همکاری چارچوب شبیه سازی بر اساس محیط محاسباتی توزیع شده
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|11448||2012||6 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : AASRI Procedia,, Volume 3, 2012, Pages 571-576
Large-scale complex system modeling and simulation involves multidisciplinary knowledge. It is usually necessary to create models using different modeling languages and methods. Therefore, a simulation system built by these models has the characteristics of heterogeneous and hierarchical structure. It will be a great challenge in designing and controlling simulation execution. This paper proposed a hierarchical modeling method and designed a synchronous control algorithm based on synchronous points array. Then we implemented a collaborative simulation framework based on distributed computing environment. The result illustrates this framework provides an efficient mechanism to support hierarchical modeling. With the rate of computing load to communication load increasing, the parallelism will be higher, thus the performance of the simulation system can be promoted.
Collaborative simulation is a simulation technology which organizes varied models to work together for analysis and evaluation. The models are usually located in different geographical areas, based on different computer systems, or built with different modeling languages and different modeling tools [1, 2]. The main idea of collaborative simulation is to solve simulation problems within the course of designing complex systems . Although some existing simulation tools, to some degree, can solve most analysis and evaluation issues of complex systems in single domain, they lack the support for complex system simulation in multidomain . With the increase of sophistication and complexity within complex systems, it is difficult to solve the problem only use one kind of simulation tools . Therefore, collaborative simulation technology for complex system simulation in multidomain becomes an important trend [6, 7]. Recently, a collaborative simulation system often combines hydromechanics, aerodynamics, mechanical control models to achieve united simulation. It involves various computing models with multidisciplinary knowledge . Besides, each computing model is developed using various modeling languages and simulation tools. As a result, the simulation system composed of those models has the characteristics of heterogeneous and hierarchical [9, 10]. It brings a great challenge in the design and corporative control of simulation systems. To solve this problem, the paper proposed a collaborative simulation framework based on distributed computing environment. The results illustrate this framework provides an efficient mechanism to support hierarchical modeling. Moreover in the distributed computing environment, the performance of the collaborative simulation system can be improved. The remainder of this paper is structured as follows: in section 2 we explain our collaborative simulation framework in detail. In section 3 we give the analysis with experiment. Finally, our conclusion will be made with an indication of the future work.
نتیجه گیری انگلیسی
With the development of simulation application, complex system oriented collaborative simulation technology expended from single domain to multidomain. This paper proposed a graphic heterogeneous and hierarchical modeling approach, and designed a synchronous control algorithm based on synchronous points array. We implemented a collaborative simulation framework based on distributed computing environment. This framework provides an efficient mechanism to realize data sharing among multidisciplinary models. It is an efficient method for complex system simulation. The results of the experiment illustrate that with the rate of computing load to communication load increasing, the parallelism of the simulation system model will be higher, thus the performance can be promoted. In the future, we plan to design various experiments for our simulation framework on high performance computing environment, and utilize the results to improve it. Another interesting line of investigation would be the research on the efficiency of communication in our collaborative simulation framework