用户名: 密码: 验证码:
基于语义交互和动态重构的兵棋推演系统概念框架及其关键技术研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
兵棋(Wargame)是现代战争模拟的重要起源,是一种利用模拟手段进行战争分析的方法。兵棋推演(Wargaming)强调“以推演人员为中心”,通过对战争进程的推演,研究战争的动态演化过程以及不确定性和偶然性对战争结果的影响,因此具有其他战争模拟方法所不能替代的作用。由于历史原因,我国一直忽略对兵棋这一战争分析工具的研究。近年来,计算机兵棋推演正逐渐成为国内研究的热点。适于作战分析的兵棋推演方式,如何与新的信息化系统相结合是目前计算机作战模拟所要研究和解决的问题。论文以此为背景,对如何构建计算机兵棋推演系统涉及到的几个关键技术问题进行了研究,其目的是将兵棋推演的思想与建模与仿真(Modeling and Simulation,M&S)、计算机网络、并行计算等现代信息技术相结合,建立能够适用于现代战争模拟的计算机兵棋推演系统。本文的主要研究内容如下:
     一.研究了兵棋推演系统的概念框架。
     论文从兵棋的发展历史、概念描述和博弈论的角度,剖析了兵棋推演的本质。在此基础上,分析了兵棋推演系统的功能需求,建立了具有四层结构的系统概念框架,并详细分析了每层结构的功能特点和涉及到的关键技术。在具体应用过程中,该框架将对建立基于语义交互和动态重构的兵棋推演系统起到重要的指导作用。
     二.论文将本体技术应用于解决兵棋推演中的人机语义交互问题,提出了基于本体的人机语义交互方法。
     在计算机兵棋推演系统中,如何让推演人员与仿真系统“自然地”交互,从而发挥各自的优势进行功能与过程的分工是一个关键问题。论文将兵棋推演中的人机交互问题,抽象为推演人员所在的军事领域和仿真开发人员所在的仿真领域之间的信息交互问题。首先建立领域本体描述领域概念,在系统构建和运行过程中,采用本体映射解决领域间信息交互的语义异构问题,同时利用本体的逻辑推理机制,对交互模型进行领域有效性验证,以解决交互过程中的概念冲突、知识冗余和数据不一致等问题。
     三.针对在线推演的需求,论文提出了面向模型的组件式兵棋推演系统动态重构机制。
     实现在线推演的关键,是能够根据决策需求快速的构建/重构仿真系统,即仿真系统的动态重构技术。论文根据进化模式动态重构的思想,结合BOM(Base Object Model)组件式仿真系统的特点,提出了基于BOM组件的可重构兵棋推演系统的动态重构机制,以满足在线推演过程中系统动态重构的需求。四.对模型组件进行快速有效地装配是仿真系统重构的关键技术之一,针对这一需求,论文提出了一种基于BOM的仿真模型组件装配方法。
     论文通过对仿真模型组件结构的分析,将组件装配过程分成两个阶段:一是仿真模型组件描述信息的装配,采用白盒组装方法,该方法要求仿真模型组件提供描述组件自身信息的模型规范文件,把这些模型描述文件装配成整个仿真系统的成员配置文件,该文件描述了仿真系统的组成成分及仿真系统的仿真功能;二是仿真模型组件执行体的装配,采用黑盒组装方法,该方法通过仿真引擎自动加载仿真模型组件的执行体,在运行过程中动态构建仿真系统。
     五.针对仿真系统重构过程中模型组件的优化配置问题,论文提出了一种基于BOM的组件式仿真系统的重构规划方法。
     论文依据并行分布计算中的多任务调度理论,结合BOM组件式仿真系统的特点,将系统重构规划分为运行前的预分配和运行时的动态调度两个方面。预分配是一种静态调度,是在满足一定的性能指标和优先约束关系的前提下,将可并行执行的BOM组件按适当的分配策略确定一种组合、分派和执行顺序,合理分配到各计算节点上有序地执行;动态调度方法考虑了系统运行时的负载波动问题,可适时获取各节点的负载信息,通过计算将过载节点上的BOM组件和仿真任务转移到轻载节点上,以实现系统的负载均衡。在实际问题中,只有将两种方法结合起来才能完成对仿真系统的最终优化。
     六.结合上述理论研究成果,设计并实现了兵棋推演管理系统。
     该系统集成了上述研究中的相关方法,为建立基于语义交互和动态重构的兵棋推演系统提供工具支撑,基于此系统可以完成对兵棋推演系统的构建、资源调度和运行管理;最后通过一个海上作战计划推演原型系统演示了如何将兵棋推演技术应用于海军作战计划的辅助制定和作战战法的论证优化,验证了本文提出的相关方法。
Wargame, as an important origin of warfare simulation, is one method of war analysis using simulation. Wargaming focuses on wargame players, by which, we can make an investigation on the dynamic process of the war and the effect of unsureness and random in the war. So wargaming can’t be replaced by other simulation methods. For some historical reasons, Chinese military have never studied on wargames. However, computer wargames have been noticed recently in China. One of the problems in the computer warfare simulation is how to integrate the analysis method of wargaming with new information systems. In this context, the paper studied on the key technologies in computer wargames, which aims for combining the nature of wargaming with modern information technologies, such as Modeling and Simulation, computer network, parallel computation and so on, and constructing computer wargames which can be used in modern warfare simulaions. The main contents of this paper are outlined as follows:
