面向DEVS的多范式建模与仿真关键技术研究与实现
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摘要
随着军事领域联合作战、工程领域载人航天和社会领域应急管理等复杂系统的规模的日益扩大,传统建模与仿真方法难以满足其对多领域和仿真性能等方面更高的要求。而多范式建模与仿真方法,这一新的复杂系统建模与仿真支撑技术对于适应多体系联合作战等复杂系统仿真具有重要意义,故对此关键技术的研究显得非常重要。论文针对多体系联合作战,从理论基础、模型变换方法和仿真优化方法三个方面对多范式建模与仿真方法进行系统的研究。
多范式建模方法的理论基石是一般系统理论和模型变换方法。复杂系统的多领域性由一般系统理论衍生出的大量基本形式化方法支持;而仿真一致性则由模型变换和仿真互联方法保证。对离散事件系统规范(Discrete EVent System specification,DEVS)的研究表明,DEVS可以等价描述其他连续和离散的形式化方法。因此,在基于元模型的模型变换理论指导下,论文选择DEVS作为通用仿真形式化方法(General Property Simulation Formalism,GPSF),研究将多体系联合作战系统中多领域模型变换为DEVS模型的一系列方法:
(1)对描述宏观行为的StateCharts模型变换为DEVS模型的方法进行研究,以解决高低层次模型之间协同仿真的问题。变换方法建立了包括语法、状态和事件三个方面的变换规则,实现了迁移、使能条件和历史状态的等价以保证规则的完备性。
(2)对组件化的BOM模型变换为DEVS模型的方法进行了研究,以重用BOM模型。变换方法采用将组件内核映射到DEVS模型的方式实现从BOM到DEVS的变换,证明了采用相同组件内核的DEVS-CK模型与BOM组件模型是等价的。
(3)基于DEVS耦合模型的耦合和封闭特性,对DEVS耦合模型的扁平化方法进行研究。通过剥离模型层次化和构造扁平化原子模型两个步骤完成耦合模型的扁平化,从而解决高耦合度模型通信效率低的问题。
(4)对多体系联合作战系统中连续-离散混合系统的模型描述问题进行研究,提出利用Modelica语言描述混合系统DEVS模型的方法。实现了Modelica-DEVS编译器,将Modelica模型编译为可以执行的仿真模型。
在模型变换方法的基础上,为了提高仿真运行效率,论文分别从分布式仿真和模型活跃度两个角度对DEVS仿真的优化方法进行了研究:
(1)提出了基于MPI的分布式并行仿真框架,设计了支持乐观时间策略的DEVS仿真引擎以提高仿真性能。同时,在仿真框架中实现了错误探测、状态存储和系统恢复的算法使其具备了容错能力。
(2)基于模型活跃度提出了活跃度增强式建模方法,在领域模型中嵌入融合活跃度元模型(Activity Combined Meta Model,ACMM)实现活跃度操作。在追踪活跃度和资源占用量化方法的支持下,资源敏感(Resource-aware)仿真框架通过计算活跃度进行资源的重分配,达到最优配置。
此外,论文还提出了基于代理模型的仿真互联方法,解决DEVS和高层体系结构(High Level Arichitecture,HLA)仿真系统的互联问题;讨论了基于Web的仿真过程管理方法,支持对异构仿真系统的一体化管理工作,通过合理配置仿真资源优化系统运行。
基于以上研究工作,论文设计和实现了面向DEVS的多范式建模与仿真原理样机系统。在建模阶段,系统引用多种建模工具进行多领域建模,通过模型变换获得模型的一致性描述;在仿真阶段,系统利用基于Web的仿真实验管理工具和态势统计工具实现了B/S结构的仿真运行架构。最后通过多体系联合作战用例的测试,验证了论文所研究的多范式建模与仿真方法的可行性。
With the development of complex systems such as Joint Operations in military field, Manned Space Flight in engineering field, Emergency Response Management in social field, the traditional Modeling and Simulation theory cannot satisfy the requirements from complex systems such as multi-field and simulation performance now. Multi-Paradigm Modeling and Simulation which is a novel support technique can solve problems on Modeling and Simulation for Complex Systems. The research on the key techniques in Multi-Paradigm Modeling and Simulation means a lot to the Multi-System Joint Operations simulation. We study the Multi-Paradigm Modeling and Simualtion on three aspects: Basic Theory, Key Model Transformation methods and Simulation Optimization Algorithms.
General System Theory and Model Transformation are the basement of Multi-Paradigm Modeling and Simulation. The Multi-Field of Complex System is supported by the formalisms derived of General System Theory. The simulation consistence of Complex System is maintained by Model Transformation and Co-Simulation. The research on Discrete EVent System specification (DEVS) shows that DEVS could be used to equivalently describe other Continuous or Discrete formalisms. We select Discrete EVent System specification (DEVS) to be the General Property Simulation Formalism (GPSF) in Complex Systems. As a result, we study a series of Model Transformation for the Multi-Filed Models in Multi-System Joint Operation under the instruction of Meta-Model based Model Transformation.
(1) StateCharts is a typical high level formalism to describe the macroscopical behavior of system. The transformation from StateCharts to DEVS is proposed to sovle the interoperability between high level and low level models. Transform rules in gramar, state and event are constructed. The equivance of transition, guard conditions and history state is implemented to accquire the completeness of transformation.
(2) Base Object Model (BOM) is a model description in BOM-based Distributed Simulation. We reuse the Compenent Kernel in BOM model by developping the transformation from BOM to DEVS. We prove that DEVS-CK is equal to the BOM component if they use the identical Component Kernel.
(3)The Flattening algorithm of coupled DEVS model is proposed according to the closure under coupling of DEVS. It improves the efficiency in High Coupled Low Computation models. Flattening is realized by direct connection and flattened atomic model construction.
(4)As the continious-discrete systems are used a lot in Multi-Systems Joint operations, we give the DEVS description of Hybrid System in Modelica. Modelica-DEVS compilor is implmented to generate simulation models.
Based on the Model Transformation, we study the optimization algorithms for DEVS simulation in the view of distributed simulation and model activity:
(1) We propose the MPI-based distributed framework which supports parallel simulation. DEVS engine is designed to support optimistical time algorithm. The Fault Detection, State Storage and System Recovery are implemented in framework to do the Fault Tolerance.
(2) We present the Activity Enhancing Modeling based on model activity. Activity Combined Meta Model (ACMM) is designed to integrate the activity into model. With the help of Activity Tracing and Quantization of Resource Usage, the Resource-aware Modeling and Simulation framework can re-allocate the resource by the activity calculation.
In addition, we present an Agent-based Co-Simulation method, which works well in the Co-Simulation between DEVS and HLA simulation system. Meanwhile, the Web-based Simulation Management is given to support the integrated management for heterogeneous simulation.
Based on the research on the Multi-Paradigm Modeling and Simulation, we design and implement the prototype system. In the modeling phase, many kinds of modeling tools are reused in the system to do the Multi-Field Modeling. Model Transformation is used to maintain the consistence in model description. In the simulation phase, the web-based management and statistical tools are used to implement the B/S system structure. The Multi-System Joint Operation cases testify the research on key techniques for Multi-Paradigm Modeling and Simulation.
