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网格GIS下协同式空间信息工作流实现技术研究
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摘要
随着信息处理技术的迅速发展和计算机软硬件设备的不断升级换代,空间信息的采集、生产、处理及存储的方式和手段获得了很大的进步,各个空间信息应用领域的空间数据规模呈指数级别增长,传统的单机集中式数据处理方式逐渐被以计算机网络为基础的行业空间信息基础设施所替代,提高了空间信息并行处理和分布式共享的程度。现有的行业空间信息基础设施网络环境的建设,为地域上分散的多个空间信息业务节点提供了高速的网络互连,使传统集中汇总式的业务流程向分布式并行处理方式的改变成为可能。但是现有的空间信息网格环境中的大量线匕业务系统主要采用的是传统Web GIS技术构建,并未能有效地解决传统的集中式空间信息处理带来的性能瓶颈问题和业务处理的复杂性问题。主要表现在:现有的Web GIS软件架构无法提供多个业务节点服务共同参与的协同式自动计算,只能够分别由各个业务节点调用本地的计算资源独立地处理本地的空间信息,然后通过网络传输对各个业务节点的计算结果逐个进行汇总。如果要更新空间信息处理的算法策略,必须对各个节点逐个地进行功能服务的更新,加重了业务系统运维的复杂度与成本,无法真正实现空间信息的分布式处理。
     网格空间信息服务工作流系统(Grid Geospatial Service Workflow System)是当前网格工作流技术与空间信息处理技术相结合的发展方向和研究重点,它将地理信息系统软件在单机系统上的处理能力提升到网格分布式环境中来,通过网格空间信息处理中间件屏蔽掉底层多源异构空间信息计算资源的复杂性,以网格服务的形式统一封装成上层的抽象资源,通过对空间信息网格服务资源的流程组合与任务编排,实现真正的空间信息分布式协同处理,充分利用了计算机网络带来的性能优势。协同式网格空间信息服务工作流技术可以按照应用需求组合空间信息网格环境中的各种空间功能服务和非空间信息服务,通过业务的流程化建模和分布式工作流引擎的任务调度可以有效地实现各个工作节点的协同工作,减少人工干预的同时,大大提高工作效率,保证数据安全性的同时具备了一定的容错性,并能整合遗留空间信息业务系统的空间功能。通过网格空间信息服务工作流管理组件,用户可以方便地使用多种空间信息资源,极大地改变了效率低下的空间业务运行模式,为网格环境下地域上分布的空间信息的集成共享提供了重要的技术保障。
     本文结合国家863重点项目“网格地理信息系统软件及其重大应用”,主要围绕网格环境下空间信息服务分布式协同处理的应用模型与实现方法,重点研究了如何采用协同式空间信息服务工作流技术解决网格GIS环境中空间信息资源组织管理、空间信息网格服务建模、业务流程构造方式和计算资源动态协作等一系列关键性问题,这对改变现有空间信息网格的行业应用模式,进一步深入推动网格技术与空间信息处理领域的结合,有着重要的现实意义。通过研究面向网格环境的空间信息资源层次化的发布及管理机制,提供了网格空间信息工作流统一的资源组织与动态映射模型,在此模型下,各种异构多源的空间数据、空间功能被跨平台的GIS内核统一融合,以网格资源统一定位符URL的方式提供给上层的工作流框架,使得工作流建模不用考虑底层资源的复杂细节;研究面向网格空间信息服务工作流的服务资源的建模方法,从服务底层逻辑功能的实现角度出发,建立了可拆卸、可动态迁移、可快速聚合的网格服务资源模型,在此基础上提出了协同式空间信息服务工作流的形式化模型并给出了基于该模型的服务资源的无缝迁移算法;研究了适用于网格环境下的分布式空间信息服务工作流系统实现的关键技术,通过建立高效的流程服务资源的动态发现与集成机制,提高了工作流系统的调度效率;基于空间功能仓库原子组件的服务资源流程化建模技术,实现了网格服务资源在工作流执行过程中的无缝迁移功能;通过对工作流引擎服务调用接口的松耦合扩展,实现了与异构业务系统功能服务的交互;结合国家地质调查等行业空间信息网格的应用现状和业务特点,通过构建行业网格空间信息作流平台原型系统,实现了基于协同式空间信息工作流的行业应用的快速构建与部署,为跨行业、跨领域的分布式空间信息获取、管理、处理及集成共享提供了基于网格工作流技术的可行性方案。具体的研究工作如下:
     (1)分析了网格计算技术、网格地理信息系统技术等分布式计算技术的研究现状及发展趋势,指出以网格技术、云计算技术为支撑的分布式空间信息处理技术必将是空间信息集成共享与应用领域发展的必然趋势;通过对网格工作流技术在空间信息处理领域研究现状的分析,指出了网格环境下空间信息工作流的理论研究和发展与实际应用需求之间还存在着很大的差距,建立协同式网格空间信息工作流模型可以很好的实现网格技术与空间信息领域模型的融合。提出协同式网格空间信息工作流的实现需要解决流程资源的组织与调度,空间功能服务的建模及协同交互等一系列关键性的问题。
     (2)研究了网格环境下流程资源节点空间信息资源的聚合发布模型。设计了跨平台的GIS内核框架,采用空间数据仓库和空间功能仓库技术对网格节点上异构多源的空间数据资源和空间功能资源进行了集成融合和统一发布,将节点流程资源抽象成4类网格资源,建立了面向空间信息工作流系统的节点资源抽象模型。研究了节点资源网格化封装技术,设计了包含节点信息服务、节点资源管理服务、节点状态监控服务以及节点空间功能服务的节点资源中间件。以节点空间信息网格资源对象的关系模型为基础,重点对节点信息服务、资源管理服务、节点状态监控服务功能接口的实现算法进行了详细的描述。流程节点的资源模型体现了网格节点既独立自治,义面向应用协同的特征。
     (3)研究了网格环境下空间信息工作流的全局资源模型。采用关系模型的方法对全局资源目录视图中的节点、空间数据、GIS服务、空间虚拟组织及全局用户对象进行了分类表达,重点论述了网格用户对全局资源访问的权限映射模型,用关系代数的方法对其进行了规则优化;在全局目录模型的基础上,设计了全局资源目录管理服务,实现了资源目录的动态更新机制。建立节点、空间虚拟组织、全局形式的三级分布式空间索引模型,实现了全局空间数据资源和虚拟组织范围内的空间数据资源的快速定位与发现。建立全局空间数据资源冗余模型,实现了工作流执行过程中空间数据资源的动态匹配,提高了工作流系统的容错性。建立了空间信息虚拟组织流程业务组织模型,实现了全局用户资源权限规则在虚拟组织中的完整映射和基于动态虚拟组织的流程资源协作。
     (4)研究了基于服务功能模板的空间信息网格服务的构建方法,在此基础上,采用活动网络图的方法建立了协同式网格空间信息服务工作流的模型。对基于协同式空间信息工作流模型的资源调度与迁移算法进行了形式化的研究。提出了协同式网格空间信息服务工作流实现的总体框架,围绕该框架研究了流程服务资源的动态发现与集成、服务功能流程模板实现的关键技术;研究了分布式服务工作流引擎实现的关键技术,通过合理扩展,实现了网格工作流系统和异构业务系统之间的对接与集成。提出了由资源发现、功能迁移和服务模板迁移组成的网格服务迁移模型,并采用空间功能仓库和空间数据仓库技术实现了流程资源的自动迁移功能。
     (5)研究了网格GIS协同式空间信息工作流与应用系统集成的关键技术。建立了基于协同式空间信息工作流技术的应用系统的总体框架,分析了工作流应用系统底层功能的支撑模块及业务组织模式。通过对现有空间信息网格的架构分析,在将网格GIS环境与基于Web GIS技术的空间应用服务系统进行无缝集成的基础上,建立了地质调查信息网格服务工作流原型系统,描述了系统主要功能模块的实现。以全国重要矿产资源潜力预测评价应用为研究对象,设计实现了基于体积法的协同式矿产资源储量分布式计算工作流应用模块,通过与已有业务系统运行结果的分析比较,验证了协同式工作流模型方案的有效性与合理性。
With the rapid development of information processing techniques and the continuous upgrading of computers, the way for spatial information acquisition, production, processing and storage had made great progress. This makes the amount of spatial information in every spatial information application domain increase exponentially. The classic centralized processing method by one single computer has been replaced by the distributed processing mode based on the spatial information infrastructure built on computer networks. This processing model improves the capability of parallel processing and distributed sharing of spatial information. The establishment of current spatial information infrastructure for industry provides high speed network connection for multiple spatial information service nodes. This makes it possible to transform the centralized business processing model into the distributed parallel processing model. Actually lots of online service systems were built on classic Web GIS platform in spatial information infrastructure environment:it doesn't effectively tackle the performance issues and reduce the complexity brought by the classic centralized processing model. The problems are mainly reflected in the following:multiple service nodes can't achieve cooperative computing automatically under the architecture of Web GIS platform. The reality is that every service node operates on their local information resource respectively, and then transfers their processing results to one aggregation node one by one. If the processing strategy changed, updating must be performed on every work node. This aggravates the difficulties of system maintenance and increase the cost. It is impossible to achieve the real distributed spatial information processing.