     1. The conceptual framework of wargames is studied.
     The nature of wargaming is analysized from the point of its history, concept and Game Theory. On this base, we make an investigation on the system requirement and establish the conceptual framework of wargames, which is a four-layered architecture. Then we illuminate functions provided by each layer, and identify key technologies needed to be solved in the framework. In the practice, the framework will instruct to develop wargames based on semantic interactions and dynamic reconfiguration technologies.
     2. An ontology based human-computer semantic interaction approach is proposed, in which ontology technologies are used to resolve the problem of human-computer interaction in wargames.
     In computer wargames, the key problem is that how players can interact with simulation systems“naturally”and how to assign works between them according to their advantages. The paper considers human-computer interactions in wargames as information interactons between different domains, i.e. the military domain (wargaming players) and the simulation domain (simulation developers). The first is to construct domain ontologies to describe domain concepts. In the process of system construction and running, ontology mappings can be used to resolve the heteronymous semantic problems, and ontology logic and consequence mechanisms can be used to validate interaction models between different domains. The validation problems consist of concept contradiction, knowledge redundancy, data inconsistency and so on.
     3. According to the online-wargaming requirement, the dynamic reconfiguration mechanism of model-oriented composable wargames is studied.
     The key point of online-wargaming is how to construct and reconfigurate simulation systems quickly in terms of the simulation requirement, i.e. the dynamic reconfiguration technologies. According to the evolution dynamic reconfiguration theory and characteristics of BOM(Base Object Model)-based composable systems, we propose the architecture of BOM-based and reconfigurable wargames, which can be reconfigured in the process of online-wargaming.
     4. The component assembly technology is one of the key technologies about the construction/reconfiguration of simulation systems, so we make an investigation how to compose BOM-based simulation model components.
     By analyzing the structure of the components, we divide the composition process into two steps. One is to compose BOM description files using White Box Composition method. Components need provide their BOM files describing themselves, and then all files should be composed into the federate configure file of the simulation system, which describes the structure and capability of the simulation system. The other is to compose the BOM executors using Black Box Composition method. The simulation engine load component executors automatically and construct the simulation system dynamically in the running process.
     5. In order to configurate model componets more effectively, a reconfiguration layout approach in BOM-based composable wargames is proposed.
     According to the scheduling theory in the parallel and distributed computation, and characteristics of BOM-based simulation systems, we divide the approach into two steps: pre-assignation and dynamic scheduling. The pre-assignation is static, which aims for choosing the optimized scheduling method (including composition, assignation and execution) and assigning BOM components to computational nodes based on some performance targets and preference constrains. The dynamic scheduling considers the load fluctuation in the running, gets the load information of each computational node, and transfers BOM components and simulation tasks from heavy nodes to light nodes to realize the load balance. In practise, we should combine the two steps to optimize the simulation system.
     6. Based on the methods above, we design and realize the Wargaming Management System (WMS).
     WMS integrates methods above and supports to construct computer wargames based on semantic interaction and dynamic reconfiguration. Using WMS, we can build wargames, assign resources and manage the running process. At last, a sea warfare wargame prototype is developed to validate methods in the paper, which illustrates how to make and optimize naval plans by wargaming.
引文
[1]黄柯棣,张金槐,李剑川等.系统仿真技术[M].长沙:国防科技大学出版社, 1998:7-10.
    [2]陈宗海.系统仿真技术及其应用第11卷卷首语[C].合肥:中国科学技术大学出版社, 2009.
    [3]杨南征.虚拟演兵:兵棋、作战模拟与仿真[M].北京:解放军出版社,2007:18-63.
    [4]彭春光,赵鑫业,刘宝宏等.兵棋推演技术综述[C].合肥:系统仿真技术及其应用第11卷, 2009:366-270.
