systems characteristics. Guidelines are developed to adopt simulation interoperability standards and conceptual modeling techniques using MBSE methods and tools. Domain specific system complexity and behavior can be captured with model-based approaches during the system architecture and functional design requirements definition. MBSE can allow simulation engineers to formally model different aspects of a problem ranging from architectures to corresponding behavioral analysis, to functional decompositions and user requirements (Jobe, 2008).
Ph.D.
Doctorate
Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering

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Hendry, Barbara. "Distributed object-oriented discrete event simulation /." Online version of thesis, 1990. http://hdl.handle.net/1850/10999.

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Books on the topic "Distributed systems simulation"

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Models and analysis in distributed systems. London: Wiley, 2011.

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IMACS World Congress on Scientific Computation (12th 1988 Paris, France). Complex and distributed systems: Analysis, simulation and control. Amsterdam: North-Holland, 1986.

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IMACS, World Congress on Scientific Computation (12th 1988 Paris France). Complex and distributed systems: Analysis, simulation and control. Amsterdam: North-Holland, 1986.

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Mihail-Ioan, Abrudean, Unguresan Mihaela-Ligia, Muresan Vlad, and SpringerLink (Online service), eds. Numerical Simulation of Distributed Parameter Processes. Heidelberg: Springer International Publishing, 2013.

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Parallel and distribution simulation systems. New York: Wiley, 2000.

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Jiao, Zhuang. Distributed-Order Dynamic Systems: Stability, Simulation, Applications and Perspectives. London: Springer London, 2012.

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Ikonen, Jouni. Improving distributed simulation in a workstation environment. Lappeenranta: Lappeenranta University of Technology, 2001.

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S©ırensen, Troels B. Intelligent Distributed Antenna Systems (IDAS): Assessment by measurement and simulation. Aalborg: Dept. of Communication Technology, Institute of Electronic Systems, Aalborg University, 2003.

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SCS Multiconference on Distributed Simulation (1990 San Diego, Calif.). Distributed simulation: Proceedings of the SCS Multiconference on Distributed Simulation, 17-19 January, 1990, San Diego, California. San Diego, Calif: Society for Computer Simulation, 1990.

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Harman, William David. Robust flight control: A distributed real-time simulation investigation. [Downsview, Ont.]: University of Toronto, Institute for Aerospace Studies, 2002.

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Book chapters on the topic "Distributed systems simulation"

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Igarza, Jean-Louis. "Distributed Simulation." In Simulation and Modeling of Systems of Systems, 295–332. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118616727.ch7.

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Loper, Margaret L. "Distributed Simulation." In Modeling and Simulation in the Systems Engineering Life Cycle, 241–53. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-5634-5_20.

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Zhou, Mike. "Distributed Parallel Power System Simulation." In Power Systems, 71–100. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32683-7_3.

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Karatza, Helen D. "Simulation of Parallel and Distributed Systems Scheduling." In Applied System Simulation, 61–80. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9218-5_4.

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Petkovski, Dj B. "Knowledge-Based Systems for Distributed Decision-Making." In Advances in Simulation, 406–11. New York, NY: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-6389-7_81.

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Lees, Michael, Brian Logan, Rob Minson, Ton Oguara, and Georgios Theodoropoulos. "Modelling Environments for Distributed Simulation." In Environments for Multi-Agent Systems, 150–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-32259-7_8.

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Igbe, Damian, N. Kalantery, S. E. Ijaha, and S. C. Winter. "Parallel Traffic Simulation in Spider Programming Environment." In Distributed and Parallel Systems, 165–72. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1167-0_20.

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Corcuera, Pedro, Mario Garcés, Eduardo Mora, and Marta Zorrilla. "Distributed Simulation with Multimedia Interface." In Computer Aided Systems Theory - EUROCAST’99, 334–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10720123_30.

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Ghasem, Nayef. "Mass Transport of Distributed Systems." In Modeling and Simulation of Chemical Process Systems, 223–72. Boca Raton, FL : CRC Press/Taylor & Francis Group, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/b22487-5.

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Ghasem, Nayef. "Heat Transfer Distributed Parameter Systems." In Modeling and Simulation of Chemical Process Systems, 273–361. Boca Raton, FL : CRC Press/Taylor & Francis Group, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/b22487-6.

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Conference papers on the topic "Distributed systems simulation"

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Iazeolla, G., A. Pieroni, A. D'Ambrogio, and D. Gianni. "A distributed approach to the simulation of inherently distributed systems." In the 2010 Spring Simulation Multiconference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1878537.1878675.

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Alcacarenho, Nuno Miguel Nave, and Joao Almeida das Rosas. "Distributed Manufacturing Systems simulation platform." In 2017 International Young Engineers Forum (YEF-ECE). IEEE, 2017. http://dx.doi.org/10.1109/yef-ece.2017.7935634.