     Geospatial Grid Service Workflow System is the emphases of research and development direction of the combination of grid workflow technologies and spatial information processing technologies. It transformed the processing capabilities of a single computer into the Grid processing capabilities by using Grid spatial information processing middleware to shield the complexity of the bottom multi-source heterogeneous spatial information computing resource, then to use Grid services to encapsulate them into the upper abstract uniform resources. After that, it can achieve the real distributed processing of spatial information by service combination and process orchestration. It can fulfill the performance advantages provided by the computer networks. Cooperative Grid spatial information workflow can freely combine GIS functional services and non-GIS-functional services that exist in Spatial Information Grid. By using the business process modeling techniques and the scheduling mechanisms of distributed workflow engine, Cooperation work among working node can be effectively implemented. The efficiency is greatly raised without manual intervention. It also has the advantages of security and fault tolerance of spatial data, and can be integrated with legacy business systems. Through the spatial information workflow management middleware, clients can use many kind of spatial information resource. It improves operating efficiency of spatial information service and provides the reliable technology guarantee for the integration and sharing of spatial information resource distributed among different nodes.
     This paper, which is supported by the Major Project of National High-tech R&D Program (863Program)"Grid GIS and Its Major Applications", mainly discussed the application model and implementation techniques of spatial information service cooperative processing in Grid computing environment. It focuses on solving the critical problems on spatial information organization and management, Grid-enabled spatial information service modeling, business process construction and computing resource cooperation dynamically. It has practical significance for changing the application patterns of Spatial Information Grid and furthering the combination of Grid Computing and spatial information processing. Through studying on the hierarchical publication and management mechanism for spatial information resource in Spatial Information Grid, a uniform organization and dynamical mapping model is presented. In this model, all multi-source heterogeneous spatial information computing resource, including spatial data, GIS service, are seamless integrated into the resource framework through the cross-platform GIS kernel component and provided to the workflow system modeling layer as Grid Uniform Resource Locator (URL) form. Based on that, workflow framework does process orchestration without considering the complex detail about bottom resources. The service-oriented modeling method is also studied; a Grid service composition model is presented from the perspective of its bottom function-realization. This model has characteristics of easy-disassembly, dynamical-transfer-enabled, rapid assembly. Cooperative spatial information workflow formalization model is provided on the basis of service composition model and a service seamless migration algorithm is also proposed. A series of key implementation technologies of distributed spatial information workflow system were studied:through modifying the classic Grid monitoring and discovering system, a efficient process resource monitoring and discovering system was realized and it can raise workflow system efficiency. Grid service seamless migration function in the process of executing a workflow instance is implemented on the basis of a service composition function supported by the spatial function warehouse. A service integration and invocation tool, as a loosely extension of workflow engine service is realized to support the interaction between workflow system and other legacy service system. Analyzed the application status and business nature of Spatial Information Grid such as China Geology Survey Information Grid (CGSIG) and developed the CGSIG workflow prototype system. Based on that, some workflow application module is rapid implemented and deployed on CGSIG. All this provided a feasible scheme for distributed spatial information retrieval, management, processing, integration and sharing across different industries and departments using Grid spatial information workflow technologies. The details of our study are listed as follow:
     (1) Analyzed the research status and development trend of distributed computing techniques such as Grid computing and Grid GIS, pointed out the distributed spatial information processing techniques supported by the Grid computing and Cloud computing will be the inevitable development trend of spatial information integration and sharing application. Based on the research status of Grid workflow techniques in spatial information processing field, pointed out that there is a considerable gap between Grid workflow and the current application requirements, and the implementation of cooperative spatial information workflow may better achieve fusion of Grid computing techniques and spatial information field. A series of critical technical problems including process resource organization and scheduling, GIS functional service composition and interoperability must be resolved for the spatial information workflow system.