    [5]刘勇奎.计算机图形学的基础算法[M].北京:科学出版社.2007.1: 164-165.
    [6] Condat L, Van D V, Blu T. Hexagonal versus Orthogonal Lattices: A New Comparison Using Approximation Theory [C], Proceedings of the IEEE International Image Processing, Italy: IEEE, 2005.9: 1116-1119.
    [7] Perla P. The Art of Wargaming[M]. U.S.Naval Institute Press. 1990:163-170.
    [8]徐学文,王寿云.现代作战模拟[M].北京:科学出版社, 2001:341-342.
    [9]罗云峰.博弈论教程[M].北京:清华出版社,2007:107-108.
    [10]彭春光,鞠儒生,杨建池等.现代兵棋推演技术分析[J].北京:系统仿真学报, 2009.21(suppl.2):97-100.
    [11]李加祥.编队综合集成作战指挥系统及在搜索潜艇中应用的研究[D].大连理工大学, 2004.10:23-24.
    [12]沈伟光.新战争论[M].浙江:浙江大学出版社. 2000.10: 304-306.
    [13]胡晓峰,杨镜宇,司光亚等.战争复杂系统仿真分析与实验[M].北京:国防大学出版社. 2008.6: 122, 356-358.
    [14] Liu Jihong, Xu Xiaodong, Xu Xinhe, Study on Human-Computer Interaction Platform for Computer Wargame[C], Proceedings of Chinese Control and Decision Conference, Chinese: IEEE, 2008.8: 2233-2238.
    [15]杨伦,彭春光,黄健等.兵棋推演中地形量化算法研究与实现[J].北京:计算机仿真. 2008,9(9): 96-99.
    [16] U.S. Joint Forces Command Joint Warfighting Center, JTLS Executive Overview[R]. USA: ROLAND&ASSOCIATES Corporation, 2007. 2-14.
    [17] Ross D. Designing a system on system wargame[R], U.S.Air Force Research Lab, 2006.6: 149-153.
    [18] Paul Bello. Theoretical Foundations for Rational Agency in Third Generation Wargames[R], U.S.Air Force Research Lab, 2006.6:169-178.
    [19] William S, Barry W. Analytic War Plans: Adaptive Force-Employment Logic in the RAND Strategy Assement System (RSAS)[R]. AD-A236 958, 1990.6:1-13.
    [20] Peng C G, Liu B H, Huang K D. The Study of Wargames based on HLA[C], Proceedings of 2008 Asia Simulation Conference. Beijing: IEEE, 2008.11: 649-653.
    [21] Scott A. Carey, Martin S. Kleiner, Michael R. Hieb, etc. Standardizing Battle Management Language - A Vital Move Towards the Army Transformation[C]. Proceedings of the 2001 Fall Simulation Interoperability Workshop, 01F-SIW-067. 2001.
    [22] Andreas Tolk, Major Kevin Galvin, Michael Hieb, etc. Coalition Battle Management Language [C]. Proceedings of the 2004 Fall Simulation Interoperability Workshop. 04F-SIW-103. USA.2004.
    [23] Ulrich Schade, Michael R. Hieb. Formalizing Battle Management Language: A Grammar for Specifying Orders[C]. Proceedings of the 2006 Spring Simulation Interoperability Workshop. 06S-SIW-068. USA. 2006.
    [24] Saikou Diallo, Andreas Tolk, Chuck Turnitsa. Merging Protocols, Grammar, Representation, and Ontological Approaches in Support of C-Bml[C]. Proceedings of the 2006 Fall Simulation Interoperability Workshop.06F-SIW-008. 2006.
    [25]陈小平.人机语义研究:人工智能观点[J].浙江大学学报(人文社会科学版),2006.26(3):13-20.
    [26] Berner Lee T. Semantic web road map.[EB/OL] W3C Design Issues. http://www.w3.org/DesignIssues/Semantic. 1998.
    [27] Berner Lee T. Publishing on the semantic web-The coming Intenet revolution will profoundly affect scientific information[J]. NATURE, 2001:1023-1024.
    [28]韩守鹏,分布式仿真系统动态重构技术研究[D],国防科技大学,博士论文,2008.10:2-3.
    [29] Canahan J., Reynolds P. and Brogan D. Visualizing coercible simulations[C]. Proceedings of the Winter Simulation Conference. 2004: 411-419.
    [30] Brogan D., Reynolds P., Bartholet R etc. Semi-Automated Simulation Transformation for DDDAS[C]. Proceedings of the 5th International Conference on Computational Science. 2005: 721-772.
