基于计算经济的网格资源管理研究
|
摘要
使用经济理论和方法解决网格资源调度问题，是当前网格研究的重点和热点。其内容涉及基本的经济模型(主要是拍卖和自由竞争)、信任问题、安全问题、监测、控制、记账和支付等几个方面。就当前的研究情况，从内容涵盖的范围看，还不能满足一个独立运行的基本经济要素，如评价、稳定性控制、契约等就没有涉及；从研究的深度看，研究内容还停留在基本的原理性试验阶段，不能满足实际需要，也不够“经济化”。因此，有更多的研究和试验工作尚有待于进一步深入、全面的开展。本文以自由竞争模型为基础，对其中的信任、价格、资源调度中的优化等问题进行了深入的探讨，主要研究工作包括以下几个方面：
1．提出了受约束的竞争经济模型(Restricted Commodity Market Model，RCMM)。该模型基于自由竞争理论，以实体间相互信任为基础、以时间和预算来约束资源调度，从而保证调度的有效性和稳定性。针对该模型，以多代理系统(Multi Agent System，MAS)描述其组成结构。
2．提出了以独立第三方的方式对实体，即资源、网格服务消费者(Grid Services Consumer，GSC)和网格服务提供者(Grid Services Provider，GSP)，进行可信任评价的方法，其评价结果形成实体在RCMM中的可信任基础，最终构成选择资源的依据。其内容包括资源信任度、GSC和GSP信誉度的概念和相应的计算方法；信誉度评价算法；以信誉度为依据的资源选择算法；评价体系结构；等等。
3．提出了以Ramsey定价为基础的最高限价策略来实现价格管制，以保证价格的平稳性。在价格协商中，实现了RCMM中的T(?)tonnement过程，加速协商，减小开销。
4．针对资源选择优化，定义了网格距离及其计算方法，提出了以网格距离为依据的优化算法；描述了局部性特征，给出了局部调度算法：设计了资源绑定的结构及绑定描述。以此为基础，提出了绑定调度算法；结合上述三种优化思想，制定了RCMM中的优化策略。
5．在RCMM中，提出了契约模型，实现了以契约为基础的资源调度管理，以支撑RCMM的经济特征。
6．提出了RCMM的监测结构和评价方法。它不仅能按照传统方法采集资源所在系统中的RUR信息，而且可全面采集任务队列、资源目录等基础设施的信息，因而在为性能评估、错误发现、恢复、容错、以及预测等提供基本支持的同时，还能为市场中的价格、供求关系、信誉度评价等提供数据。
Employing economic approaches to tackle resource scheduling is a hot spot inthe grid technology, which involves various contents including economic model(such as auction and free competition), trust, security, monitoring, control, tally,payment, and so on. Current though, the state of art in the grid resource schedulingis far behind other grid research areas. No economic element that supports multiplecriteria including evaluation, stable control, contract and so forth is proposed in therelated works. And most results achieved in the related projects are still atexperiment stage, which can not satisfy the practical requirements. Trying to solvethese intractable problems needs, this dissertation adopts the free competition modelas the basis, discusses the resource scheduling problems including trust, price andscheduling optimization in detail. The main contributions of this dissertation are asfollows:
1. The theoretical hypothesis of the RCMM(Restricted Commodity MarketModel) model is proposed. Based on the free competition model and trustbetween entities, the resource scheduling according to the time andbudget is constrained in the RCMM model. And the architecture of RCMMmodel is composed by the multiple agent; systems.
2. Trust evaluation of the entities that contain resource, GSC andGSP is performed by the independent third party organization. Accordingto this approach, the trust basis between entities and the selectioncriteria of resource scheduling are formed, including concepts ofresource trust, GSC(Grid Services Consumer) credit, GSP(Grid ServicesProvider) credit and their calculation formulas, credit evaluationalgorithm, resource selection algorithm based on credit, evaluationarchitecture.
3. T(?)tonnement price negotiation process is implemented in the RCMMmodel. And a highest price fixing approach based on the Ramsey pricetheory to carry out price controlling is firstly presented, which guarantees the stability of price.
4. Aiming at optimization of resource selection, the concept of griddistance and its computation method is defined, then the optimizationalgorithm based on grid distance is introduced. The local schedulingalgorithm is presented according to the description of localcharacteristics. A binding scheduling algorithm is given according tothe definition and structure of resource binding. The whole optimizationstrategy is composed by the three optimization approaches above.
5. The contract-based resource scheduling management that definesthe structure and transition process of the contracts is proposed in theRCMM model, which underpins the economic features of the RCMM model.