     (2) Analyzed the aggregation publish model of spatial information resource on one process node in Grid. Designed the cross-platform GIS kernel framework and realized the integration and uniform publish of multi-source heterogeneous spatial data resource and spatial function resource using spatial data warehouse and spatial function warehouse techniques. Node resource abstract model for spatial information work flow was presented by abstracting the process node resource into four logical resources. Grid service based encapsulation techniques for node logical resources is also discussed. Node resource middleware including node information service, Node resource management service, node status monitoring service and node GIS service was designed and implemented. Based on the relational model of node resource objects, the algorithms of the web interface of node information service, resource management service and node status monitoring are addressed. The node resource model embodies the feature of independent and autonomous, and application-oriented collaborative.
     (3) Analyzed the global resource model of Grid spatial information workflow. Classified node object, spatial data, GIS service, and spatial virtual organization and Grid users in the global resource directory view by relational model and illustrated the uniform representation for these objects. The user access privileges mapping model for workflow resources was focused on, and some optimization have been done for this model using relational algebra. Based on the global resource directory model, the global resource directory management service was designed to support the dynamical updating mechanism. A three level distributed spatial index model which consist of node, spatial virtual organization and global object is presented to realize rapid resource locating and discovering in global resource or in specific virtual organization. The global redundancy replica model for spatial data is established to support the spatial data replica dynamical match during the process execution, and it improves fault-tolerance for workflow system. Spatial information virtual organization model is discussed and user access privileges in spatial information virtual organization and global range are unified.
     (4) Analyzed service composition model on the basis of service function template. Based on that, activity network graph is adopted to establish the cooperative spatial information workflow. Formalization of the resource scheduling and migration algorithm was presented. The overall implementation framework of cooperative spatial information workflow is presented. Centering on this framework, the process resource dynamical locating&integration and the implementation of function template based service composition are discussed. the key technologies of distributed service workflow engine was analyzed. The assembly and integration function between workflow system and heterogeneous legacy system is implemented. A three-step Grid service migration model which consists of resource locating, function migration and service template migration was presented and the automatic migration function was realized by using spatial function warehouse and spatial data warehouse techniques.
     (5) Analyzed key technologies of the cooperative spatial information workflow and application system integration. Establish the overall framework of the collaborative spatial information workflow technology-based application system. The underlying functionality support modules of workflow applications and business organizational model are discussed. By analyzing existing Spatial Information Grid architectures, the Geological Survey Information Grid workflow prototype system was built on the basis of seamless integration of Grid GIS environment and Web GIS-based spatial information service system and the main function modules of the system were illustrated. Choose national important mineral resource potential prediction and evaluation application as research object, design and implement the distributed mineral resources reserves volume-estimating-method-based computing application modules using cooperative workflow techniques. Through the analysis of the results with existing online Web GIS based business systems. The rationality and validity of collaborative spatial information workflow were validated.
引文
[1]Foster I, Kesselman C. Globus:A metacomputing infrastructure toolkit[J]. International Journal of Supercomputer Applications and High Performance Computing.1997,11(2):115-128.
    [2]Huang Z, Fang Y, Chen B, et al. Development of a Grid GIS prototype for geospatial data integration[C]. Shenzhen, China:7th International Conference on Grid and Cooperative Computing, GCC 2008, October 24,2008-October 26,2008. Inst. of Elec. and Elec. Eng. Computer Society,2008.
    [3]Sun Q, Chi T, Wang X, et al. Design of Middleware based Grid GIS[C]. Seoul, Korea, Republic of:2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005, July 25, 2005-July 29,2005. Institute of Electrical and Electronics Engineers Inc.,2005.
    [4]Wan L, Xie Z, Wu L, et al. MGSCP:A scalable service migration framework for spatial information grid[C]. Shanghai, China:2011 19th International Conference on Geoinformatics, Geoinformatics 2011, June 24,2011-June 26,2011. IEEE Computer Society,2011.
    [5]Wu M, Shen J, Wen Y, et al. On the Grid-enabled geospatial information workflow[C]. Nanjing, China:1st International Conference on Information Science and Engineering, ICISE2009, December 26, 2009-December 28,2009. IEEE Computer Society,2009.
    [6]李德仁.论广义空间信息网格和狭义空间信息网格[J].遥感学报.2005(5):513-520.
    [7]方裕,邬伦,谢昆青,等.分布式协同计算的GIS技术研究[J].地理与地理信息科学.2006(3):9-12.
    [8]林峰,郭宝,钱蔚.面向公共电网GIS平台的电网地理图形应用架构[J].电力系统自动化.2011(24):63-67.
    [9]亢大麟,张君.基于网格GIS的旅游统计数据可视化研究[J].统计与信息论坛.2011(12):70-74.
    [10]Foster I, Kesselman C. The Globus project:a status report[J]. Future Generation Computer Systems.1999,15(5-6):607-621.
    [11]Foster I, Kesselman C, Tuecke S. The anatomy of the grid:Enabling scalable virtual organizations[J]. International Journal of High Performance Computing Applications.2001,15(3): 200-222.
    [12]Foster I. What is the Grid?-a three point checklist[J]. GRIDtoday.2002,1(6).
    [13]Stoica I, Morris R, Karger D, et al. Chord:A scalable peer-to-peer lookup service for internet applications[J]. SIGCOMM Comput. Commun. Rev.2001,31(4):149-160.
    [14]Litzkow M J, Livny M, Mutka M W. Condor-a hunter of idle workstations[C]. Distributed Computing Systems,1988.,8th International Conference on.1988.
    [15]Berman F, Fox G C, Hey A J G. Grid computing:making the global infrastructure a reality[M]. New York:J. Wiley,2003:1012.
    [16]Foster I, Kesselman C. Globus project:a status report[J]. Future Generation Computer Systems. 1999,15(5):607-621.
    [17]Grimshaw A S, Wulf W A, Team C T L. The Legion vision of a worldwide virtual computer[J]. Commun. ACM.1997,40(1):39-45.
    [18]Roman D, Keller U, Lausen H, et al. Web Service Modeling Ontology[J]. Appl. Ontol.2005,1(1): 77-106.
    [19]Fielding R, Gettys J, Mogul J, et al. Hypertext Transfer Protocol---{HTTP}/1.1[J].1999(2616).