多范式建模方法的理论基石是一般系统理论和模型变换方法。复杂系统的多领域性由一般系统理论衍生出的大量基本形式化方法支持;而仿真一致性则由模型变换和仿真互联方法保证。对离散事件系统规范(Discrete EVent System specification,DEVS)的研究表明,DEVS可以等价描述其他连续和离散的形式化方法。因此,在基于元模型的模型变换理论指导下,论文选择DEVS作为通用仿真形式化方法(General Property Simulation Formalism,GPSF),研究将多体系联合作战系统中多领域模型变换为DEVS模型的一系列方法:
(1)对描述宏观行为的StateCharts模型变换为DEVS模型的方法进行研究,以解决高低层次模型之间协同仿真的问题。变换方法建立了包括语法、状态和事件三个方面的变换规则,实现了迁移、使能条件和历史状态的等价以保证规则的完备性。
(2)对组件化的BOM模型变换为DEVS模型的方法进行了研究,以重用BOM模型。变换方法采用将组件内核映射到DEVS模型的方式实现从BOM到DEVS的变换,证明了采用相同组件内核的DEVS-CK模型与BOM组件模型是等价的。
(3)基于DEVS耦合模型的耦合和封闭特性,对DEVS耦合模型的扁平化方法进行研究。通过剥离模型层次化和构造扁平化原子模型两个步骤完成耦合模型的扁平化,从而解决高耦合度模型通信效率低的问题。
(4)对多体系联合作战系统中连续-离散混合系统的模型描述问题进行研究,提出利用Modelica语言描述混合系统DEVS模型的方法。实现了Modelica-DEVS编译器,将Modelica模型编译为可以执行的仿真模型。
在模型变换方法的基础上,为了提高仿真运行效率,论文分别从分布式仿真和模型活跃度两个角度对DEVS仿真的优化方法进行了研究:
(1)提出了基于MPI的分布式并行仿真框架,设计了支持乐观时间策略的DEVS仿真引擎以提高仿真性能。同时,在仿真框架中实现了错误探测、状态存储和系统恢复的算法使其具备了容错能力。
(2)基于模型活跃度提出了活跃度增强式建模方法,在领域模型中嵌入融合活跃度元模型(Activity Combined Meta Model,ACMM)实现活跃度操作。在追踪活跃度和资源占用量化方法的支持下,资源敏感(Resource-aware)仿真框架通过计算活跃度进行资源的重分配,达到最优配置。
此外,论文还提出了基于代理模型的仿真互联方法,解决DEVS和高层体系结构(High Level Arichitecture,HLA)仿真系统的互联问题;讨论了基于Web的仿真过程管理方法,支持对异构仿真系统的一体化管理工作,通过合理配置仿真资源优化系统运行。
基于以上研究工作,论文设计和实现了面向DEVS的多范式建模与仿真原理样机系统。在建模阶段,系统引用多种建模工具进行多领域建模,通过模型变换获得模型的一致性描述;在仿真阶段,系统利用基于Web的仿真实验管理工具和态势统计工具实现了B/S结构的仿真运行架构。最后通过多体系联合作战用例的测试,验证了论文所研究的多范式建模与仿真方法的可行性。
With the development of complex systems such as Joint Operations in military field, Manned Space Flight in engineering field, Emergency Response Management in social field, the traditional Modeling and Simulation theory cannot satisfy the requirements from complex systems such as multi-field and simulation performance now. Multi-Paradigm Modeling and Simulation which is a novel support technique can solve problems on Modeling and Simulation for Complex Systems. The research on the key techniques in Multi-Paradigm Modeling and Simulation means a lot to the Multi-System Joint Operations simulation. We study the Multi-Paradigm Modeling and Simualtion on three aspects: Basic Theory, Key Model Transformation methods and Simulation Optimization Algorithms.
General System Theory and Model Transformation are the basement of Multi-Paradigm Modeling and Simulation. The Multi-Field of Complex System is supported by the formalisms derived of General System Theory. The simulation consistence of Complex System is maintained by Model Transformation and Co-Simulation. The research on Discrete EVent System specification (DEVS) shows that DEVS could be used to equivalently describe other Continuous or Discrete formalisms. We select Discrete EVent System specification (DEVS) to be the General Property Simulation Formalism (GPSF) in Complex Systems. As a result, we study a series of Model Transformation for the Multi-Filed Models in Multi-System Joint Operation under the instruction of Meta-Model based Model Transformation.
(1) StateCharts is a typical high level formalism to describe the macroscopical behavior of system. The transformation from StateCharts to DEVS is proposed to sovle the interoperability between high level and low level models. Transform rules in gramar, state and event are constructed. The equivance of transition, guard conditions and history state is implemented to accquire the completeness of transformation.
(2) Base Object Model (BOM) is a model description in BOM-based Distributed Simulation. We reuse the Compenent Kernel in BOM model by developping the transformation from BOM to DEVS. We prove that DEVS-CK is equal to the BOM component if they use the identical Component Kernel.
(3)The Flattening algorithm of coupled DEVS model is proposed according to the closure under coupling of DEVS. It improves the efficiency in High Coupled Low Computation models. Flattening is realized by direct connection and flattened atomic model construction.
(4)As the continious-discrete systems are used a lot in Multi-Systems Joint operations, we give the DEVS description of Hybrid System in Modelica. Modelica-DEVS compilor is implmented to generate simulation models.
Based on the Model Transformation, we study the optimization algorithms for DEVS simulation in the view of distributed simulation and model activity:
(1) We propose the MPI-based distributed framework which supports parallel simulation. DEVS engine is designed to support optimistical time algorithm. The Fault Detection, State Storage and System Recovery are implemented in framework to do the Fault Tolerance.
(2) We present the Activity Enhancing Modeling based on model activity. Activity Combined Meta Model (ACMM) is designed to integrate the activity into model. With the help of Activity Tracing and Quantization of Resource Usage, the Resource-aware Modeling and Simulation framework can re-allocate the resource by the activity calculation.
In addition, we present an Agent-based Co-Simulation method, which works well in the Co-Simulation between DEVS and HLA simulation system. Meanwhile, the Web-based Simulation Management is given to support the integrated management for heterogeneous simulation.
Based on the research on the Multi-Paradigm Modeling and Simulation, we design and implement the prototype system. In the modeling phase, many kinds of modeling tools are reused in the system to do the Multi-Field Modeling. Model Transformation is used to maintain the consistence in model description. In the simulation phase, the web-based management and statistical tools are used to implement the B/S system structure. The Multi-System Joint Operation cases testify the research on key techniques for Multi-Paradigm Modeling and Simulation.
引文
[1] Bertalanffy L V. General system theory [M]. New York, USA:Braziller, 1968.
[2] M Mitchell Waldrop. Complexity: the emerging science at the edge of order and chaos [M]. New York: Tocuhstone, 1992.
[3]钱学森,于景元,戴汝为.一个科学新领域——开放的复杂巨系统及其方法论[J].自然杂志, 1990, 13(1): 3~10.
[4]王行仁等.我国系统建模与仿真技术的发展-----为纪念中国系统仿真学会成立二十周年而作[J].系统仿真学报, 2009, 21(21): 6683~6688.
[5]黄柯棣,张金槐,查亚兵等.系统仿真技术[M].长沙:国防科技大学出版社,1998.
[6]李伯虎,柴旭东,朱文海等.现代建模与仿真技术发展中的几个焦点[J].系统仿真学报, 2004, 16(9): 1871~1878.
[7] Locke J. An Introduction to the Internet Networking Environment and SIMNET/DIS [R]. Naval Postgraduate School, 1993.
[8] IEEE Standard for Distributed Interactive Simulation Application Protocols. Std.1278.1a-1998 [S]. 1998.
[9] Weatherly R.M., Wilson A.L. and Canova B.S. Advanced Distributed Simulation through the Aggregate Level Simulation Protocol[C]//Wailea, Hawaii. 1996.
[10] IEEE Standard for Modeling and Simulation (M&S) High Level Architecture Object Model Template Specification [S]. IEEE Std 1516.2-2000, Sep. 2000.
[11] U.S. Department of Defense , Modeling and Simulation Master Plan, http://www.dmso.mil, 1995-10/2010-08.
[12] U.S. Defense Modeling and Simulation Office. Conceptual Models of the Mission Space (CMMS) Technical Framework. Feb 1997.
[13]胡晓峰,罗批,司光亚等.战争复杂系统建模与仿真[M].北京:国防大学出版社, 2005.
[14] Andreas Idebrant, Peter Fritzson, Martin Hagstr?m. AirCraft– A Modelica Library for Aircraft Dynamics Simulation[C]. //5th EuroSim Congress on Modeling and Simulation, Paris, 2004.
[15] Bernard P. Zeigler, Herbert Praehofer, Tag Gon King. Theory of Modeling and Simulation, 2nd Edition[M]. London: Acdemaic Press, 2000.
[16] Hans Vangheluwe, Juan de Lara, P. J. Mosterman. AN INTRODUCTION TO MULTI-PARADIGM MODELLING AND SIMULATION[C],//AI, Simulation and Planning in High Autonomy Systems, AIS‘2002', 2002:9~20.
[17] Holland J. Adaptation in Natural and Artificial Systems [M]. Cambridge, MA, USA: MIT Press, 1992.
[18] Joel L.Schff. Cellular Automata: A Discrete View of the World [M]. New York:JOHN WILEY & SONS, 2007.
[19] Kennedy J., Eberhart R. Particle Swarm Optimization[C]. //Proceedings of IEEE International Conference on Neural Networks. IV.2005:1942~1948.
[20]张明智,胡晓峰,司光亚,赵占龙.基于Agent的体系对抗仿真建模方法研究[J].系统仿真学报, 2005, 17(11): 2785~2792.