6. The monitoring and evaluation system of the RCMM model is implemented.Information, not only RUR data of the sub-system where the resource reside, butalso infrastructure data including task queue and resource directory, can be gatheredby this system. Based on the information, performance evaluation, defect detection,recovery, fault-tolerant and prediction can be supported, besides data of marketprice, supply and demand relation, credit evaluation can be provided.
1．提出了受约束的竞争经济模型(Restricted Commodity Market Model，RCMM)。该模型基于自由竞争理论，以实体间相互信任为基础、以时间和预算来约束资源调度，从而保证调度的有效性和稳定性。针对该模型，以多代理系统(Multi Agent System，MAS)描述其组成结构。
2．提出了以独立第三方的方式对实体，即资源、网格服务消费者(Grid Services Consumer，GSC)和网格服务提供者(Grid Services Provider，GSP)，进行可信任评价的方法，其评价结果形成实体在RCMM中的可信任基础，最终构成选择资源的依据。其内容包括资源信任度、GSC和GSP信誉度的概念和相应的计算方法；信誉度评价算法；以信誉度为依据的资源选择算法；评价体系结构；等等。
3．提出了以Ramsey定价为基础的最高限价策略来实现价格管制，以保证价格的平稳性。在价格协商中，实现了RCMM中的T(?)tonnement过程，加速协商，减小开销。
4．针对资源选择优化，定义了网格距离及其计算方法，提出了以网格距离为依据的优化算法；描述了局部性特征，给出了局部调度算法：设计了资源绑定的结构及绑定描述。以此为基础，提出了绑定调度算法；结合上述三种优化思想，制定了RCMM中的优化策略。
5．在RCMM中，提出了契约模型，实现了以契约为基础的资源调度管理，以支撑RCMM的经济特征。
6．提出了RCMM的监测结构和评价方法。它不仅能按照传统方法采集资源所在系统中的RUR信息，而且可全面采集任务队列、资源目录等基础设施的信息，因而在为性能评估、错误发现、恢复、容错、以及预测等提供基本支持的同时，还能为市场中的价格、供求关系、信誉度评价等提供数据。
Employing economic approaches to tackle resource scheduling is a hot spot inthe grid technology, which involves various contents including economic model(such as auction and free competition), trust, security, monitoring, control, tally,payment, and so on. Current though, the state of art in the grid resource schedulingis far behind other grid research areas. No economic element that supports multiplecriteria including evaluation, stable control, contract and so forth is proposed in therelated works. And most results achieved in the related projects are still atexperiment stage, which can not satisfy the practical requirements. Trying to solvethese intractable problems needs, this dissertation adopts the free competition modelas the basis, discusses the resource scheduling problems including trust, price andscheduling optimization in detail. The main contributions of this dissertation are asfollows:
1. The theoretical hypothesis of the RCMM(Restricted Commodity MarketModel) model is proposed. Based on the free competition model and trustbetween entities, the resource scheduling according to the time andbudget is constrained in the RCMM model. And the architecture of RCMMmodel is composed by the multiple agent; systems.
2. Trust evaluation of the entities that contain resource, GSC andGSP is performed by the independent third party organization. Accordingto this approach, the trust basis between entities and the selectioncriteria of resource scheduling are formed, including concepts ofresource trust, GSC(Grid Services Consumer) credit, GSP(Grid ServicesProvider) credit and their calculation formulas, credit evaluationalgorithm, resource selection algorithm based on credit, evaluationarchitecture.
3. T(?)tonnement price negotiation process is implemented in the RCMMmodel. And a highest price fixing approach based on the Ramsey pricetheory to carry out price controlling is firstly presented, which guarantees the stability of price.
4. Aiming at optimization of resource selection, the concept of griddistance and its computation method is defined, then the optimizationalgorithm based on grid distance is introduced. The local schedulingalgorithm is presented according to the description of localcharacteristics. A binding scheduling algorithm is given according tothe definition and structure of resource binding. The whole optimizationstrategy is composed by the three optimization approaches above.
5. The contract-based resource scheduling management that definesthe structure and transition process of the contracts is proposed in theRCMM model, which underpins the economic features of the RCMM model.
6. The monitoring and evaluation system of the RCMM model is implemented.Information, not only RUR data of the sub-system where the resource reside, butalso infrastructure data including task queue and resource directory, can be gatheredby this system. Based on the information, performance evaluation, defect detection,recovery, fault-tolerant and prediction can be supported, besides data of marketprice, supply and demand relation, credit evaluation can be provided.