    [20]Murata M, Lee D, Mani M, et al. Taxonomy of XML schema languages using formal language theory[J]. ACM Trans. Internet Technol.2005,5(4):660-704.
    [21]Vinoski S. CORBA:integrating diverse applications within distributed heterogeneous environments[J]. Communications Magazine, IEEE.1997,35(2):46-55.
    [22]Sessions R. COM and DCOM:Microsoft's vision for distributed objects[M]. John Wiley\& Sons, Inc.,1998.
    [23]Prodan R, Fahringer T. From Web services to OGSA:experiences in implementing an OGSA-based grid application[C].2003.
    [24]Curbera F, Duftler M, Khalaf R, et al. Unraveling the Web services web:an introduction to SOAP, WSDL, and UDDI[J]. Internet Computing, IEEE.2002,6(2):86-93.
    [25]Tuecke S, Czajkowski K, Foster I, et al. Open Grid Services Infrastructure (OGSI)[J].
    [26]Foster I, Czajkowski K, Ferguson D E, et al. Modeling and Managing State in Distributed Systems:The Role of OGSI and WSRF[J]. Proceedings of the IEEE.2005,93(3):604-612.
    [27]Foster I. Globus Toolkit Version 4:Software for Service-Oriented SystemsNetwork and Parallel Computing[J].2005,3779:2-13.
    [28]Welch V, Siebenlist F, Foster I, et al. Security for Grid services[C]. High Performance Distributed Computing,2003. Proceedings.12th IEEE International Symposium on.2003.
    [29]Huedo E, Montero R S, Llorente I M. A modular meta-scheduling architecture for interfacing with pre-WS and WS Grid resource management services [J]. Future Generation Computer Systems. 2007,23(2):252-261.
    [30]Smith C. Open source metascheduling for virtual organizations with the community scheduler framework (CSF)[J]. Technical whitepaper, Platform Computing.2003.
    [31]Feng H, Misra V, Rubenstein D. PBS:a unified priority-based schedule[J]. SIGMETRICS Perform. Eval. Rev.2007,35(1):203-214.
    [32]Wei X, Li W, Tatebe O, et al. Integrating Local Job Scheduler-LSF TM with Gfarm TM[J]. Parallel and Distributed Processing and Applications.2005:196-204.
    [33]Geer D. Grid Computing Using the Sun Grid Engine[J]. Technical Enterprises, Inc.2003.
    [34]Allcock W, Bresnahan J, Kettimuthu R, et al. The Globus Striped GridFTP Framework and Server[C]. Proceedings of the 2005 ACM/IEEE conference on Supercomputing. IEEE Computer Society,2005.
    [35]Madduri R K, Hood C S, Allcock W E. Reliable file transfer in Grid environments[C]. Local Computer Networks,2002. Proceedings. LCN 2002.27th Annual IEEE Conference on.2002.
    [36]Chervenak A L, Schuler R, Ripeanu M, et al. The Globus Replica Location Service:Design and Experience[J]. Parallel and Distributed Systems, IEEE Transactions on.2009,20(9):1260-1272.
    [37]Schopf J M, Pearlman L, Miller N, et al. Monitoring the grid with the Globus Toolkit MDS4[C]. Journal of Physics:Conference Series. IOP Publishing,2006.
    [38]Herness E N, High J R J, Mcgee J R. WebSphere Application Server:A foundation for on demand computing[J]. IBM Systems Journal.2004,43(2):213-237.
    [39]Ferreira L, International B M C I, Ebrary I. Grid Computing with the IBM Grid Toolbox[M]. IBM, International Technical Support Organization,2004.
    [40]Romberg M. The UNICORE Grid infrastructure[J]. Sci. Program.2002,10(2):149-157.
    [41]Bradley J, Brown C, Carpenter B, et al. The OMII Software Distribution[C]. East Midlands Conference Centre, Nottingham:All Hands Meeting 2006.2006.
    [42]Gentzsch W, Girou D, Kennedy A, et al. DEISA-Distributed European Infrastructure for Supercomputing Applications[J]. Journal of Grid Computing.2011,9(2):259-277.
    [43]Schwiegelshohn U. D-Grid:A national grid infrastructure in Germany[J]. Annales des Telecommunications/Annals of Telecommunications.2010,65(11-12):763-769.
    [44]Walton N A, Lawrence A, Linde T. AstroGrid:Powering science from multi-streamed data[C]. Glasgow, United kingdom:Optimizing Scientific Return for Astronomy through Information Technologies, June 24,2004-June 25,2004. SPIE,2004.
    [45]Ng M H, Johnston S, Wu B, et al. BioSimGrid:Grid-enabled biomolecular simulation data storage and analysis[J]. Future Generation Computer Systems.2006,22(6):657-664.
    [46]Antonioletti M, Atkinson M, Baxter R, et al. The design and implementation of Grid database services in OGSA-DAI[J]. Concurrency and Computation:Practice and Experience.2005,17(2-4): 357-376.
    [47]P A A S A. The gLite workload management system[J]. Journal of Physics:Conference Series. 2008,119(6):62007.
    [48]Ruth P A D P. The open science grid[J]. Journal of Physics:Conference Series.2007,78(1): 12057.
    [49]Beckman P H. Building the TeraGrid [J]. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.2005,363(1833):1715-1728.
    [50]Depei Q. CNGrid:a test-bed for Grid technologies in China[C]. Distributed Computing Systems, 2004. FTDCS 2004. Proceedings.10th IEEE International Workshop on Future Trends of.2004.
    [51]Xu Z, Li W, Zha L, et al. Vega:A Computer Systems Approach to Grid Computing[J]. Journal of Grid Computing.2004,2(2):109-120.
    [52]de Alfonso C, Caballer M, Hernandez V. WINGS:Versatile Workflow for the Grid[C]. Advanced Engineering Computing and Applications in Sciences,2008. ADVCOMP'08. The Second International Conference on.2008.
    [53]Stanoevska-Slabeva K, Parrilli D, Thanos G. BEinGRID:Development of Business Models for the Grid IndustryGrid Economics and Business Models[J].2008,5206:140-151.
    [54]Ghemawat S, Gobioff H, Leung S. The google file system[C]. Lake George, NY, United states: SOSP'03:Proceedings of the 19th ACM Symposium on Operating Systems Principles, October 19, 2003-October 22,2003. Association for Computing Machinery,2003.