[21]钱学森,于景元,戴汝为.一个科学新领域——开放的复杂巨系统及其方法论[J].自然杂志, 1990, 13(1): 3~10.
[22]戴汝为.从定性到定量的综合集成技术[J].模式识别与人工智能,1991, 4 (1): 5~10.
[23]于景元,涂元季.从定性到定量综合集成方法一案例研究[J].系统工程理论与实践,2002, 22 (5):1~7.
[24] Davis P K, Bigelow J. Introduction to Multi-Resolution Model (MRM) with an Example Involving Precision Fires [C].// Enabling technology for Simulation Science (II), Proceeding of SPIE AeoroSense. 1998.
[25] Biddle M. A Proposed Scheme for Implementing Aggregation and Disaggregation in HLA [C].// Processing of 2000 Fall SIW. 2000.
[26]毛媛,刘杰,李伯虎.基于元模型的复杂系统建模方法研究[J].系统仿真学报, 2002, 14(4): 411~414, 454.
[27] OMG, Meta Object Facility (MOF) Specification Version 1.3[S], 2000.
[28]王飞跃.关于复杂系统的建模、分析、控制和管理[J].复杂系统与复杂性科学, 2006, 3(2): 26~34.
[29]刘晓平,唐益明,郑利平.复杂系统与复杂系统仿真研究综述[J].系统仿真学报, 2008, 20(23): 6303~6315.
[30] Balci, O.. The implementation of four conceptual frameworks for simulation modeling in high-level languages[C]. // Proceedings of the Winter Simulation Conference, San Diedo: Society for Computer Simulation International (SCS), 1988:287~295.
[31]黄柯棣.对建模与仿真技术学科的粗浅理解——为庆祝《计算机仿真》杂志创刊20周年而写[J].计算机仿真, 2004, 21(9):F010~F013.
[32]军用仿真术语标准研究课题组.军用建模与仿真通用术语汇编[M].北京:国防工业出版社, 2004.
[33] Balci, O. Principles of simulation model validation, verification, and testing[J]. Transactions of the Society for Computer Simulation International, 1997, 14(1):3~12. Special Issue: Principles of Simulation.
[34] Magee, B. Popper[M]. London: Fontana Press (An Imprint of HarperCollins Publishers), 1985.
[35] Wymore., A. W., A Mathematical Theory of Systems Engineering– the Elements[M]. Wiley series on systems engineering and analysis. New York: Wiley, 1967.
[36] Zeigler, B. P.. Multifacetted Modelling and Discrete Event Simulation[M]. Academic Press, London, 1984.
[37] Engstrom E., & Krueger J.. A Meta-Modeler's Job is Never Done: Building and Evolving Domain-Specific Tools With DOME[C]. // IEEE International Symposium on Computer Aided Control System Design, 2000:83~88.
[38] Nordstrom G., Sztipanovits J., Karsai, G., Ledeczi, A.. Metamodeling-rapid design and evolution of domain-specific modeling environments[C] // Engineering of Computer-Based Systems, 1999. Proceedings. 1999: 68~74.
[39] Czarnecki K., & Helsen S.. Classification of Model Transformation Approaches[C]. // OOPSLA‘03 Workshop on Generative Techniques in the Context of Model-Driven Architecture, 2003.
[40]王学斌,吴泉源,史殿习.模型驱动架构中的模型转换方法[J].计算机工程与科学, 2006, 28(11): 133~135.
[41]鹿旭东,万建成.元模型支持下的模型转换[J].计算机工程与应用, 2005, 41:72~75.
[42] Dorr, H. Ef?cient graph rewriting and its implementation[M]. New York: Springer-Verlag, 1995.
[43] Olegas Vasilecas, D. B., APPLYING THE META-MODEL BASED APPROACH TO THE TRANSFORMATION OF ONTOLOGY AXIOMS INTO RULE MODEL[J]. INFORMATION TECHNOLOGY AND CONTROL, 2007, 36(1A): 122~125.
[44] Booth, Taylor L. Sequential Machines and Automata Theory (1st ed.)[M]. New York: John Wiley and Sons, 1967.
[45] Ashvin Radiya, Robert G. Sargent. A logic-based foundation of discrete event modeling and simulation[J]. ACM Transactions on Modeling and Computer Simulation, 1994, 1(1):3–51.
[46] Ki Hyung Kim, Yeong Rak Seong, Tag Gon Kim, Kyu Ho Park. Distributed simulation of hierarchical DEVS models: Hierarchical scheduling locally and time warp globally[J]. Transactions of the Society for Computer Simulation International, 1996, 13(3):135–154.
[47] Vangheluwe H.. DEVS as a common denominator for Multi-Formalism hybrid systems modeling[C].// IEEE International Symposium on Computer Aided Control System Design. Anchorage, Alaska, 2000:129~134.
[48] Bekey G. A., Kogan B. Y.(eds). Modeling and Simulation: Theory and Practice [M]. Norwell: Springer, 2003.
[49] Ernesto Kofman, J.S. Lee, B. Z., DEVS Representation of Differential Equation Systems: Review of Recent Advances[C]. // Proc of DEVS Workshop, European Simulation Conference. Prague, 2001:591~595.
[50]卢绍文.重叠交替更新过程的DTSS仿真校验的两个问题[J].自动化学报, 2009, 35(5):636~640.
[51] Moore, E. F.. Gedanken-experiments on Sequential Machines. AutomataStudies[J]. Annals of Mathematical Studies, 1956, 34:129~153.
[52]刘秀罗,黄柯棣,朱小俊.有限状态机在CGF行为建模中的应用[J].系统仿真学报, 2001, 13(5):663~665.
[53] Harel, D.. Statecharts: A Visual Formalism for Complex Systems[J]. Science of Computer Programming, 1987, 8(3):231~274.
[54]朱雪阳,唐稚松. Statecharts的组合语义与求精[J].软件学报, 2006, 17(4): 670~681.
[55]钱俊彦,赵岭忠.基于LTS的Statecharts操作语义研究[J].计算机工程, 2006, 32(22):43~45.
[56] Harel, D., Naamad, A. The STATEMATE semantics of statecharts[J]. ACM Trans. Softw. Eng. Methodol, 5(4), 293~333.
[57] S. Schulz, T.C. Ewing, J.W. Rozenblit. Discrete EVent System speci?cation (DEVS) and Statemate Statecharts equivalence for embedded systems modeling[C]. // 7th IEEE International Conference and Workshop on the Engineering of Computer Based Systems, Edinburgh: IEEE Computer Society, 2000.
[58]刘晨,王维平,朱一凡.状态机嵌入DEVS的组合建模方法研究[J].国防科技大学学报, 2005, 27(5):56~61.
[59] Spencer Borland, Hans Vangheluwe. Transforming statecharts to DEVS[C]. // Summer Computer Simulation Conference (Student Workshop), Montreal: Society for Computer Simulation International (SCS), 2003:154~159.
[60] SISO-STD-003-2006, Base Object Model (BOM) Template Specification[S]. SISO, 2006.
[61] J. Gong, C. Han, X. Qiu, and K. Huang. Constructing the Extensible HLA Federate Architecture[J]. Journal of System Simulation, 2006, 18(11):3126~3130.
[62] J. Gong and K. Huang. Research on HLA Composible Simulation Framework Based on BOM[C]. // Proceedings of the 7th International Conference on System Simulation and Scientific Computing, 2006: 59~60.
[63] IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA) - Frame and Rules[S]. Simulation Interoperability Standards Organization, 2000.
[64] IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA)- Federate Interface Specification[S]. Simulation Interoperability Standards Organization, 2000.
[65] Opdyke WF. Refactoring object-oriented frameworks [D]. Urbana-Champaign: University of Illinois, 1992.
[66] P. Gustavson, T. Chase. Using XML and BOMs to Rapidly Compose Simulation and Simulation Environment[C]. //Proceedings of the 2004 Winter Simulation Conference, Washington , 2004:1467~1475.
[67]龚建兴.基于BOM的可扩展仿真系统框架研究[D].长沙:国防科技大学,2007.
[68] Chow, A. C.-H.. Parallel DEVS: A parallel, hierarchical, modular modeling formalism and its distributed simulation[J]. Transactions of the Society for Computer Simulation International, 1996, 13 (2):55~67.
[69] B. Azzedine, M. Zhang, S. Ahmad. DEVS Approach to Real-Time RTI Design For Large-Scale Distributed Simulation Systems[J]. Simulation, 2008, 84(5):231~238.