引文
[1] Ming Xu. Effective Internet Grid Computing for Industrial Users. Proceedings of Cluster Computing and the Grid, First IEEE/ACM International Symposium, 2001. p34.
[2] Steve Taylor, Mike Surridge, Darren Marvin. Grid Resources for Industrial Applications. Proceedings of the IEEE International Conference on Web Services(ICWS'04)-Volume 00. IEEE Computer Society, Washington, DC, USA; 2004, P. 402
[3] Jerry Rolia, Jim Pruyne, Xiaoyun Zhu, et al. Grids for Enterprise Applications. Proceedings of the 9 workshop on Job Scheduling Strategies for Parallel Programs. Seattle, June 2003, pp 129-147
[4] Chaitanya K. Survey and Taxonomy of Grid Resource Management Systems. University of Texas, Austin Technical Report, 2003 http:www.cs.utexas.edu/users/browne/cs395f2OO3/projects/KandagatlaReport.pdf.
[5] 何琨，赵勇．网格资源管理与调度研究综述，武汉理工大学学报·信息与管理工程版，第27卷第4期(总第119期)，2005年8月
[6] Karl Czajkowski, Ian Foster et al. A Resource Management Architecture for Metacomputing Systems, Proc. IPPS/SPDP'98 Workshop, on Job Scheduling Strategies for Parallel Processing, 1998, pp. 62-82.
[7] Rajkumar Buyya, David Abramson, Jonathan Giddy. Nimrod/G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid, Distributed, Parallel, and Cluster Computing ACM-class: CO Journal-ref: HPC Asia 2000, IEEE Press.
[8] Wolski, R.,Plank, J.S., Bryan, T., et al. G-commerce: market formulations controlling resource allocation on the computational grid, Parallel and Distributed Processing Symposium., Proceedings 15th International,2001, P 8.http://www.cs.utk.edu/～plank/plank/papers/IPDPS-01.html
[9] Alexander Barmouta, Rajkumar Buyya. GridBank: A Grid Accounting Services Architecture(GASA)Distributed Systems Sharing and Integration, Proceedings of the 17th Annual International Parallel and Distributed Processing Symposium (IPDPS 2003), IEEE Computer Society Press, USA, 2003, Nice, France.
[10] Ian Foster, Alain Roy. A Quality of" Service Architecture that Combines Resource Reservation and Application Adaptation, Proceedings of the Eighth International Workshop on Quality of Service, June, 2000, pp. 181-188.
[11] Det Buaklee. Near-Optimal Adaptive Control of a Large Grid Application, Proc. 16th Annual ACM Int'l. Conf. on Supercomputing(ICS 2002), New York, June 2002. pp. 315-326
[12] Robert S.Pindyck. Volatility and Commodity Price Dynamics. Journal of Futures Market, Vol. 24,. No.11, pp. 1029-1047.
[13] Bill Nitzberg, Jennifer M. Schopf. Current Activities in the Scheduling and Resource Management Area of the Global Grid Forum. JSSPP 2002, Springer-Verlag Berlin Heidelberg. LNCS 2537, 2002. pp. 229-235.
[14] Buyya R. Economic-based Distributed Resource Management and Scheduling for Grid Computing. B.E.(Mysore Univ.)and M.E.(Bangalore Univ.)doctor thesis,http://www.buyya.com
[15] 王效俐，王其藩．中国价格模型研究综述，管理工程学报，1998，12(3)：52-56
[16] Torsten Eymann, Oscar Ardaiz, Michele Catalano. Catallaxy-based Grid Markets. Multiagent and Grid. Systems, Special Issue on Smart Grid Technologies & Market Models, 1(4), 2005.
[17] 徐志伟，冯百明，李伟．网格计算技术，电子工业出版社，2o04年，第一版。
[18] B. Tierney, R. Aydt, D. Gunter, et al. A Grid Monitoring Architecture, GGF Performance Working Group, 2002, http://www-didc.lbl.gov/GGF-PERF/GMA-WG/papers/GWD-GP-16-2.pdf
[19] R. Buyya, D. Abramson, and J. Giddy, An Economy Driven Resource Management Architecture for Global Computational Power Grids, Proceedings of the 2000 International Conference on Parallel and Distributed Processing Techniques and Applications, 2000, Las Vegas, USA, CSREA Press, USA, 2000.