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Brumbulli, Mihal, and Joachim Fischer. "Simulation visualization of distributed communication systems." In 2012 Winter Simulation Conference - (WSC 2012). IEEE, 2012. http://dx.doi.org/10.1109/wsc.2012.6465021.

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Nadeem, M. Faisal, S. Arash Ostadzadeh, Stephan Wong, and Koen Bertels. "Task scheduling strategies for dynamic reconfigurable processors in distributed systems." In Simulation (HPCS). IEEE, 2011. http://dx.doi.org/10.1109/hpcsim.2011.5999811.

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Yin, Dengpan, and Tevfik Kosar. "A data-aware workflow scheduling algorithm for heterogeneous distributed systems." In Simulation (HPCS). IEEE, 2011. http://dx.doi.org/10.1109/hpcsim.2011.5999814.

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Azzedin, Farag. "Trust-based taxonomy for free riders in distributed multimedia systems." In Simulation (HPCS). IEEE, 2010. http://dx.doi.org/10.1109/hpcs.2010.5547108.

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Sharawi, Abeer, Serge Sala-diakanda, Adam Dalton, Sergio Quijada, Nabeel Yousef, Luis Rabelo, and Jose Sepulveda. "A Distributed Simulation Approach for Modeling and Analyzing Systems of Systems." In 2006 Winter Simulation Conference. IEEE, 2006. http://dx.doi.org/10.1109/wsc.2006.323191.

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Rodrigues, Cristiano, Daniel Castro Silva, Rosaldo J. F. Rossetti, and Eugenio Oliveira. "Distributed flight simulation environment using flight simulator X." In 2015 10th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2015. http://dx.doi.org/10.1109/cisti.2015.7170615.

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Baumann, Tommy. "Simulation-Driven Design of Distributed Systems." In SAE 2011 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2011. http://dx.doi.org/10.4271/2011-01-0458.

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Markowski, Adam, and Emil Michta. "Simulation of Distributed Measurement-Control Systems." In 2007 IEEE Instrumentation & Measurement Technology Conference IMTC 2007. IEEE, 2007. http://dx.doi.org/10.1109/imtc.2007.378995.

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Reports on the topic "Distributed systems simulation"

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Rutherford, Matthew J., Antonio Carzaniga, and Alexander L. Wolf. Simulation-Based Testing of Distributed Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada444809.

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Varaiya, Pravin. Distributed Interactive Simulation for Intelligent Vehicle Highway Systems. Fort Belvoir, VA: Defense Technical Information Center, August 1997. http://dx.doi.org/10.21236/ada328724.

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Smith, Mark E. Distributed Test and Evaluation of Aerospace Systems: The Joint Advanced Distributed Simulation Joint Test Force Experience. Fort Belvoir, VA: Defense Technical Information Center, August 1999. http://dx.doi.org/10.21236/ada378017.

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Fujimoto, Richard, Michael Hunter, and Haesun Park. Dynamic Systems for Individual Tracking via Heterogeneous Information Integration and Crowd Source Distributed Simulation. Fort Belvoir, VA: Defense Technical Information Center, December 2015. http://dx.doi.org/10.21236/ad1004753.

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Luckham, David C. Formal Specification and Simulation of Reference Architectures for Distributed and Safety Critical Avionics Systems. Fort Belvoir, VA: Defense Technical Information Center, March 1998. http://dx.doi.org/10.21236/ada379499.

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Lerman, David J., Richard L. Rogers, Jr Stephens, and Clarence W. Eliminating Positional Discrepancies Encountered during Integration of Dissimilar Systems on a Distributed Interactive Simulation Network. Fort Belvoir, VA: Defense Technical Information Center, July 1997. http://dx.doi.org/10.21236/ada498618.

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Branson, Roger, and Howard Fry. Advanced Distributed Simulation Technology Advanced Rotary Wing Aircraft. Strawman Verification and Validation Plan for the ARWA Simulator System. Fort Belvoir, VA: Defense Technical Information Center, April 1994. http://dx.doi.org/10.21236/ada280237.

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Branson, Roger, and Robert Anschuetz. Advanced Distributed Simulation Technology Advanced Rotary Wing Aircraft. System/Segment Specification. Volume 5. Simulation System Module AH-64D Kit. Fort Belvoir, VA: Defense Technical Information Center, March 1994. http://dx.doi.org/10.21236/ada280433.

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Branson, Roger, and Robert Anschuetz. Advanced Distributed Simulation Technology Advanced Rotary Wing Aircraft. System/Segment Specification. Volume 3. Visual System Module. Fort Belvoir, VA: Defense Technical Information Center, March 1994. http://dx.doi.org/10.21236/ada280239.

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Anschuetz, Robert R., and II. Advanced Distributed Simulation Technology Advanced Rotary Wing Aircraft. Software Programmer's Manual Visual System Module. Fort Belvoir, VA: Defense Technical Information Center, April 1994. http://dx.doi.org/10.21236/ada280260.

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