[70] Alex Chun Hen Chow, Bernard P. Zeigler. Parallel DEVS: A parallel, hierarchical, modular, Modeling Formalism[C]. // Proceedings of 26th conference on Winter Simulation, San Diego: Society for Computer Simulation International, 1994:716~722.
[71] Z. Ming. An introduction to DEVS and Distributed DEVS[C]. //SpringSim‘08: Proceedings of the 2008 Spring simulation multiconference, San Diego: Society for Computer Simulation International, 2008: 351~351.
[72] G. F. Riley, R. Fujimoto, M. H. Ammar. Network aware Time Management and Event Distribution[C]. //Proc. of the 14th Workshop on Parallel and Distributed Simulation, Washingdon, DC: IEEE Computer Society, 2000.
[73] M. Zhang, B. Zeigler, P. Hammonds. DEVS/RMI-an Auto-Adaptive and Recon?gurable Distributed Simulation Environment for Engineering Studies[J]. Journal of Test and Evaluation, 2006, 27(1):49~60.
[74] S. Cheon, C. Seo, and B. P. Zeigler. Sunwoo Park. Design and Implementation of Distributed DEVS simulation in a Peer to Peer Network System[C]. //2004 Military, Government, and Aerospace Simulation, 2004.
[75] C. Seo, S. Park, B. Kim, S. Cheon, B. P. Zeigler. Implementation of Distributed High-performance DEVS Simulation Framework in the Grid Computing Environment[C]. // 2004 High Performance Computing Symposium, 2004.
[76] Himmelspach, J., A. M. Uhrmacher. Sequetial processing of pdevs models[C]. // 3rd European Modeling and Simulation, Barcelona, 2006:239~244.
[77] Himmelspach, J., R. Ewald, S. Leye, A. M. Uhrmacher. Parallel and distributed simulation of parallel DEVS models[C]. // SpringSim‘07: Proceedings of the 2007 spring simulation multiconference, San Diego: Society for Computer Simulation International, 2007:249~256.
[78] S. Cheon, C. Seo, B. P. Z., Sunwoo Park. Design and implementation of distributed devs simulation in a peer to peer network system[C]. // Military, Government, and Aerospace Simulation, 2004.
[79] H. Shang, G. A. Wainer. Dynamic structure DEVS: Improving the real-time embedded systems simulation and design[C]. // Annual Simulation Symposium, Ottawa: IEEE Computer Society, 2008:271~278.
[80] A. Muzy, J. Nutaro. Algorithms for ef?cient implementations of the DEVS & DSDEVS abstract simulators[C]. // 1st Open International Conference on Modeling & Simulation, 2005:273~279.
[81] P. Fritzson, P. Bunus. Modelica, A General Object-Oriented Language forContinuous and Discrete-Event System Modeling and Simulation[C]. // In Proceedings of the 35th Annual Simulation Symposium, 2002:14~18.
[82] H. Song. Infrastructure for devs modelling and experimentation[D]. Master Thesis in McGill University, Montreal, Canada, 2006.
[83] Hans L.M. Vangheluwe. DEVS as a Common Denominator for Multi-formalism Hybrid Systems Modeling[C]. // Proceedings of the 2000 IEEE International Symposium on Computer-Aided Control Shstem Design, Anchorage, 2007.
[84] Kofman, E., Lee, J., and Zeigler, B. DEVS Representation of Di?erential Equation Systems. Review of Recent Advances[C]. In Proceedings of ESS‘01, 2001.
[85] D‘Abreu M.C., Wainer G.A.. M/CD++: modeling continuous systems using Modelica and DEVS[C]. // 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, 2005:229~236.
[86] Mariana C. D‘abreu, Gabriel A. Wainer. Experimental results on the implementation of Modelica using DEVS modeling and simulation[C]. SIMULATION SERIES, 2006.
[87]吴义忠,蒋占四,陈立平.基于Modelica语言的多领域模型仿真优化研究[J].系统仿真学报, 2009, 21(12):2612~2615.
[88]赵建军,丁建完,周凡利,陈立平. Modelica语言及其多领域统一建模与仿真机理[J].系统仿真学报, 2006, 18(z2):570~573.
[89] Xu, W.. The Design and Implementation of theμModelica Compiler[D]. Montreal, Master's thesis. McGill University. School of Computer Science, 2005.
[90] Modelica– A Unified Object-Oriented Language for Physical Systems Modeling Language Specification[S]. Modelica Association, 2000.
[91] M. H. Hwang. DEVS++:C++ Open Source Library of DEVS Formalism. http://odevspp.sourceforge.net/, first edition, 2007.
[92] Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides. Design Patterns[M]. Reading, Massachusetts: Addison-Wesley Professional, 1995.
[93] Fujimoto, R. M. Parallel and distributed Simulation Systems[C]. // Proceedings of the Winter Simulation Conference, Arlington, 2001:147~157.
[94] Zeigler B, Cho H, Lee J., Sarjoughian H.. The DEVS/HLA Distributed Simulation Environment And Its Support for Predictive Filtering[R]. Tunson, AZ, ECE Department, University of Arizona, 1998.
[95] M. Zhang, B. P. Zeigler, P. Hammonds. DEVS/RMI-An Auto-Adaptive and Reconfigurable Distributed Simulation Environment for Engineering Studies[J]. ITEA Journal, 2005.
[96] C. Seo, S. Park, B. Kim, S. Cheon, B. P. Zeigler. Implementation of Distributed High-performance DEVS Simulation Framework in the Grid Computing Environment[C]. // Advanced Simulation Technologies conference (ASTC), Arlington, 2004.
[97] S. Mittal, J. L. Risco. DEVSML: Automating DEVS Execution over SOATowards Transparent Simulators[C]. // Special Session on DEVS Collaborative Execution and Systems Modeling over SOA, DEVS Integrative M&S Symposium, 2007.
[98]都志辉.高性能计算之并行编程技术——MPI并行程序设计[M].北京:清华大学出版社, 2001.
[99] Foster Ian. Designing and Building Parrallel Programs: Concepts and Tools for Parallel Software Engineering[M]. Reading, MA: Addison-Wesley, 1995.
[100] Jefferson D. Virtual Time[J]. ACM Transactions on Programming Languages and Systems, 7(3): 404~425.
[101]王学慧.并行与分布式仿真系统中的时间管理技术研究[D].长沙:国防科学技术大学, 2006.
[102] Richard M. Fujimoto. Parallel and Distributed Simulation Systems[M]. New York: Wiley, 2000.
[103] O.P. Damani, V.K. Garg. Fault-Tolerant Distributed Simulation[C]. // Parallel and Distributed Simulation, Workshop on Parallel and Distributed Simulation, Los Alamitos, 1998:3~8.
[104] Aguilar Jose, Hern′andez Marisela. Fault Tolerance Protocols for Parallel Programs Based on Tasks Replication[C]. MASCOTS‘00: Proceedings of the 8th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Washington. DC, 2000:397~404.
[105] Dan Chen, Stephen J. Turner, Wentong Cai. Towards Fault-tolerant HLA-based Distributed Simulations[J]. SIMULATION, 84(10-11):493~509.
[106] Min M., Shiyao J., Chaoqun Y., Xiaojian L.. Dynamic Fault Tolerance in Distributed Simulation System[C]. //Proc. International Conference on Computational Science (1), Reading, UK, 2006:769~776.
[107] S. Balsamo, A. Di Marco, P. Inverardi, M. Simeoni. Model-based performance prediction in software development: A survey[J]. IEEE Trans. Softw. Eng., 2004, 30(5):295~310.
[108] D. C. Petriu, H. Shen. Applying the UML performance pro?le: Graph grammar-based derivation of LQN models from UML speci?cations. SpringerVerlag, 2002:159~177.
[109] Chanda Ghose Dasguptaa, Gary S. Dispensab, Sanjoy Ghose. Comparing the predictive performance of a neural network model with some traditional market response models[J]. International Journal of Forecasting, 1994, 10(2):235~244.
[110] A. Muzy, B. Zeigler. Introduction to the activity tracking paradigm in component-based simulation[J]. The Open Cybernetics and Systemics Journal, 2008, 2:48~56.
[111] X. H., Lewis Ntaimo. DEVS-FIRE: Towards an integrated simulation environment for surface wild?re spread and containment[J]. SIMULATION, 2008, 84(4): 137~155.