[20] K. Krauter, R. Buyya, and M. Maheswaran, A Taxonomy and Survey of Grid Resource Management Systems for Distributed Computing, International Journal of Software: Practice and Experience(SPE), Wiley Press, New York, USA, 2002(32). pp. 135-164
[21] F. Berman and R. Wolski, The AppLeS Project: A Status Report. Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing [C]. Britain:IEEE, 2001.pp.55-63
[22] J. Frey, T. Tannenbaum, M. Livny, I. Foster, et al. Condor-G: A Computation Management Agent for Multi-Institutional Grids, Proceedings of the Tenth International Symposium on High Performance Distributed Computing (HPDC-10), IEEE CS Press, 2001. Britain: IEEE, 2001.pp.55-63
[23] S. Fitzgerald, I. Foster, C. Kesselman, et al. A Directory Service for Configuring High-Performance Distributed Computations, Proc 6th IEEE Symp on High-Performance Distributed Computing. 1997. pp.365-375.
[24] S. Chapin, J. Karpovich, A. Grimshaw. The Legion Resource Management System, Proceedings of the 5th Workshop on Job Scheduling Strategies for Parallel Processing, San Juan, Puerto Rico, USA, Springer Verlag Press, Germany, 1999.pp.162-178
[25] R. Buyya, D. Abramson, J. Giddy. A Case for Economy Grid Architecture for Service-Oriented Grid Computing, Proceedings of the International Parallel and Distributed Processing Symposium: 10th IEEE International Heterogeneous Computing Workshop (HCW 2001), San Francisco, California, USA, IEEE CS Press, USA, 2001. pp. 4-18
[26] Rajkumar Buyya, Heinz Stockinger, Jonathan Giddy, et al.. Economic Models for Management of Resources in Grid Computing, Technical Track on Commercial Applications for High-Performance Computing, SPIE International Symposium on The Convergence of Information Technologies and Communications (ITCom 2001), August 20-24, 2001, Denver, Colorado, USA.
[27] R. Smith, R. Davis. The Contract Net Protocol: High Level Communication and Control in a Distributed Problem Solver, IEEE Transactions on Computers, Vol. C-29(12),pp.1104-1113.
[28] Yi Chi, Shoubao Yang, Zheng Feng: Grid Monitoring and Data Visualization. Proceedings of Grid and Cooperative Computing, Shanghai, China, 2003, pp.219-222.
[29] S. Smale, Dynamics in general equilibrium theory, American Economic Review, Vol. 66, No. 2, 1976, pp 284-294,
[30] Yong-Han Lee. Market-based Dy(?)mic Resource Control of Distributed Multiple Projects. The Pennsylvania State University. Department of Industrial Engineering. Thesis in. Industrial Engineering.2002.
[31] He Yanxiang, Chen Yantao, et al. Planning Management of Multiagent-Based distributed Open Computing Environment Model, Operating Systems Review, ACM Press, USA, 1998, 32(1). Pp. 57-64
[32] Azzedin I, Maheswaran M. Integrating Trust into Grid Resource Management Sys ems. In Proceedings of International Conference on Parallel Processing, Vancouver, BC, Canada, 2002, pp.47-54
[33] Rajkumar Buyya, Jonathan Giddy, David Abramson. An Evaluation of Economy-based Resource Trading and Scheduling on Computational Power Grids for Parameter Sweep Applications, The Second Worksnop on Active Middleware Services(AMS 2000), Kluwer Academic Press, Pittsburgh, USA.2000.
[34] LI MaoSheng, YANG ShouBao, FU QianFei, et al. Research on Grid Resource Reliability Model Based on Promise. ITCC(1)2005: 15. pp.310-315.
[35] Bundy A. A Concise Business Guide to Contract Law, Gower Publishing Ltd. UK, 1998.
[36] Smith, J.C. The Law of Contract, 1989, Sweet & Maxwell Ltd.
[37] A Michael Spence. Job Market Signaling. The Quarterly. Journal of Economics, 1973,Vol. 87(3).MIT Press, pp. 355-74.
[38] Henri Casanova. NetSolve: A Network Server for Solving Computational Science Problems, Journal of supercomputer Applications and High Performance Computing, 111(3): pp.212-223
[39] Serafeim Zanikolas, Rizos Sakellariou. A taxonomy of grid monitoring systems, Future Generation Computer Systems, v.21 n. 1, pp. 163-188
[40] A. C., A. Gray, L. Ma, et al. R-gma: An information integration system for grid monitoring, In Proceedings of the 10th International Conference on Cooperative Information Systems, volume 2888 of Lecture Notes in. Computer Science, Springer, 2003. pp.462-481.
[41] J. Gomoluch, M. Schroeder. Performance Evaluation of Market-based Resource Allocation for Grid Computing. Practice and Experience Concurrency Computat.: Pract. Exper. 2004: 16(5), pp.469-475.