    [31] Carnahan J. and Reynolds P. An Experiment in Simulation Coercion[C]. Proceedings of the Interservice/Industry Training, Simulation, and Education Conference. 2003:1-9.
    [32] Liu X., Reynolds P., Brogan D. Using Abstraction in the Verification of Simulation Coercion[C]. Proceedings of the 20th ACM/IEEE Workshop on the Principles of Advanced and Distributed Simulation (PADS). 2006:1-8.
    [33] SISO Base Object Model Product Development Group. Base Object Model (BOM) Template Specification[S].SISO-STD-003-2006.2006.3.
    [34] SISO Base Object Model Product Development Group. Guide for Base Object Model (BOM) Use and Implementation[S]. SISO-STD- 003-2006.2006.3.
    [35]龚建兴,韩超,邱晓刚,黄柯棣.构建可扩展的HLA联邦成员架构[J].系统仿真学报, 2006, 18(11): 3127-3130.
    [36]彭春光,龚建兴,黄柯棣.基于基本对象模型的仿真模型组装器的研究[J].系统仿真学报,2008.20(12):3175-3178.
    [37]龚建兴,钟蔚,黄健等.基本对象模型(BOM)在HLA仿真系统中的应用[J].系统仿真学报, 2006, 18(S2): 327-331.
    [38] EUROPEAN SPACE AGENCY, SMP2.0 Handbook[R]. Europe:ESOC, 2005.10.
    [39] EUROPEAN SPACE AGENCY, SMP2.0 Metamodel[R]. Europe:ESOC, 2005.10.
    [40] EUROPEAN SPACE AGENCY, SMP2.0 Component Model[R]. Europe:ESOC, 2005.10.
    [41] EUROPEAN SPACE AGENCY, SMP2.0 C++ Mapping[R]. Europe:ESOC, 2005.10.
    [42] Pratt, David, Ragusa, L. C., von der Lippe, Sonia. Composability as an Architecture Driver[C]. Proceedings of the 1999 Interservice/Industry Training, Simulation and Education Conference, Orlando Florida, 1999.
    [43] Mikel D. Petty, Eric W. Weisel. A Composability Lexicon[C]. Proceeding of the Spring 2003 Simulation Interoperability Workshop. Orlando FL, 2003, 181-187.
    [44] IEEE, IEEE Standard or modeling and Simulation (M&S) High Level Architecture (HLA)-Framework and Rules[S], Std 1516, 2000.
    [45] IEEE, IEEE Standard or modeling and Simulation (M&S) High Level Architecture (HLA)-Federate Interface Specification[S], Std 1516.1, 2000.
    [46] Mikel D. Petty, Eric W. Weisel. A Formal Basis for a Theory of Semantic Composability[C]. Proceedings of the Spring 2003 Simulation Interoperability Workshop. Orlando FL. 2003: 416-423.
    [47]张童.面向服务的语义可组合仿真关键技术研究[D],国防科技大学,博士论文,2008.4:22-24.
    [48] Yasuhiro Tsujimura, Mitsuo Gen. Genetic algorithms for solving multiprocessor scheduling problems[J]. Lecture Notes in Computer Science, Springer, 1997:106-115.
    [49] GRAHAM R L. Bounds on multiprocessing timing anomalies [J]. SIAM Journal on Applied Mathematics, 1969, 17(2):416-429.
    [50] COFFMAN J E, GAREY M, JOHNSON D. An application of bin-packing to multiprocessor scheduling [J].SIAM Journal on Computing, 1987(7):1-17.
    [51] DONALD K F . Tighter bounds for the multi-fit processor scheduling algorithm[J].SIAM Journal on Computing, 1984, 13(1):170-181.
    [52] KANG Yimei, ZHENG Yingping. Independent task scheduling on identical parallel processors[J].Acta Automatica Sinica, 1997, 23(1): 81-84.
    [53]姜思杰,高彦臣,朱小兵.一类资源负荷均衡问题的误差极小化调度算法[J].系统仿真学报, 2004, 16(2):293-296.
    [54] ALESS ANDRO M, DARIO P. Job-shop scheduling with blocking and no-wait constraints[J]. European Journal of operational Research, 2002, 143(3): 498-517.
    [55] POTTS C N, WHITEHEAD J D. Workload balancing and loop layout in the designof a flexible manufacturing system[J]. European Journal of Operational Research, 2001, 129(2): 326-336.
    [56]曹华军,刘飞,施金良.一类资源负荷均衡问题的优化调度模型及其算法[J].计算机集成制造系统, 2005, 11(5): 669-672.
    [57]何炎祥,罗先林,吴思等.对三种典型分布式任务分配算法的分析[J],小型微型机算机系统,1997.18(11): 1-6.