[112] X. Hu, A. Muzy, L. Ntaimo. A hybrid agent cellular space modeling approach forre spread and suppression simulation[C] // WSC‘05: Proceedings of the 37th conference on Winter simulation. Winter Simulation Conference, 2005: 248~255.
[113] L. N. Xiaolin Hu. Dynamic multi-resolution cellular space modeling for forest ?re simulation[C] // Proceedings of the DEVS Integrative M&S Symposium (DEVS‘06), Spring Simulation Multiconference, 2006: 95~102.
[114] B. P. Zeigler, R. Jammalamadaka, S. R. Akerkar. Continuity and change (activity) are fundamentally related in DEVS simulation of continuous systems[C]. // AIS, 2004:1~13.
[115] R. Jammalamadaka. Activity characterization of spatial models: Application to the discrete event solution of partial differential equations[D]. Master‘s thesis, University of Arizona, Tucson, Ariz, 2003.
[116] A.Muzy, J. Nutaro, B. Zeigler, P. Coquillard. Modeling and simulation of ?re spreading through the activity tracking paradigm[C]. Ecological Modelling, 2008, 219(1-2): 212 ~225.
[117] M. Emerson, J. Sztipanovits. Techniques for Meta-Model composition[C] // The 6th OOPSLA Workshop on Domain-Speci?c Modeling, OOPSLA 2006. ACM, ACM Press, 2006: 123~139.
[118] R. Lagerstr¨om, M. Chenine, P. Johnson, U. Franke. Probabilistic MetaModel merging[C]. //CAiSE Forum, 2008: 25~28.
[119] Vangheluwe H., de Lara J. Computer Automated Multi-paradigm Modelling for Analysis and Design of Traffic Networks[C]. //Winter Simulation Conference, Washington, 2004.
[120]陈晓波,熊光楞,郭斌,张和明.基于HLA的协同仿真运行研究[J].系统仿真学报, 2003, 15(12):1707~1711.
[121]王江云,王行仁.基于HLA的协同仿真运行管理集成环境[J].北京航空航天大学学报, 2003, 23(3): 273~277.
[122] Braulio Adriano de Mello, Flávio Rech Wagner. A Standardized Co-simulation Backbone[C]. // Eleventh International Conference on Very Large Scale Integration of Systems-on/Chip, 2001:181~192.
[123] L. Gheorghe, F. Bouchhima, G. Nicolescu, H. Boucheneb. A Formalization of global simulation models for Continuous/Discrete systems[C]. // Proceedings of the 2007 summer computer simulation conference. San Diego, CA, USA: Society for Computer Simulation International, 2007:559~566.
[124] B. H. G. L. B. F. Nicolescu, G.. Methodology for efficient Design of Continuous/Discrete-events Co-Simulation tools[C]. // Anderson, J.,Huntsinger, R. (eds.) High Level Simulation Languages and Applications - HLSLA, San Diego, 2007:172~179.
[125] Rajeev Alur, David Dill. The theory of timed automata[C]. // Real-Time: Theory in Practice 1992:45~73.
[126] H. P. Dacharry, N. Giambiasi. A formal verification approach for DEVS[C].// Proceedings of the 2007 summer computer simulation conference. San Diego, CA,USA: Society for Computer Simulation International, 2007:312~319.
[127] L. Gheorghe, F. Bouchhima, G. Nicolescu, H. Boucheneb. Semantics for model-based validation of Continuous/Discrete systems[C]. // DATE‘08: Proceedings of the conference on Design, automation and test in Europe. New York, NY, USA: ACM, 2008: 498~503.
[128]陈伟,薛云志,赵琛,李明树.一种基于时间自动机的实时系统测试方法[J].软件学报,2007,18(1):62~73.
[129]晏荣杰,李广元,徐雨波,刘春明.唐稚松有限精度时间自动机的可达性检测[J].软件学报,2006,17(1):1~10.
[130]梁冰,刘群.基于UPPAAL的数据关联时序有限自动机模型验证[J].计算机工程, 2007, 33(22):6~8.
[131]周清雷,姬莉霞,王艳梅.基于UPPAAL的实时系统模型验证[J].计算机应用, 2004, 24(9):129~131.
[132] G. BEHRMANN. A Tutorial on UPPAAL[Online]. Proc, of SFM-RT‘04,2004, Available: http://ci.nii.ac.jp/naid/10018437108/en/.
[133]陈彬,王全民,龚建兴,黄柯棣.作战模拟态势显示的关键技术研究[J].国防科技大学学报,2009, 31(6):115~120.
[134]张柯,邱晓刚,彭春光,陈彬.分布仿真实验管理系统的设计与实现[J].系统仿真学报, 2008, 20(24): 6627-6630.
[135] Lara Juan, Vangheluwe Hans. AToM3: A Tool for Multi-formalism and Meta-modelling[Z] Fundamental Approaches to Software Engineering, Lecture Notes in Computer Science, 2002.
[136] FAN-LI Zhou, LI-PING Chen, YI-ZHONG Wu, JIAN-WAN Ding, JIAN-JUN Zhao, YUN-QING Zhang.MWorks: a Modern IDE for Modeling and Simulation of Multidomain Physical Systems Based on Modelica[C]. Modelica 2006:725~732.
[137]段伟,彭春光,张柯,邱晓刚,陈彬.分布仿真实验管理系统中实验规划方法研究[J].系统仿真学报, 2008, 20(24):6631~6635.
[138]陈彬,刘宝宏,黄柯棣.组件式仿真系统中基于Web的管理控制方法[J].计算机工程, 2009, 35(24):250~252.
[139] Bin Chen, Qiang He, Rusheng Ju, Kedi Huang. Research on Web-based Real-time Statistical method in combat simulation[C]. //7th International Conference on System Simulation and Scientific Computing, 2008. ICSC 2008. Asia Simulation Conference, 2008:281~286.
[140]陈彬,鞠儒生,蒋召锦,黄柯棣.一种基于Web的作战模拟态势显示方法[J].系统仿真学报, 2009, 21(24):7934~7938.
[141]杨新,王小虎,申功璋,文传源.飞机六自由度模型及仿真研究[J].系统仿真学报,2000, 12(3):210~213.
[142]余修端,孙秀霞,秦硕.全数字通用飞行仿真平台的设计与实现[J].计算机工程, 2008, 34(17):263~265.
[143]梁彦刚,陈磊,唐国金.有限状态机在导弹防御系统中的应用[J].微计算机信息, 2007, 23(7):244~246.
[144]苏伟,罗雪山,张耀鸿.基于StateCharts的C4ISR系统建模方法研究[J].计算机仿真, 2005, 22(9):61~64.
[145]孙吉贵,刘杰,赵连宇.聚类算法研究[J].软件学报, 2008, 19(1):48~61.
[146]段明秀.层次聚类算法的研究及应用[D].长沙:中南大学, 2009.
[147]王全民,张卫华,郭刚,黄柯棣.综合射频环境效应仿真及其在JMASE中的实现[J].计算机仿真, 2006, 23(9):49~52.
[2] M Mitchell Waldrop. Complexity: the emerging science at the edge of order and chaos [M]. New York: Tocuhstone, 1992.
[3]钱学森,于景元,戴汝为.一个科学新领域——开放的复杂巨系统及其方法论[J].自然杂志, 1990, 13(1): 3~10.
[4]王行仁等.我国系统建模与仿真技术的发展-----为纪念中国系统仿真学会成立二十周年而作[J].系统仿真学报, 2009, 21(21): 6683~6688.
[5]黄柯棣,张金槐,查亚兵等.系统仿真技术[M].长沙:国防科技大学出版社,1998.
[6]李伯虎,柴旭东,朱文海等.现代建模与仿真技术发展中的几个焦点[J].系统仿真学报, 2004, 16(9): 1871~1878.
[7] Locke J. An Introduction to the Internet Networking Environment and SIMNET/DIS [R]. Naval Postgraduate School, 1993.
[8] IEEE Standard for Distributed Interactive Simulation Application Protocols. Std.1278.1a-1998 [S]. 1998.
[9] Weatherly R.M., Wilson A.L. and Canova B.S. Advanced Distributed Simulation through the Aggregate Level Simulation Protocol[C]//Wailea, Hawaii. 1996.
[10] IEEE Standard for Modeling and Simulation (M&S) High Level Architecture Object Model Template Specification [S]. IEEE Std 1516.2-2000, Sep. 2000.
[11] U.S. Department of Defense , Modeling and Simulation Master Plan, http://www.dmso.mil, 1995-10/2010-08.