    [55]Chang F, Dean J, Ghemawat S, et al. Bigtable:A distributed storage system for structured data[J]. ACM Transactions on Computer Systems.2008,26(2).
    [56]Burrows M. The Chubby lock service for loosely-coupled distributed systems[C]. Seattle, Washington:USENIX Association,2006.
    [57]Dean J, Ghemawat S. MapReduce:simplified data processing on large clusters[J]. Commun. ACM.2008,51(1):107-113.
    [58]Naghshineh M, Ratnaparkhi R, Dillenberger D, et al. IBM Research Division cloud computing initiative[J]. IBM Journal of Research and Development.2009,53(4):1.
    [59]Buyya R, Chee S Y, Venugopal S. Market-Oriented Cloud Computing:Vision, Hype, and Reality for Delivering IT Services as Computing Utilities[C]. High Performance Computing and Communications,2008. HPCC'08.10th IEEE International Conference on.2008.
    [60]Foster I, Yong Z, Raicu I, et al. Cloud Computing and Grid Computing 360-Degree Compared[C]. Grid Computing Environments Workshop,2008. GCE'08.2008.
    [61]Bohn R B, Messina J, Fang L, et al. NIST Cloud Computing Reference Architecture[C]. Services (SERVICES),2011 IEEE World Congress on.2011.
    [62]Garrett J. Ajax:A New Approach to Web Applications[J].2005.
    [63]Vaughan-Nichols S J. Will HTML 5 Restandardize the Web?[J]. Computer.2010,43(4):13-15.
    [64]Buxmann P, Hess T, Lehmann S. Software as a Service[J]. WIRTSCHAFTSINFORMATIK. 2008,50(6):500-503.
    [65]Keller E, Rexford J. The "Platform as a service" model for networking[C]. San Jose, CA: Proceedings of the 2010 internet network management conference on Research on enterprise networking. USENIX Association,2010.
    [66]Prodan R, Ostermann S. A survey and taxonomy of infrastructure as a service and web hosting cloud providers[C]. Grid Computing,2009 10th IEEE/ACM International Conference on.2009.
    [67]Li A, Yang X, Kandula S, et al. CloudCmp:comparing public cloud providers[C]. Melbourne, Australia:Proceedings of the 10th annual conference on Internet measurement. ACM,2010.
    [68]Marinos A, Briscoe G. Community Cloud ComputingCloud Computing[J].2009,5931:472-484.
    [69]Grossman R L. The Case for Cloud Computing[J]. IT Professional.2009,11(2):23-27.
    [70]Juve G, Deelman E, Vahi K, et al. Scientific workflow applications on Amazon EC2[C]. E-Science Workshops,2009 5th IEEE International Conference on.2009.
    [71]Miller F P, Vandome A F, Mcbrewster J. Amazon Web Services[J].2010.
    [72]Palankar M R, Iamnitchi A, Ripeanu M, et al. Amazon S3 for science grids:a viable solution?[C]. Proceedings of the 2008 international workshop on Data-aware distributed computing. ACM,2008.
    [73]Zahariev A. Google App Engine[J]. Helsinki University of Technology.2009.
    [74]Campbell D G, Kakivaya G, Ellis N. Extreme scale with full sql language support in microsoft sql azure[C]. Proceedings of the 2010 international conference on Management of data. ACM,2010.
    [75]Borthakur D. The hadoop distributed file system:Architecture and design[J]. Hadoop Project Website.2007,11:21.
    [76]Borthakur D. Hdfs architecture guide[J].2010 08-17)[2010-12-01]. http://hadoop.apache org/hdfs/docs/r0.21.0/hdfs——design.pdf.2008.
    [77]Kellerman J. Hbase:Structured storage of sparse data for hadoop[J].2009.
    [78]Hunt P, Konar M, Junqueira F P, et al. ZooKeeper:Wait-free coordination for Internet-scale systems[C]. Proceedings of the 2010 USENIX conference on USENIX annual technical conference. USENIX Association,2010.
    [79]Clark R. OpenStack Open Source Cloud Computing Software. San Francisco, CA,2010[J].
    [80]Khetrapal A, Ganesh V. HBase and Hypertable for large scale distributed storage systems[J]. Dept. of Computer Science, Purdue University.2006.
    [81]Iskold A. Amazon dynamo:The next generation of virtual distributed storage[J].2007.
    [82]Chodorow K, Dirolf M. MongoDB:the definitive guide[M]. O'Reilly Media, Inc.,2010.
    [83]Anderson C. Apache CouchDB:The definitive Guide[J]. http://couchdb.Apache.org/index.htm Acessado em.2009,5(06):2009.
    [84]Hewitt E. Cassandra:the definitive guide[M]. O'Reilly Media, Inc.,2010.
    [85]Paksula M. Persisting Objects in Redis Key-Value Database[J]. Science.2010.
    [86]Viswanath B, Mislove A, Cha M, et al. On the evolution of user interaction in facebook[C]. Proceedings of the 2nd ACM workshop on Online social networks. ACM,2009.
    [87]Java A, Song X, Finin T, et al. Why we twitter:understanding microblogging usage and communities[C]. Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis. ACM,2007.
    [88]Keahey K. Nimbus:Open Source Infrastructure-as-a-Service Cloud Computing SoftwarefC]. Workshop on adapting applications and computing services to multicore and virtualization, CERN, Switzerland.2009.
    [89]Keahey K, Foster I, Freeman T, et al. Virtual workspaces:Achieving quality of service and quality of life in the grid[J]. Scientific Programming.2005,13(4):265.
    [90]Bresnahan J, Keahey K, Labissoniere D, et al. Cumulus:an open source storage cloud for science[C]. Proceedings of the 2nd international workshop on Scientific cloud computing. ACM,2011.
    [91]Wms O. Web Map Server Interfaces Implementation Specification,2001[S].
    [92]Vretanos P. Web feature service implementation specification [S].2005:2005.
    [93]Hassan M M, Huh E N. An Efficient Grid Based Metadata Processing And Sharing Architecture For GEOSS[C]. Advanced Communication Technology,2008. ICACT 2008.10th International Conference on. IEEE,2008.
    [94]Chu K D, Di L, Thornton P. Introduction of grid computing application projects at the NASA earth science technology office[J]. Advances in Grid and Pervasive Computing.2006:289-298.
    [95]Gorgan D, Rodila D, Bacu V, et al. OGC and Grid Interoperability in enviroGRIDS Project[J]. EGU General Assembly 2010, held 2-7 May,2010 in Vienna, Austria, p.13457.2010,12:13457.