    [58] Watts J, Taylor S. A practical approach to dynamic load balancing[J]. IEEE Transactions on Parallel and Distributed Systems. 1998, 9(3): 235-248.
    [59]兰舟.基于动态关键任务的多处理器任务分配算法[J].计算机学报, 2007, 30(3): 454-462.
    [60] Chen H, Flann N S, Watson D W. Parallel genetic simulated annealing: a massively parallel SIMD approach[J]. IEEE Transactions on Parallel and Distributed computing. 1998, 9(2): 126-136.
    [61] Marc Dean Millot, Roger Molander, Peter A.Wilson.“The Day After…”Study: Nuclear Proliferation in the Post-Cold War World. Volumn I [R]. USA:RAND, 1993: 7-8.
    [62] Roger C.Molander, David Aaron, Robert E.Hunter, etc.“The Day After…in Jerusalem”A Strategic Planning Exercise on the Path to Achieving Peace in the Middle East[R]. USA: RAND, 2009: 5-18.
    [63] Paul W, Timothy B, Igor G. Joint Synthetic Battlespace: Cornerstone for Predictive Battlespace Awareness[C]. Proceeding of the 8th C2 Research and Technology Symposium, 2003:1-21.
    [64] Dynamic Data Driven Application Systems (DDDAS) Workshop Report [R]. www.cise.nsf.gov/dddas, 2000.
    [65] Dynamic Data Driven Application Systems (DDDAS) Workshop Report[R]. www.cise.nsf.gov/dddas, 2006.
    [66]钱学森,于景元,戴汝为,一个科学领域开放的复杂巨系统及其方法论[J],上海:自然杂志,1990,13(1):3-10.
    [67]胡晓峰,罗批,司光亚等,战争复杂系统建模与仿真[M],国防大学出版社,北京,2005:335-340.
    [68] T.Bemers-Lee, M.Fischetti, M.Dertouzos. Weaving the Web: The Original Design and Utimate Destiny of the World Wide Web by its Invertor[M]. Harper, San Francisco.1999.
    [69]张维明.语义信息模型[M],北京,电子工业出版社,2002.3:1-7.
    [70] Wiederhold. Intelligent Integration of Information[M]. Kluwer Academic. Publishers, Boston MA. 1996:101-110.
    [71] Albert J.“Theoretical Foundation of Schema Restructuring in Heterogeneous Multidatabase Systems”[C]. Proceeding soft the ACM Conference on Information and Knowledge Management, Washington D.C.2000:1-4.
    [72] IEEE, IEEE Standard or modeling and Simulation (M&S) High Level Architecture (HLA)-Object Model Template (OMT)[S], Std 1516.2, 2000.
    [73] SISO. Standard for: Military Scenario Definition Language (MSDL)[Z].SISO-STD-007-2008. 2008.10.
    [74] Studer R, Benjamins V R, Fensel D. Knowledge enineerng: principles and methods [J]. Data and Knowledge Engineering, 1998, 25(122):161-197.
    [75] Lassila O, Swick R R. 1999.Resource Description Framework(RDF) model and syntax[S]. http://www.w3.org/TR/1999/REC-rdf-syntax-19990222.
    [76] Berners-Lee T.1998.Why RDF model is different form the XML model[EB/OL]. http://www.w3.org/DesignIssues/RDF-XML.html.
    [77] Fensel D, van Harmelen F, Horrocks I, etc. OIL: An ontology infrastructure for the semantic web[J]. IEEE Intelligent Systems. 2001.16(2): 38-45.
    [78] Hendler J, McGuinness LD. The DARPA agent markup language[J]. IEEE Intelligent Systems. 2000.15(6):67-73.
    [79] Michael K. Smith,Chris Welty,Deborah L. McGuinness, OWL Web Ontology Language Guide [EB/OL],W3C Recommendation, 2004, http://www.w3.org/TR/ 2004/REC-owl-guide-20040210/.
    [80] Peter F,Pat Hayes,Ian Horrocks,OWL Web Ontology Language Semantics and Abstract Syntax[EB/OL], W3C Recommendation, 2004, http://www.w3.org/TR/ 2004/REC-owl-semantics-20040210.
    [81] Smith M K, Welty C, McGuinness D L. OWL web ontology language guide[EB/OL]. http://www.w3.org/TR/owl-guide. 2004.
    [82] Uschold M, King M. Towards a Methodology for Building Ontologies. In Proceeding of the 14th International Joint Conference on Artifical intelligenceWorkshop on Basic Ontological Issues in Knowledge Sharing[C]. Montreal, Canada, 1995:1-13.