[12] U.S. Defense Modeling and Simulation Office. Conceptual Models of the Mission Space (CMMS) Technical Framework. Feb 1997.
[13]胡晓峰,罗批,司光亚等.战争复杂系统建模与仿真[M].北京:国防大学出版社, 2005.
[14] Andreas Idebrant, Peter Fritzson, Martin Hagstr?m. AirCraft– A Modelica Library for Aircraft Dynamics Simulation[C]. //5th EuroSim Congress on Modeling and Simulation, Paris, 2004.
[15] Bernard P. Zeigler, Herbert Praehofer, Tag Gon King. Theory of Modeling and Simulation, 2nd Edition[M]. London: Acdemaic Press, 2000.
[16] Hans Vangheluwe, Juan de Lara, P. J. Mosterman. AN INTRODUCTION TO MULTI-PARADIGM MODELLING AND SIMULATION[C],//AI, Simulation and Planning in High Autonomy Systems, AIS‘2002', 2002:9~20.
[17] Holland J. Adaptation in Natural and Artificial Systems [M]. Cambridge, MA, USA: MIT Press, 1992.
[18] Joel L.Schff. Cellular Automata: A Discrete View of the World [M]. New York:JOHN WILEY & SONS, 2007.
[19] Kennedy J., Eberhart R. Particle Swarm Optimization[C]. //Proceedings of IEEE International Conference on Neural Networks. IV.2005:1942~1948.
[20]张明智,胡晓峰,司光亚,赵占龙.基于Agent的体系对抗仿真建模方法研究[J].系统仿真学报, 2005, 17(11): 2785~2792.
[21]钱学森,于景元,戴汝为.一个科学新领域——开放的复杂巨系统及其方法论[J].自然杂志, 1990, 13(1): 3~10.
[22]戴汝为.从定性到定量的综合集成技术[J].模式识别与人工智能,1991, 4 (1): 5~10.
[23]于景元,涂元季.从定性到定量综合集成方法一案例研究[J].系统工程理论与实践,2002, 22 (5):1~7.
[24] Davis P K, Bigelow J. Introduction to Multi-Resolution Model (MRM) with an Example Involving Precision Fires [C].// Enabling technology for Simulation Science (II), Proceeding of SPIE AeoroSense. 1998.
[25] Biddle M. A Proposed Scheme for Implementing Aggregation and Disaggregation in HLA [C].// Processing of 2000 Fall SIW. 2000.
[26]毛媛,刘杰,李伯虎.基于元模型的复杂系统建模方法研究[J].系统仿真学报, 2002, 14(4): 411~414, 454.
[27] OMG, Meta Object Facility (MOF) Specification Version 1.3[S], 2000.
[28]王飞跃.关于复杂系统的建模、分析、控制和管理[J].复杂系统与复杂性科学, 2006, 3(2): 26~34.
[29]刘晓平,唐益明,郑利平.复杂系统与复杂系统仿真研究综述[J].系统仿真学报, 2008, 20(23): 6303~6315.
[30] Balci, O.. The implementation of four conceptual frameworks for simulation modeling in high-level languages[C]. // Proceedings of the Winter Simulation Conference, San Diedo: Society for Computer Simulation International (SCS), 1988:287~295.
[31]黄柯棣.对建模与仿真技术学科的粗浅理解——为庆祝《计算机仿真》杂志创刊20周年而写[J].计算机仿真, 2004, 21(9):F010~F013.
[32]军用仿真术语标准研究课题组.军用建模与仿真通用术语汇编[M].北京:国防工业出版社, 2004.
[33] Balci, O. Principles of simulation model validation, verification, and testing[J]. Transactions of the Society for Computer Simulation International, 1997, 14(1):3~12. Special Issue: Principles of Simulation.
[34] Magee, B. Popper[M]. London: Fontana Press (An Imprint of HarperCollins Publishers), 1985.
[35] Wymore., A. W., A Mathematical Theory of Systems Engineering– the Elements[M]. Wiley series on systems engineering and analysis. New York: Wiley, 1967.
[36] Zeigler, B. P.. Multifacetted Modelling and Discrete Event Simulation[M]. Academic Press, London, 1984.
[37] Engstrom E., & Krueger J.. A Meta-Modeler's Job is Never Done: Building and Evolving Domain-Specific Tools With DOME[C]. // IEEE International Symposium on Computer Aided Control System Design, 2000:83~88.
[38] Nordstrom G., Sztipanovits J., Karsai, G., Ledeczi, A.. Metamodeling-rapid design and evolution of domain-specific modeling environments[C] // Engineering of Computer-Based Systems, 1999. Proceedings. 1999: 68~74.
[39] Czarnecki K., & Helsen S.. Classification of Model Transformation Approaches[C]. // OOPSLA‘03 Workshop on Generative Techniques in the Context of Model-Driven Architecture, 2003.
[40]王学斌,吴泉源,史殿习.模型驱动架构中的模型转换方法[J].计算机工程与科学, 2006, 28(11): 133~135.
[41]鹿旭东,万建成.元模型支持下的模型转换[J].计算机工程与应用, 2005, 41:72~75.
[42] Dorr, H. Ef?cient graph rewriting and its implementation[M]. New York: Springer-Verlag, 1995.
[43] Olegas Vasilecas, D. B., APPLYING THE META-MODEL BASED APPROACH TO THE TRANSFORMATION OF ONTOLOGY AXIOMS INTO RULE MODEL[J]. INFORMATION TECHNOLOGY AND CONTROL, 2007, 36(1A): 122~125.
[44] Booth, Taylor L. Sequential Machines and Automata Theory (1st ed.)[M]. New York: John Wiley and Sons, 1967.
[45] Ashvin Radiya, Robert G. Sargent. A logic-based foundation of discrete event modeling and simulation[J]. ACM Transactions on Modeling and Computer Simulation, 1994, 1(1):3–51.
[46] Ki Hyung Kim, Yeong Rak Seong, Tag Gon Kim, Kyu Ho Park. Distributed simulation of hierarchical DEVS models: Hierarchical scheduling locally and time warp globally[J]. Transactions of the Society for Computer Simulation International, 1996, 13(3):135–154.
[47] Vangheluwe H.. DEVS as a common denominator for Multi-Formalism hybrid systems modeling[C].// IEEE International Symposium on Computer Aided Control System Design. Anchorage, Alaska, 2000:129~134.
[48] Bekey G. A., Kogan B. Y.(eds). Modeling and Simulation: Theory and Practice [M]. Norwell: Springer, 2003.
[49] Ernesto Kofman, J.S. Lee, B. Z., DEVS Representation of Differential Equation Systems: Review of Recent Advances[C]. // Proc of DEVS Workshop, European Simulation Conference. Prague, 2001:591~595.
[50]卢绍文.重叠交替更新过程的DTSS仿真校验的两个问题[J].自动化学报, 2009, 35(5):636~640.
[51] Moore, E. F.. Gedanken-experiments on Sequential Machines. AutomataStudies[J]. Annals of Mathematical Studies, 1956, 34:129~153.
[52]刘秀罗,黄柯棣,朱小俊.有限状态机在CGF行为建模中的应用[J].系统仿真学报, 2001, 13(5):663~665.
[53] Harel, D.. Statecharts: A Visual Formalism for Complex Systems[J]. Science of Computer Programming, 1987, 8(3):231~274.
[54]朱雪阳,唐稚松. Statecharts的组合语义与求精[J].软件学报, 2006, 17(4): 670~681.
[55]钱俊彦,赵岭忠.基于LTS的Statecharts操作语义研究[J].计算机工程, 2006, 32(22):43~45.
[56] Harel, D., Naamad, A. The STATEMATE semantics of statecharts[J]. ACM Trans. Softw. Eng. Methodol, 5(4), 293~333.
[57] S. Schulz, T.C. Ewing, J.W. Rozenblit. Discrete EVent System speci?cation (DEVS) and Statemate Statecharts equivalence for embedded systems modeling[C]. // 7th IEEE International Conference and Workshop on the Engineering of Computer Based Systems, Edinburgh: IEEE Computer Society, 2000.
[58]刘晨,王维平,朱一凡.状态机嵌入DEVS的组合建模方法研究[J].国防科技大学学报, 2005, 27(5):56~61.
[59] Spencer Borland, Hans Vangheluwe. Transforming statecharts to DEVS[C]. // Summer Computer Simulation Conference (Student Workshop), Montreal: Society for Computer Simulation International (SCS), 2003:154~159.