    [96]方金云,何建邦.网格GIS体系结构及其实现技术[J].地球信息科学.2002(4):36-42.
    [97]骆剑承,周成虎,蔡少华,等.基于中间件技术的网格GIS体系结构[J].地球信息科学.2002(3).
    [98]蔡少华,骆剑承,陈秋晓,等.网格GIS中的GML语言技术与设计框架[J].地球信息科学.2003(3):47-50.
    [99]沈占锋,骆剑承,蔡少华,等.网格GIS的应用架构及关键技术[J].地球信息科学.2003(4):57-62.
    [100]冯宪澄,蔡家楣,王卫红,等.GML在网格GIS中的应用研究[J].计算机工程.2004(10):49-50.
    [101]Gml O. Geography Markup Language (GML) 3.0 Implementation Specification[J]. OpenGIS Consortium.2003.
    [102]刘建英,徐爱萍.网格GIS中空间信息描述语言的研究[J].科技导报.2006(6):45-47.
    [103]黄舟.网格环境下空间计算任务处理技术研究[D].北京大学,2009.
    [104]陈占龙,吴洁,谢忠,等.分布式空间信息的对等协同计算机制研究[J].计算机应用研究.2008,25(7):2060-2063,2070.
    [105]董鹏.分布式空间信息的高效查询与分析系统研究[D].中国科学院遥感应用研究所,2003.
    [106]林志勇,孟令奎,李雯静.基与多智能体的空间信息协同分析研究[J].计算机工程与应用.2007,43(12):13-16.
    [107]朱军.虚拟地理环境中基于多Agent的数据和计算协同研究[D].中国科学院遥感应用研究所,2006.
    [108]李姗姗.空间信息分布式协同高性能计算框架的初步研究[D].中国地质大学(北京),2009.
    [109]高劲松,张文,关泽群,等.基于虚拟SAN的网格GIs数据存储技术研究[J].武汉大学学报(信息科学版).2005(3):214-217.
    [110]孙庆辉,骆剑承,赵军喜.网格GIS数据传输机制与策略[J].地球信息科学.2005(1):65-70.
    [111]谢忠俍.基于网格的GIs空间数据库集成实验研究[J].福建电脑.2011(5):78-79.
    [112]陈红英,杨宜民,李卫华.网格GIS信息服务系统的研究与实现[J].计算机工程.2006(13):260-262.
    [113]孟令奎,张文,Wang Frank Zhigang.基于层次化P2P协议的网格空间数据库系统模型[J].武汉大学学报(信息科学版).2008(12):1233-1236.
    [114]Zhou H, Yu F, Bin C, et al. Development of a Grid GIS Prototype for Geospatial Data Integration[C]. Grid and Cooperative Computing,2008. GCC'08. Seventh International Conference on. 2008:628-631
    [115]Yong Z, Yu F, Bin C, et al. A New Grid GIS Prototype for Vector Geospatial Data[C]. Grid and Cooperative Computing,2009. GCC'09. Eighth Internationa] Conference on.2009:367-372
    [116]蔡正林,韩金华,李梦琪.网格GIS体系结构研究及应用[J].计算机技术与发展.2006(7):221-223.
    [117]Aydin G, Sayar A, Gadgil H, et al. Building and applying geographical information system Grids[J]. Concurrency and Computation:Practice and Experience.2008,20(14):1653-1695.
    [118]Chang G S, Tsai W F, Lin F P, et al. A GEO Grid implementation for 3D GIS Taiwan[C]. Proceedings of the 20089th IEEE/ACM International Conference on Grid Computing. IEEE Computer Society,2008.
    [119]Di L, Chen A, Yang W, et al. The development of a geospatial data Grid by integrating OGC Web services with Globus-based Grid technology[J]. Concurrency and Computation:Practice and Experience.2008,20(14):1617-1635.
    [120]Wang S, Cowles M K, Armstrong M P. Grid computing of spatial statistics:using the TeraGrid for G i*(d) analysis[J]. Concurrency and Computation:Practice and Experience.2008,20(14): 1697-1720.
    [121]Comito C, Gounaris A, Sakellariou R, et al. A service-oriented system for distributed data querying and integration on Grids[J]. Future Generation Computer Systems.2009,25(5):511-524.
    [122]Dai Y S, Levitin G, Wang X. Optimal task partition and distribution in grid service system with common cause failures[J]. Future Generation Computer Systems.2007,23(2):209-218.
    [123]Wang S, Armstrong M P.A quadtree approach to domain decomposition for spatial interpolation in grid computing environments[J]. Parallel Computing.2003,29(10):1481-1504.
    [124]Matsumura Y, Oiso M, Matsuda M, et al. Application of Grid Task Scheduling Algorithm RR to Medium-Grained Evolution Strategies[C]. Natural Computation,2007. ICNC 2007. Third International Conference on. IEEE,2007.
    [125]Priya S B, Prakash M, Dhawan K K. Fault tolerance-genetic algorithm for grid task scheduling using check point[C]. Grid and Cooperative Computing,2007. GCC 2007. Sixth International Conference on. IEEE,2007.
    [126]李谷君,刘中伟.空间信息网格技术的发展和方向探讨[J].国土资源信息化.2009(1):61-65.
    [127]陈娟,王立挺.基于网格GIS的数字区域水资源监控管理系统研究[J].海峡科学.201 1(8):22-25.
    [128]王磊,史明昌,雷章.基于网格GIS探讨数字流域平台构建[J].水电能源科学.2010(2):65-68.
    [129]徐龙琴,刘双印,肖来胜,等.网格GIS及其在粤西数字海洋中的应用研究[J].电脑开发与应用.2007(7):16-18.
    [130]谢绍锋,肖化顺.面向数据服务与计算服务的林业空间信息网格技术[J].中南林业科技大学学报.2011(10):1565-1566.
    [131]刘强,程博艳.西南资源环境空间信息网格研究[J].测绘科学.2007(5):11-15.
    [132]Kouyoumjian V. The New Age of Cloud Computing and GIS[R].,2010.
    [133]李少丹.“云GIS”的发展趋势分析[J].电脑知识与技术.2011(16):3824-3826.
    [134]李水英.基于云计算的地理空间信息公共服务平台建设构想[J].数字技术与应用.2011(8):233-236.
    [135]周红伟,李琦.基于云计算的空间信息服务系统研究[J].计算机应用研究.2011(7):2586-2588.