    [83] Gruninger M, Fox M S. The Role of Competency Questions in Enterprise Engineering[C]. In Proceeding of the IFIP WG 5.7 Workshop on Benchmarking: Theory and Practice. Trondheim, Norway, 1994: 212-221.
    [84] Schreiber G, Wielinga B, Jansweijer W. The KACTUS View on the‘O’World[C]. In Proceedings the 14th International Joint Conference on Artificail Intelligence Workshop on Basic Ontological Issues in Knowledge Sharing. Montreal, Canada, 1995:1-10.
    [85] Bernaras A, Laresgoiti I, Corera J. Building and Reusing Ontologies for electricalnetwork Applications[C]. In Proceedings of the 12th European Conference on Artificial Intelligence (ECAI’96). Chichester, UK, 1996: 298-302.
    [86] Gomez-Perez A. A Framework to Verify Knowledge Shring Technology[J]. Expert Systems with Application, 1996, 11(4): 54-60.
    [87] Fernandez M, Gomez P A, Juristo N. Methontology: From Ontological Art Towards Ontological Engineering[C]. In Proceedings of the American Association forArtificail Intelligence Spring Symposium Series on Ontological Engineering. Stanford, California, USA, 1997: 33-40.
    [88] Lopez M F, Gomez-Perez A, Sierra J P, etc. Building a Chemical Ontology Using Methontology and the Ontology Design Environment[J]. IEEE Intelligent System, 1999, 14(1): 37-46.
    [89]张宇航.知识工程中的本体综述[J].计算机工程. 2005.31: 112-114.
    [90] Adam P. Todd M. Object Model Working Group Core Plan Reresentation[R].USA: Springfield,1997:1-19.
    [91] David E. Wikins Karen L. A Common Knowledge Represention for Plan Generation and Reactive Execution[J]. Myers Journal of Logic and Computation 1994:731-761.
    [92] Pease, A. Carrico. The JTF ATD Core Plan Representation: Request for Comment[R]. Armstrong Lab: AL/HR-TP-96-9631, Wright-Patterson AFB, OH. 1996:95-99.
    [93]胡晓峰,司光亚,吴琳等,战争模拟引论[M].北京,国防大学出版社, 2004:98-142.
    [94]毕义明,刘良,刘伟等.军事建模与仿真[M].北京,国防工业出版社. 2009.3: 293-298.
    [95]刘忠,张维明,阳东升等.作战计划系统技术[M].北京,国防工业出版社. 2007.11:35-37.
    [96] Gregory A. Silver, Osama Al-Haj Hassan, John A. Miller. From Domain Ontologies to Modeling Ontologies to Executable Simulation Models[C]. Proceedings of the 2007 Winter Simulation Conference. USA: WSC, 2007: 1108-1117.
    [97] Paul A Fishwick, John A Miller. Ontologies for Modeling and Simulation: Issues and Approaches[C]. Proceedings of the 2004 Winter Simulation Conference. USA: WSC, 2004: 259-264.
    [98] Gregory A Silver, Lee W Lacy, John A Miller. Ontology based Representations of Simulation Models Following the Process Interaction World View [C]. Proceedings of the 2006 Winter Simulation Conference. USA: WSC, 2006: 1168-1176.
    [99] John A Miller, Gregory Baramidze. Simulation and the Semantic Web[C]. Proceedings of the 2005 Winter Simulation Conference. USA: SWC, 2005: 2371-2377.
    [100] Wache H, Vogele T, Visser U, etc. Ontology-Based Integration of Information -A Survey of Existing Approaches[C]. Proceedings of IJCAI-01 Workshop: Ontologies and Information Sharing, Seattle, WA 2001: 108-117.
    [101]金鑫.基于本体的领域信息交互语义化研究[D].东华大学.博士学位论文. 2004.10:6-7.
    [102] Niles I, Pease A. 2001. Toward a standard upper ontology[C]. In Proceeding of the Second International Conference on Formal Ontology in Information System. Ogunquit, Maine, USA, 2-9.
    [103] Fensel D. Ontologies: Silver Bullet for Knowledge Management andCommerce[J]. Berlin, German: Springer-Verlag, 2000:61-75.
    [104] Levenshtein. Binary Codes capable of correcting deletions, insertions, and reversals[J]. Cybernetics and Control Theory. 1966, 10(8):707-710.
    [105] A Rodrfguez, M Egenhofer.Determining Semantic Similarity Among Entity Classes from Different Ontologies[J]. IEEE Transactions on Knowledge and Data Engineering, 2003.15(2): 442-456.