[60] SISO-STD-003-2006, Base Object Model (BOM) Template Specification[S]. SISO, 2006.
[61] J. Gong, C. Han, X. Qiu, and K. Huang. Constructing the Extensible HLA Federate Architecture[J]. Journal of System Simulation, 2006, 18(11):3126~3130.
[62] J. Gong and K. Huang. Research on HLA Composible Simulation Framework Based on BOM[C]. // Proceedings of the 7th International Conference on System Simulation and Scientific Computing, 2006: 59~60.
[63] IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA) - Frame and Rules[S]. Simulation Interoperability Standards Organization, 2000.
[64] IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA)- Federate Interface Specification[S]. Simulation Interoperability Standards Organization, 2000.
[65] Opdyke WF. Refactoring object-oriented frameworks [D]. Urbana-Champaign: University of Illinois, 1992.
[66] P. Gustavson, T. Chase. Using XML and BOMs to Rapidly Compose Simulation and Simulation Environment[C]. //Proceedings of the 2004 Winter Simulation Conference, Washington , 2004:1467~1475.
[67]龚建兴.基于BOM的可扩展仿真系统框架研究[D].长沙:国防科技大学,2007.
[68] Chow, A. C.-H.. Parallel DEVS: A parallel, hierarchical, modular modeling formalism and its distributed simulation[J]. Transactions of the Society for Computer Simulation International, 1996, 13 (2):55~67.
[69] B. Azzedine, M. Zhang, S. Ahmad. DEVS Approach to Real-Time RTI Design For Large-Scale Distributed Simulation Systems[J]. Simulation, 2008, 84(5):231~238.
[70] Alex Chun Hen Chow, Bernard P. Zeigler. Parallel DEVS: A parallel, hierarchical, modular, Modeling Formalism[C]. // Proceedings of 26th conference on Winter Simulation, San Diego: Society for Computer Simulation International, 1994:716~722.
[71] Z. Ming. An introduction to DEVS and Distributed DEVS[C]. //SpringSim‘08: Proceedings of the 2008 Spring simulation multiconference, San Diego: Society for Computer Simulation International, 2008: 351~351.
[72] G. F. Riley, R. Fujimoto, M. H. Ammar. Network aware Time Management and Event Distribution[C]. //Proc. of the 14th Workshop on Parallel and Distributed Simulation, Washingdon, DC: IEEE Computer Society, 2000.
[73] M. Zhang, B. Zeigler, P. Hammonds. DEVS/RMI-an Auto-Adaptive and Recon?gurable Distributed Simulation Environment for Engineering Studies[J]. Journal of Test and Evaluation, 2006, 27(1):49~60.
[74] S. Cheon, C. Seo, and B. P. Zeigler. Sunwoo Park. Design and Implementation of Distributed DEVS simulation in a Peer to Peer Network System[C]. //2004 Military, Government, and Aerospace Simulation, 2004.
[75] C. Seo, S. Park, B. Kim, S. Cheon, B. P. Zeigler. Implementation of Distributed High-performance DEVS Simulation Framework in the Grid Computing Environment[C]. // 2004 High Performance Computing Symposium, 2004.
[76] Himmelspach, J., A. M. Uhrmacher. Sequetial processing of pdevs models[C]. // 3rd European Modeling and Simulation, Barcelona, 2006:239~244.
[77] Himmelspach, J., R. Ewald, S. Leye, A. M. Uhrmacher. Parallel and distributed simulation of parallel DEVS models[C]. // SpringSim‘07: Proceedings of the 2007 spring simulation multiconference, San Diego: Society for Computer Simulation International, 2007:249~256.
[78] S. Cheon, C. Seo, B. P. Z., Sunwoo Park. Design and implementation of distributed devs simulation in a peer to peer network system[C]. // Military, Government, and Aerospace Simulation, 2004.
[79] H. Shang, G. A. Wainer. Dynamic structure DEVS: Improving the real-time embedded systems simulation and design[C]. // Annual Simulation Symposium, Ottawa: IEEE Computer Society, 2008:271~278.
[80] A. Muzy, J. Nutaro. Algorithms for ef?cient implementations of the DEVS & DSDEVS abstract simulators[C]. // 1st Open International Conference on Modeling & Simulation, 2005:273~279.
[81] P. Fritzson, P. Bunus. Modelica, A General Object-Oriented Language forContinuous and Discrete-Event System Modeling and Simulation[C]. // In Proceedings of the 35th Annual Simulation Symposium, 2002:14~18.
[82] H. Song. Infrastructure for devs modelling and experimentation[D]. Master Thesis in McGill University, Montreal, Canada, 2006.
[83] Hans L.M. Vangheluwe. DEVS as a Common Denominator for Multi-formalism Hybrid Systems Modeling[C]. // Proceedings of the 2000 IEEE International Symposium on Computer-Aided Control Shstem Design, Anchorage, 2007.
[84] Kofman, E., Lee, J., and Zeigler, B. DEVS Representation of Di?erential Equation Systems. Review of Recent Advances[C]. In Proceedings of ESS‘01, 2001.
[85] D‘Abreu M.C., Wainer G.A.. M/CD++: modeling continuous systems using Modelica and DEVS[C]. // 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, 2005:229~236.
[86] Mariana C. D‘abreu, Gabriel A. Wainer. Experimental results on the implementation of Modelica using DEVS modeling and simulation[C]. SIMULATION SERIES, 2006.
[87]吴义忠,蒋占四,陈立平.基于Modelica语言的多领域模型仿真优化研究[J].系统仿真学报, 2009, 21(12):2612~2615.
[88]赵建军,丁建完,周凡利,陈立平. Modelica语言及其多领域统一建模与仿真机理[J].系统仿真学报, 2006, 18(z2):570~573.
[89] Xu, W.. The Design and Implementation of theμModelica Compiler[D]. Montreal, Master's thesis. McGill University. School of Computer Science, 2005.
[90] Modelica– A Unified Object-Oriented Language for Physical Systems Modeling Language Specification[S]. Modelica Association, 2000.
[91] M. H. Hwang. DEVS++:C++ Open Source Library of DEVS Formalism. http://odevspp.sourceforge.net/, first edition, 2007.
[92] Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides. Design Patterns[M]. Reading, Massachusetts: Addison-Wesley Professional, 1995.
[93] Fujimoto, R. M. Parallel and distributed Simulation Systems[C]. // Proceedings of the Winter Simulation Conference, Arlington, 2001:147~157.
[94] Zeigler B, Cho H, Lee J., Sarjoughian H.. The DEVS/HLA Distributed Simulation Environment And Its Support for Predictive Filtering[R]. Tunson, AZ, ECE Department, University of Arizona, 1998.
[95] M. Zhang, B. P. Zeigler, P. Hammonds. DEVS/RMI-An Auto-Adaptive and Reconfigurable Distributed Simulation Environment for Engineering Studies[J]. ITEA Journal, 2005.
[96] C. Seo, S. Park, B. Kim, S. Cheon, B. P. Zeigler. Implementation of Distributed High-performance DEVS Simulation Framework in the Grid Computing Environment[C]. // Advanced Simulation Technologies conference (ASTC), Arlington, 2004.
[97] S. Mittal, J. L. Risco. DEVSML: Automating DEVS Execution over SOATowards Transparent Simulators[C]. // Special Session on DEVS Collaborative Execution and Systems Modeling over SOA, DEVS Integrative M&S Symposium, 2007.
[98]都志辉.高性能计算之并行编程技术——MPI并行程序设计[M].北京:清华大学出版社, 2001.
[99] Foster Ian. Designing and Building Parrallel Programs: Concepts and Tools for Parallel Software Engineering[M]. Reading, MA: Addison-Wesley, 1995.
[100] Jefferson D. Virtual Time[J]. ACM Transactions on Programming Languages and Systems, 7(3): 404~425.
[101]王学慧.并行与分布式仿真系统中的时间管理技术研究[D].长沙:国防科学技术大学, 2006.
[102] Richard M. Fujimoto. Parallel and Distributed Simulation Systems[M]. New York: Wiley, 2000.
[103] O.P. Damani, V.K. Garg. Fault-Tolerant Distributed Simulation[C]. // Parallel and Distributed Simulation, Workshop on Parallel and Distributed Simulation, Los Alamitos, 1998:3~8.
[104] Aguilar Jose, Hern′andez Marisela. Fault Tolerance Protocols for Parallel Programs Based on Tasks Replication[C]. MASCOTS‘00: Proceedings of the 8th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Washington. DC, 2000:397~404.