    [136]武云龙,王思勇,李新楼.基于云计算的遥感数据处理模型的设计与实现[J].电脑知识与技术.2010(14):3646-3648.
    [137]Hollingsworth D. Workflow management coalition:The workflow reference model[J]. Document Number TC00-1003.1995(1.1).
    [138]Soonwook H, Kesselman C. Grid workflow:a flexible failure handling framework for the grid[C]. High Performance Distributed Computing,2003. Proceedings.12th IEEE International Symposium on. 2003.
    [139]Van der Aalst W, Van Hee K M. Workflow management:models, methods, and systems[M]. The MIT press,2004.
    [140]王宏艳.基于Petri网的煤城网格工作流模型[J].煤炭技术.2011(4):252-253.
    [141]杨浩澜,李华,李世畅,等.智能公交系统中动态网格工作流模型研究[J].计算机科学.2010(1):130-132.
    [142]金海,王述振.一种基于有色Petri网的网格工作流模型[J].华中科技大学学报(自然科学版).2006(7):39-41.
    [143]孙妍姑.基于Petri网的网格工作流建模与优化[J].淮南师范学院学报.2011(4):80-82.
    [144]顾丽,李玲,乔佩利.基于扩展型工作流网的网格工作流模型研究[J].信息技术.2009(5):160-163.
    [145]Krishnan S, Wagstrom P, Von Laszewski G. GSFL:A workflow framework for grid services[J]. Preprint ANL/MCS-P980-0802, Argonne National Laboratory.2002,9700.
    [146]Fahringer T, Qin J, Hainzer S. Specification of grid workflow applications with AGWL:an Abstract Grid Workflow Language[C]. Cluster Computing and the Grid,2005. CCGrid 2005. IEEE International Symposium on. IEEE,2005.
    [147]Bivens H P. Grid workflow[J]. Grid Computing Environments Working Group Document.2001: 757-768.
    [148]李春泉,杨宝业,王彦伟.制造网格工作流任务调度技术[J].机械设计与制造.2011(8):264-266.
    [149]张敏,余青松,黄俊,等.基于GAPSO混合算法的网格工作流调度研究[J].计算机应用与软件.2011,28(4):236-238,241.
    [150]单冬红,杨照峰.基于遗传算法负载均衡的网格工作流技术研究[J].计算机与数字工程.2011(10):81-84,100.
    [151]李迪,黄德才.基于免疫遗传算法的网格工作流服务选择[J].浙江工业大学学报.2010,38(6):673-678.
    [152]郑秋新,蒋秀凤.基于GA-SA算法的网格工作流调度[J].计算机与现代化.2009(3):66-69.
    [153]李迪.基于QoS的网格工作流调度模型和算法研究[D].浙江工业大学,2010.
    [154]李金忠.QoS优化的网格工作流调度算法研究[D].广西大学,2009.
    [155]姚磊,戴冠中,张慧翔,等.QoS约束下基于双向分层的网格工作流调度算法[J].计算机科学.2009,36(9):24-27.
    [156]李金忠,夏洁武,曾劲涛,等.多QoS约束的双目标最优的网格工作流调度研究[J].计算机应用研究.2009,26(9):3472-3474.
    [157]余小永,牛建强,徐帅彬.基于QoS的网格工作流的选择调度算法[J].通信技术.2009,42(7):220-221,235.
    [158]Amin K, Von Laszewski G, Hategan M, et al. Gridant:A client-controllable grid workflow system[C]. System Sciences,2004. Proceedings of the 37th Annual Hawaii International Conference on. IEEE,2004.
    [159]Deelman E, Singh G, Su M H, et al. Pegasus:A framework for mapping complex scientific workflows onto distributed systems[J]. Scientific Programming.2005,13(3):219-237.
    [160]Cao J, Jarvis S A, Saini S, et al. Gridflow:Workflow management for grid computing[C]. Cluster Computing and the Grid,2003. Proceedings. CCGrid 2003.3rd IEEE/ACM International Symposium on. IEEE,2003.
    [161]Ludascher B, Altintas I, Berkley C, et al. Scientific workflow management and the Kepler system[J]. Concurrency and Computation:Practice and Experience.2006,18(10):1039-1065.
    [162]高勇,刘瑜,邬伦.基于Petri网的空间信息工作流模型[J].计算机工程.2005,31(16):1-3.
    [163]杨宁,杨明祥.水利网格工作流管理系统及其在水污染事件中的应用[J].现代电子技术.2011(5):203-206.
    [164]郭昂,武永卫,田金兰,等.面向生物信息学计算的网格工作流系统[J].华中科技大学学报(白然科学版).2006:130-133.
    [165]周超,孙海龙,胡春明,等.面向生物信息的网格工作流开发与运行环境[J].计算机科学与探索.2010(3):275-282.
    [166]别晓峰,岳秀清,朱松岩.基于服务网格工作流技术的联合作战实验平台[J].指挥控制与仿真.2009(2):70-73.
    [167]张富,周进.网格空间信息工作流研究[J].华北水利水电学院学报.201 1(5):27-30.
    [168]汤双权,金可音,余青,等.工作流过程模型研究[J].计算机技术与发展.2007(12):44-47.
    [169]龚强,龚天卓.地理空间信息网格中坚件功能设计与组件模型[J].地理信息世界.2008(04).
    [170]Foster I, Kesselman C, Nick J M, et al. Grid services for distributed system integration[J]. Computer.2002,35(6):37-46.
    [171]Aijun C, Liping D, Yaxing W, et al. Grid-enabled Standard-compliant Open Computing Environment for Earth Science Exploration and Applications[C]. Geoscience and Remote Sensing Symposium,2006. IGARSS 2006. IEEE International Conference on.2006:237-240
    [172]Liping D. Customizable virtual geospatial products at web/grid service environment[C]. Geoscience and Remote Sensing Symposium,2005. IGARSS'05. Proceedings.2005 IEEE International.2005:4215-4218
    [173]Goodenough D G, Hao C, Liping D, et al. Grid-enabled OGC environment for EO data and services in support of Canada's forest applications[C]. Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International.2007:4773-4776
    [174]万林.中间件技术在Grid GIS中的应用研究[J].软件导刊.2007(23):61-63.
    [175]Humphrey M, Wasson G. Architectural foundations of WSRF.NET[J]. International Journal of Web Services Research.2005,2(3):83-97.
    [176]Codd E F. A relational model of data for large shared data banks[J]. Commun. ACM.1970,13(6): 377-387.