    [106] Anhai D, Jayant M, Pedro D. Learning to map between ontologies on the semantic web[C]. Proceedings of the 11th International WorldWide Web Conference, USA, 2002:662-673.
    [107]彭春光,邱晓刚,张柯.仿真环境下基于XML模式的脚本生成系统研究[J].计算机仿真. 2006.23(8): 248-251.
    [108]彭春光. HLA仿真环境下的脚本生成系统研究[D].国防科学技术大学.硕士学位论文.2005.11: 23-24.
    [109]陆建江,张亚非,苗壮等.语义网原理与技术[M].北京.科学出版社. 2007.3:132-152.
    [110] Horrocks I, Li L, Turi D, ec al. 2004. The instance store: Description logic reasoning with large numbers of individuals[C]. In Proceedings of the 2004 International Workshop on description Logics. Whistler, British Colmbia, Canada, 31-40.
    [111] Baader F, Calvanese D, McGuinness D, etc. The Description Logic Handbook: Theory[M], Implementation and Applications. Cambridge: Cambridge University Press, 2003:5-8.
    [112] Baader F, Horrocks I, Sattler U. Description Logics as Ontology Languages for the Semantic Web[J]. Lecture Notes in Artificial Intelligence, Springer-Verlag, 2005: 228-248.
    [113]夏卉,龙朝晖,描述逻辑语义推理机制的应用研究[J],现代图书情报技术,2006.11: 61-64
    [114] Racer Systems GmbH&Co.KG. RacerPro Reference Manual Version 1.9.[EB/OL]. http://www.racer-systems.com. 2005.12.
    [115] Racer Systems GmbH&Co.KG. RacerPro Reference User’s Guide Version 1.9.[EB/OL]. http://www.racer-systems.com. 2005.12.
    [116] Evren S, Bijan P, Bernardo C G, etc. Pellet: A practical OWL-DL reasoner[J]. Journal of Web Semantics. Elsevier B.V. 2007.3: 51-53.
    [117] Dmitry T, Ian H. FaCT++ Description Logic Reasoner: System Description. Automated Reasoning, Lecture Notes in Computer Science, 2006, Volume 4130/2006: 292-297.
    [118]徐德智,汪智勇,王斌,当前主要本体推理工具的比较与研究[J],现代图书情报技术,2006.(12), 12-15
    [119] Matthew H, Simon J, Georgina M, etc. A Practical Guide To Building OWLOntologies Using Protégé-OWL Plugin and CO-ODE TOOls Edition1.0[R]. The University Of Manchester. 2007.10:14-80.
    [120] M.M. Lehman, FN.Parr.Program Evolution and its Impact on Software Engineering[C]. Proceedings of the 2nd Intenational Conference on Software Engineering. San Francisco, California, United States. 1976: 350-357.
    [121] Michel Wermelinger. A Hierarchic Architecture Model for Dynamic Reconfiguration[C]. Proceedings of the 2nd Intemational Workshop on Software Engineering for Parallel and Distributed Systems. Boston, MA, USA. 1997:243-254.
    [122] Michel Wermelinger. Towards a Chemical Model for Software Architecture Reconfiguration[C]. Proceedings of the International Conference on Configurable Distributed Systems. Washington, DC, USA. 1998: 111-118.
    [123] Moazami G.Consistency preserving dynamic reconfiguration of distributed systems[D]. Ph.D. thesis, Imperial College, London. 1999.3.
    [124] SISO Base Object Model Product Development Group. Base Object Model (BOM) Template Specification[S]. SISO-STD-003-2006.2006.3
    [125] SISO Base Object Model Product Development Group. Guide for Base Object Model (BOM) Use and Implementation[S]. SISO-STD-003-2006.2006.3
    [126]张琦,尹全军,黄柯棣.基本对象模型概念研究[J].系统仿真学报, 2005, 17(7): 1667-1669.
    [127]刘秀罗.可组构性建模与仿真技术研究及应用[R].博士后出站报告.北京:国防大学, 2005.5
    [128]龚建兴.基于BOM的可扩展仿真系统框架研究[D],国防科技大学,博士论文,2007.4: 110-112.
    [129]李渊,何明.基于BOM进行快速仿真开发的关键技术研究[C].中国自动化学会系统仿真专业2004年会. 2004.
    [130]王志坚,费玉奎,娄渊清.软件构件技术及其应用[M].北京:科学出版社. 2005:122-135.
    [131] Oandamudi S P, Cheng P. A hierarchical Task Queue Organization for Shared-Memory Multiprocessor Systems[J] , IEEE Transaction On Parallel and Distributed System, 1995, 6(1):1-16.
