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Wyszukujesz frazę "Computing simulation" wg kryterium: Temat

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    Wyświetlanie 1-6 z 6
    Tytuł:
    Weballted : interdisciplinary modeling in grid and cloud
    Autorzy:
    Zgurovsky, M.
    Petrenko, A.
    Ladogubets, V.
    Finogenov, O.
    Bulakhova, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/305515.pdf
    Data publikacji:
    2013
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    simulation
    grid computing
    cloud computing
    SOA
    web services
    Opis:
    This paper presents a multi-layered architecture of computer simulation software capable of utilizing grid and cloud resources, characterized in that the functionality of the system is distributed according to a service-oriented approach, and the system supports the execution of custom user-defined computing scenarios in grid or in cloud (by web services orchestration with an adherence to existing standards) but hides the complexity of direct web services management from the user with the help of the abstract workflow model and a web-accessible problem solving environment with a graphical workflow editor.
    Źródło:
    Computer Science; 2013, 14 (2); 295-306
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Simulation of manufacturing and logistics systems for the 21th century
    Autorzy:
    Palajová, S.
    Figa, Š.
    Gregor, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/117896.pdf
    Data publikacji:
    2011
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    simulation
    emulation
    metamodelling
    cloud computing
    Opis:
    This paper deals with computer simulation of manufacturing systems. It contains the basic simulation theory and principles of a simulation project management. Furthermore the authors introduced the idea of parametric simulation model, followed by special application areas of simulation, e.g. scheduling, emulation, metamodelling. The paper discusses the possibility to utilize a cloud computing technology in simulation. The case example of the application of simulation by the optimization of real production system concludes the working part of paper. The final part summarizes benefits and recommendations.
    Źródło:
    Applied Computer Science; 2011, 7, 2; 47-60
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Simulation of manufacturing and logistics systems for the 21th century
    Autorzy:
    Palajová, S.
    Figa, S.
    Gregor, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/118003.pdf
    Data publikacji:
    2012
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    simulation
    emulation
    metamodelling
    cloud computing
    Opis:
    This paper deals with computer simulation of manufacturing systems. It contains the basic simulation theory and principles of a simulation project management. Furthermore the authors introduced the idea of parametric simulation model, followed by special application areas of simulation, e.g. scheduling, emulation, metamodelling. The paper discusses the possibility to utilize a cloud computing technology in simulation. The case example of the application of simulation by the optimization of real production system concludes the working part of paper. The final part summarizes benefits and recommendations.
    Źródło:
    Applied Computer Science; 2012, 8, 1; 45-57
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Artificial Life. Biologically-inspired algorithms
    Autorzy:
    Komosiński, Maciej
    Powiązania:
    https://bibliotekanauki.pl/articles/703205.pdf
    Data publikacji:
    2008
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial life
    simulation
    biologically-inspired algorithms
    evolution
    computing
    Opis:
    This article presents Artificial Life, an interdisciplinary field of study that helps understand life on Earth (life as we know it) and other, possible kinds of life (as it could be). Artificial Life research builds models of life and synthesizes related phenomena and processes in all currently available media – software, hardware and wetware. The first part of this work focuses on Artificial Life as a research field. In the second part, three exemplary computer science algorithms are shown that are inspired by biological processes. These are evolutionary and coevolutionary algorithms, swarm intelligence and ant algorithms, and artificial immune systems. The final part of this work provides a number of reflections on the goals of Artificial Life research, human nature and limitations, and our problems with evaluating complex outcomes of digital life experimentation.
    Źródło:
    Nauka; 2008, 4
    1231-8515
    Pojawia się w:
    Nauka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Using a vision cognitive algorithm to schedule virtual machines
    Autorzy:
    Zhao, J.
    Mhedheb, Y.
    Tao, J.
    Jrad, F.
    Liu, Q.
    Streit, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/330838.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    cloud computing
    vision cognitive algorithm
    VM scheduling
    simulation
    chmura obliczeniowa
    algorytm poznawczy
    szeregowanie
    symulacja
    Opis:
    Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NP-hard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 3; 535-550
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A hybrid scheduler for many task computing in big data systems
    Autorzy:
    Vasiliu, L.
    Pop, F.
    Negru, C.
    Mocanu, M.
    Cristea, V.
    Kolodziej, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/907647.pdf
    Data publikacji:
    2017
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    many task computing
    scheduling heuristics
    QoS
    big data system
    simulation
    obliczenia wielofunkcyjne
    szeregowanie zadań
    duży zbiór danych
    Opis:
    With the rapid evolution of the distributed computing world in the last few years, the amount of data created and processed has fast increased to petabytes or even exabytes scale. Such huge data sets need data-intensive computing applications and impose performance requirements to the infrastructures that support them, such as high scalability, storage, fault tolerance but also efficient scheduling algorithms. This paper focuses on providing a hybrid scheduling algorithm for many task computing that addresses big data environments with few penalties, taking into consideration the deadlines and satisfying a data dependent task model. The hybrid solution consists of several heuristics and algorithms (min-min, min-max and earliest deadline first) combined in order to provide a scheduling algorithm that matches our problem. The experimental results are conducted by simulation and prove that the proposed hybrid algorithm behaves very well in terms of meeting deadlines.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2017, 27, 2; 385-399
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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