    [177]Codd E F. Relational database:a practical foundation for productivity[J]. Commun. ACM.1982, 25(2):109-117.
    [178]Reuter A, Gray J. Transaction processing:concepts and techniques[M]. San Mateo, Calif.: Morgan Kaufmann Publishers,1993:1070.
    [179]Tiirker C, Gertz M. Semantic integrity support in SQL:1999 and commercial (object-)relational database management systems[J]. The VLDB Journal.2001,10(4):241.
    [180]Hunt P, Konar M, Junqueira F P, et al. ZooKeeper:wait-free coordination for internet-scale systems[C]. Boston, MA:Proceedings of the 2010 USENIX conference on USENIX annual technical conference. USENIX Association,2010.
    [181]Wang G, Li G, Zhao Y, et al. Development of database grid service based on GDT[C]. Jilin, China:2011 International Conference on Mechatronic Science, Electric Engineering and Computer, MEC 2011, August 19,2011-August 22,2011. IEEE Computer Society,2011.
    [182]邵晓艳,刘宁.基于G1S海量数据的网格空间索引技术[J].科技风.2009(22):260-262.
    [183]刘润涛,郝忠孝.一种极小化交叠空间数据索引结构[J].哈尔滨工程大学学报.2009(8):909-912.
    [184]刘文闳,熊伟,吴烨,等.空间索引并行批量加载算法研究[J].现代电子技术.2011(22):90-94.
    [185]李灿辉.基于内存数据库的空件索引结构CSR树性能研究[J].数字技术与应用.2011(9):128.
    [186]熊才权,马乐乐,孙贤斌.空间索引技术研究[J].计算机技术与发展.2010(10):219-223.
    [187]龚俊,柯胜男,鲍曙明.一种全新的R树节点选择算法[J].计算机应用研究.2008(10):2946-2948.
    [188]陈敏,王晶海.R*-树空间索引的优化研究[J].计算机应用.2007(10):2581-2583.
    [189]赵园春,李成名,赵春宇.基于R树的分布式并行空间索引机制研究[J].地理与地理信息科学.2007(6):38-41.
    [190]徐少平,徐少文,罗洁.XBR树:一种基于四叉树的空间对象移动路径索引结构[J].现代计算机(专业版).2005(6):9-12.
    [191]黄明,陈哲.基于改进QR-树的空间数据索引的研究[J].黑龙江工程学院学报.2005(3):18-20.
    [192]刘苏波,朱建冲,徐海珠.基于工作流管理的资源调度模型[J].火力与指挥控制.2011(4):126-130.
    [193]张宁.余霏.分布式工作流技术研究综述[J].贵州大学学报(白然科学版).2008(1):84-87.
    [194]王晓华,赵正德,石秀丽.网格协同工作流模型的研究与实现[J].计算机工程与设计.2006(12):2234-2237.
    [195]杨波,严坤,姜劲松,等.面向Web服务架构的协同工作流模型[J].计算机工程与设计.2011(3):927-930.
    [196]张毅,李国卿,赵军喜,等.插件式GIS应用框架关键技术研究[J].测绘科学技术学报.2010(4):298-301.
    [197]Inmon W H. Building the data warehouse[M].4th ed. ed. Indianapolis, Ind.:Wiley,2005:543.
    [198]肖志超,叶华平,何世彬.空间数据仓库技术及其建模研究[J].中国储运.2010(10):92-94.
    [199]葛凡,祝玉华.空间数据仓库综述[J].许昌学院学报.2010(2):81-83.
    [200]万波,杨林.数据中心:GIS功能仓库的关键技术[J].地球科学(中国地质大学学报).2010(3):357-361.
    [201]吴信才.数据中心集成开发技术:新一代GIS架构技术与开发模式[J].地球科学(中国地质大学学报).2009(3):540-546.
    [202]胡茂胜.基于数据中心模式的分布式异构空间数据无缝集成技术研究[D].中国地质大学(武汉),2009.
    [203]Salimifard K, Wright M. Petri net-based modelling of workflow systems:An overview[J]. European Journal of Operational Research.2001,134(3):664-676.
    [204]Peterson J L. Petri net theory and the modeling of systems[M]. Englewood Cliffs, N.J.: Prentice-Hall,1981:290.
    [205]Liu D, Wang J, Chan S C F, et al. Modeling workflow processes with colored Petri nets[J]. Computers in Industry.2002,49(3):267-281.
    [206]Zhuge H, Cheung T, Pung H. A timed workflow process model[J]. Journal of Systems and Software.2001,55(3):231-243.
    [207]Tolosana-Calasanz R, Banares J A, alvarez P, et al. An uncoordinated asynchronous checkpointing model for hierarchical scientific workflows[J]. Journal of Computer and System Sciences.2010,76(6):403-415.
    [208]金莹,丁峰.广义随机Petri网在工作流建模中的应用研究[J].安庆师范学院学报(自然科学版).2010(1):26-29.
    [209]黄园媛,高春鸣.基于活动网络图的工作流过程定义工具的研究[J].计算机工程与应用.2006(2):48-51.
    [210]梁玲,孔令德.基于活动网络图的柔性工作流系统的设计与实现[J].太原科技大学学报.2007(1):19-23.
    [211]徐俊霞,沙砾,赵霁.基于活动网络图工作流过程模型的设计[J].电脑知识与技术(学术交流).2007(8):464-466.
    [212]刘军,汤晓安,干哲,等.基于活动网络图的工作流模型研究[J].微计算机信息.2009(9):9-11.
    [213]周昌盛,金恭华,倪永军,等.基于活动网络图的面向扩展的工作流过程模型[J].机电工程.2010(2):24-27.
    [214]黄磊.基于活动网络图的模具协同制造模型研究[J].广西轻工业.2011(11):36-37.
    [215]Elmaghraby S E. Activity networks:project planning and control by network models[M]. New York:Wiley,1977:443.
    [216]Cho H, Jung M, Kim M. Enabling technologies of agile manufacturing and its related activities in Korea[J]. Computers and Industrial Engineering.1996,30(3):323-334.
    [217]Frayret J, D Amours S, Montreuil B, et al. A network approach to operate agile manufacturing systems[J]. International Journal of Production Economics.2001,74(1-3):239-259.
    [218]吕霞,刘畅,耿燕婷,等.中国地质调查信息网格平台构建和地质图数据服务的实现[J].地质通报.2011(9):1462-1472.

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