[105] Dan Chen, Stephen J. Turner, Wentong Cai. Towards Fault-tolerant HLA-based Distributed Simulations[J]. SIMULATION, 84(10-11):493~509.
[106] Min M., Shiyao J., Chaoqun Y., Xiaojian L.. Dynamic Fault Tolerance in Distributed Simulation System[C]. //Proc. International Conference on Computational Science (1), Reading, UK, 2006:769~776.
[107] S. Balsamo, A. Di Marco, P. Inverardi, M. Simeoni. Model-based performance prediction in software development: A survey[J]. IEEE Trans. Softw. Eng., 2004, 30(5):295~310.
[108] D. C. Petriu, H. Shen. Applying the UML performance pro?le: Graph grammar-based derivation of LQN models from UML speci?cations. SpringerVerlag, 2002:159~177.
[109] Chanda Ghose Dasguptaa, Gary S. Dispensab, Sanjoy Ghose. Comparing the predictive performance of a neural network model with some traditional market response models[J]. International Journal of Forecasting, 1994, 10(2):235~244.
[110] A. Muzy, B. Zeigler. Introduction to the activity tracking paradigm in component-based simulation[J]. The Open Cybernetics and Systemics Journal, 2008, 2:48~56.
[111] X. H., Lewis Ntaimo. DEVS-FIRE: Towards an integrated simulation environment for surface wild?re spread and containment[J]. SIMULATION, 2008, 84(4): 137~155.
[112] X. Hu, A. Muzy, L. Ntaimo. A hybrid agent cellular space modeling approach forre spread and suppression simulation[C] // WSC‘05: Proceedings of the 37th conference on Winter simulation. Winter Simulation Conference, 2005: 248~255.
[113] L. N. Xiaolin Hu. Dynamic multi-resolution cellular space modeling for forest ?re simulation[C] // Proceedings of the DEVS Integrative M&S Symposium (DEVS‘06), Spring Simulation Multiconference, 2006: 95~102.
[114] B. P. Zeigler, R. Jammalamadaka, S. R. Akerkar. Continuity and change (activity) are fundamentally related in DEVS simulation of continuous systems[C]. // AIS, 2004:1~13.
[115] R. Jammalamadaka. Activity characterization of spatial models: Application to the discrete event solution of partial differential equations[D]. Master‘s thesis, University of Arizona, Tucson, Ariz, 2003.
[116] A.Muzy, J. Nutaro, B. Zeigler, P. Coquillard. Modeling and simulation of ?re spreading through the activity tracking paradigm[C]. Ecological Modelling, 2008, 219(1-2): 212 ~225.
[117] M. Emerson, J. Sztipanovits. Techniques for Meta-Model composition[C] // The 6th OOPSLA Workshop on Domain-Speci?c Modeling, OOPSLA 2006. ACM, ACM Press, 2006: 123~139.
[118] R. Lagerstr¨om, M. Chenine, P. Johnson, U. Franke. Probabilistic MetaModel merging[C]. //CAiSE Forum, 2008: 25~28.
[119] Vangheluwe H., de Lara J. Computer Automated Multi-paradigm Modelling for Analysis and Design of Traffic Networks[C]. //Winter Simulation Conference, Washington, 2004.
[120]陈晓波,熊光楞,郭斌,张和明.基于HLA的协同仿真运行研究[J].系统仿真学报, 2003, 15(12):1707~1711.
[121]王江云,王行仁.基于HLA的协同仿真运行管理集成环境[J].北京航空航天大学学报, 2003, 23(3): 273~277.
[122] Braulio Adriano de Mello, Flávio Rech Wagner. A Standardized Co-simulation Backbone[C]. // Eleventh International Conference on Very Large Scale Integration of Systems-on/Chip, 2001:181~192.
[123] L. Gheorghe, F. Bouchhima, G. Nicolescu, H. Boucheneb. A Formalization of global simulation models for Continuous/Discrete systems[C]. // Proceedings of the 2007 summer computer simulation conference. San Diego, CA, USA: Society for Computer Simulation International, 2007:559~566.
[124] B. H. G. L. B. F. Nicolescu, G.. Methodology for efficient Design of Continuous/Discrete-events Co-Simulation tools[C]. // Anderson, J.,Huntsinger, R. (eds.) High Level Simulation Languages and Applications - HLSLA, San Diego, 2007:172~179.
[125] Rajeev Alur, David Dill. The theory of timed automata[C]. // Real-Time: Theory in Practice 1992:45~73.
[126] H. P. Dacharry, N. Giambiasi. A formal verification approach for DEVS[C].// Proceedings of the 2007 summer computer simulation conference. San Diego, CA,USA: Society for Computer Simulation International, 2007:312~319.
[127] L. Gheorghe, F. Bouchhima, G. Nicolescu, H. Boucheneb. Semantics for model-based validation of Continuous/Discrete systems[C]. // DATE‘08: Proceedings of the conference on Design, automation and test in Europe. New York, NY, USA: ACM, 2008: 498~503.
[128]陈伟,薛云志,赵琛,李明树.一种基于时间自动机的实时系统测试方法[J].软件学报,2007,18(1):62~73.
[129]晏荣杰,李广元,徐雨波,刘春明.唐稚松有限精度时间自动机的可达性检测[J].软件学报,2006,17(1):1~10.
[130]梁冰,刘群.基于UPPAAL的数据关联时序有限自动机模型验证[J].计算机工程, 2007, 33(22):6~8.
[131]周清雷,姬莉霞,王艳梅.基于UPPAAL的实时系统模型验证[J].计算机应用, 2004, 24(9):129~131.
[132] G. BEHRMANN. A Tutorial on UPPAAL[Online]. Proc, of SFM-RT‘04,2004, Available: http://ci.nii.ac.jp/naid/10018437108/en/.
[133]陈彬,王全民,龚建兴,黄柯棣.作战模拟态势显示的关键技术研究[J].国防科技大学学报,2009, 31(6):115~120.
[134]张柯,邱晓刚,彭春光,陈彬.分布仿真实验管理系统的设计与实现[J].系统仿真学报, 2008, 20(24): 6627-6630.
[135] Lara Juan, Vangheluwe Hans. AToM3: A Tool for Multi-formalism and Meta-modelling[Z] Fundamental Approaches to Software Engineering, Lecture Notes in Computer Science, 2002.
[136] FAN-LI Zhou, LI-PING Chen, YI-ZHONG Wu, JIAN-WAN Ding, JIAN-JUN Zhao, YUN-QING Zhang.MWorks: a Modern IDE for Modeling and Simulation of Multidomain Physical Systems Based on Modelica[C]. Modelica 2006:725~732.
[137]段伟,彭春光,张柯,邱晓刚,陈彬.分布仿真实验管理系统中实验规划方法研究[J].系统仿真学报, 2008, 20(24):6631~6635.
[138]陈彬,刘宝宏,黄柯棣.组件式仿真系统中基于Web的管理控制方法[J].计算机工程, 2009, 35(24):250~252.
[139] Bin Chen, Qiang He, Rusheng Ju, Kedi Huang. Research on Web-based Real-time Statistical method in combat simulation[C]. //7th International Conference on System Simulation and Scientific Computing, 2008. ICSC 2008. Asia Simulation Conference, 2008:281~286.
[140]陈彬,鞠儒生,蒋召锦,黄柯棣.一种基于Web的作战模拟态势显示方法[J].系统仿真学报, 2009, 21(24):7934~7938.
[141]杨新,王小虎,申功璋,文传源.飞机六自由度模型及仿真研究[J].系统仿真学报,2000, 12(3):210~213.
[142]余修端,孙秀霞,秦硕.全数字通用飞行仿真平台的设计与实现[J].计算机工程, 2008, 34(17):263~265.
[143]梁彦刚,陈磊,唐国金.有限状态机在导弹防御系统中的应用[J].微计算机信息, 2007, 23(7):244~246.
[144]苏伟,罗雪山,张耀鸿.基于StateCharts的C4ISR系统建模方法研究[J].计算机仿真, 2005, 22(9):61~64.
[145]孙吉贵,刘杰,赵连宇.聚类算法研究[J].软件学报, 2008, 19(1):48~61.
[146]段明秀.层次聚类算法的研究及应用[D].长沙:中南大学, 2009.
[147]王全民,张卫华,郭刚,黄柯棣.综合射频环境效应仿真及其在JMASE中的实现[J].计算机仿真, 2006, 23(9):49~52.