    [132] Beaumont O, Legrand A, Robert Y. Optimal Algorithms for Scheduling Divisible Workloads on Heterogeneous Systems[C]. In Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS’03), 2003: 98-111.
    [133] Cheng Shuchu,Huang Yuehmin.Scheduling multi-processor tasks with resource and timing constraints using genetic algorithm[C]. IEEE International Symposium on Computational Intelligence in Robotics and Automation,2003:624-629.
    [134]朱福喜.启发式合调度和面向AND/OR约束的调度算法研究[D],武汉大学研究生院博士论文, 2002:18-21.
    [135]朱福喜,何炎祥.并行分布计算中的调度算法理论与设计[M].武汉大学出版社. 2003: 22-23.
    [136] Simons,Barbara.Multiprocessor Scheduling of Unit-Time Jobs with Arbitrary Release Times and Deadlines[J].SIAM Journal On Computing, 1983.6(2), 294-299.
    [137] M.A.Al-Mouhamed.Lower Bound on the Number of Processors and Time for Scheduling Precedence Graphs with Communication Costs[J]. IEEE Transactions on Software Engineering.1990.16(12), 1390-140l.
    [138] Jie W. Distributed System Design[M]. China Machine Press. 2001:224-225.
    [139] Ishfaq, A. and G.Arif, Semi-distributed load balance for massively parallel multicomputer systems[J], IEEE Transactions on Software Engineering, 1991, 17(10),987-1004
    [140] Leff A, Yu P S. An Adaptive stragety for load sharing in distributed database environments with information lags[J], Journal of Parallel and Distributed Computing, 1991: 91-103
    [141] Xu, J. and K.Hwang, Heuristic methods for dynamic load balancing in a message-passing multicomputer[J], Journal of Parallel and Distributed Computing, 1993: 1-13.
    [142] Chunguang Peng, Qiang He, Xiaocheng Liu, etc. Component Scheduling in the Distributed Simulation based on BOM[C]. 2nd International Conference on Computer Modeling and Simulation (ICCMS 2010), January 2010, Sanya, China:vol2, 98-102.
    [143]彭春光,刘健,黄柯棣.基于基本对象模型的组件式成员规划技术研究[J].系统仿真学报,2009.21(15):4697-4700.
    [144] Farn Wang,Al Mok,E.Allen Emerson,Formal Specification of Asynchronous Distributed Real-time Systems by APTL[C]. Proceeding of Tri’ada, 1995, 132-156.
    [145] Gerasoulis, T.Yang. A comparison of Clustering Heuristics for Scheduling DAGs on Multiprocessors[J]. Journal of Parallel and Distributed Computing, 1992, 16(4), 276-291.
    [146]鞠九滨,杨鲲,徐高潮.使用资源利用率作为负载平衡系统的负载指标[J].软件学报. 1996. 7(4): 238-243.
    [147] Zhou Songnian, Zheng Xiaohu. Utopia: load sharing facility for large, heterogeneous distributed computer system[J]. Software Practice and Experience, 1993, 23(12):1305-1336.
    [148] Zhang Xiaodong, Qu Yanxia, Xiao Li. Improving distributed work load performance by sharing both CPU and memory resources[C]. In: Proceeding of 20th International Conference on Distributed Computing Systems. ICDCS2000, 2000:1-9.
    [149] Mor Harchol Balter, Allen Downey B. Exploiting process lifetime distributions for dynamic load balancing[J]. ACM Transaction on Computer System, 1997, 15(3):253-285.
    [150] Bozyigit M, Melhi M. Load balancing framework for distributed system[J]. Computer System Science&Engineering, 1997, 12 (5) :287-293.
    [151]胡凯.网络分布式并行计算的负载平衡[J].北京航空航天大学学报, 2004, 30(11):1121-1124.
    [152]张柯,邱晓刚,彭春光等.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.
    [153]彭春光,段伟,张柯等.分布仿真实验管理系统的兼容性研究[J].系统仿真学报,2008,20(24):6643-6645.
    [154]段伟,彭春光,张柯等.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.
    [155]刘晓铖,张柯,陈彬等.分布仿真实验管理系统中实验运行控制工具的设计[J]系统仿真学报,2008,20(24):6646-6649.
    [156]陈彬,张柯,刘晓铖等.分布仿真实验管理系统网络中间件的研究与实现[J].系统仿真学报,2008,20(24):6639-6642.
    [157]刘健,张柯,彭春光等.分布仿真实验管理系统中守护端的设计与实现[J].系统仿真学报,2008,20(24):6636-6638.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700