[42] Shoukat Ali, Howard Jay Siegel. Measuring the Robustness of a Resource Allocation, IEEE Transactions on Parallel and Distributed System.Vol. 15, No. 7, July 2004, pp.,630-641
[43] Barnett, S., Cameron, RG. Introduction to Mathematical Control Theory, Clarendon Press, Oxford, 1985.4.
[44] Gurmeet Singh Manku. Balanced Binary Trees for ID Management and Load Balance in Distributed Hash Tables, PODC 2004:197-205
[45] F. Azzedin, M. Maheswaran. Evolving and Managing Trust in Grid Computing Systems, IEEE Canadian Conference on Electrical & Computer Engineering(CCECE'02), May 2002, pp. 1424-1429
[46] M. Maheswaran. Quality of Service Driven Resource Management Algorithms for Network Computing, 1999 Int'l Conference on Parallel and Distributed Processing Technologies and Applications(PDPTA'99), June 1999, pp. 1090-1096.
[47] I. Foster, C. Kesselman, G. Tsudik, et al. A security architecture for computational Grids, ACM Conference on Computers and Security, 1998, pp. 83-91.
[48] 魏利明，陈相宁．PKI技术分析，网络安全技术与应用，2005，3：19-21
[49] 北大网研：信用与中国电子商务，http://tech.sina.com.cn/i/c/2002-11-01/1124147406.shtml
[50] Blaze M, Feigenbaum J. et al. Decentralied Trust Management. Proc of 17th Symposium on Security and Privacy,IEEE CS Press, 1996, pp. 164-173
[51] Konurad K.Fuchs G.et al. Trust and Electronic Commerce more than a Technical Problem, Proceedings of the 18th IEEE Symposium on Reliable Distributed Systems, 1999, pp.360-365
[52] Kini A, Choobineh J. Trust in Electronic Commerce: Definition and Theoretical Consideration. Proc. 31. st. International Conference on System Sciences, Annual Hawaii, IEEE, 1998. pp. 51-61
[53] Zacharia, G., Moukas, A., Maes, P. Collaborative Reputation Mechanisms in Electronic Marketplaces. Decision Support Systems, December 2000, Elsevier Science, Amsterdam, Netherlands, Vol. 29(4)pp. 371-388,.
[54] Sonja Buchegger, Jean-Yves Le Boudec. A Robust Reputation System for Mobile ad hoc Networks, Proceedings of P2PEcon, Harvard University, Cambridge MA, 2004. pp.1321-1330
[55] V. Shmatikov, C. Ta'cott. Reputation-based trust management. Journal of Computer Securiy, Volume 13, Issue 1, Special issue on WITS'03, 2005,pp.167-190
[56] Zacharia, G., Maes P. Trust Management Through Reputation Mechanisms, Applied Artificial Intelligence Journal, Taylor and Francis Ltd, London, UK; ISSN: 0883-9514, 2000, Vol. 14:(9), pp. 881-908
[57] Beulah Kurian Alunkal, Ivana Veljkovic, Gregor yon Laszewski,et al. Reputation-Based Grid Resource Selection, Proceedings of the Workshop on Adaptive Grid Middleware(AGridM 2003), September 28, 2003, New Orleans LA, USA.
[58] Global Grid Forum, RUR-Resource Usage Record Working Group, http://www.gridforum.org/3 SRM/
[59] Padovan, B., Sackmann, S., Eymann, T.et al. A Prototype for an Agent-based Secure Electronic Marketplace including Reputation Tracking Mechanisms. Proceedings of the 34th Hawaiian International Conference on Systems Sciences, Outrigger Wailea Resort, Maul: IEEE Computer Society, 2001. pp. 2235-2244 http://www.hicss.hawaii.edu/HICSS 34/PDFs/INBTB06.pdf.
[60] 冷崇总．谈谈价格机制的内容，市场经济管理，1997年8月，第11卷第3期
[61] 李泊溪．经济均衡与非均衡理论，模型和应用，改革出版社，1991
[62] Bergman L. A System of Computable Genaral Equilibrium Models for Small Economy, Mathematical Modelling,1982,3(5).
[63] Drazen A. Recent Dcvelopments in Macroeconomic Disequilibrium Theory, Econometrica, 1980, 48, pp.283-306.
[64] Portes R. Macroecomomic Equilibrium and Disequilibriumin Centrally Planned Economics. Economics Inquiry, 1981; 19(Oct)
[65] Cao, H. Xiao, N. Lu, X. et al. A Market-based Approach to Allocate Resources for Computational Grids. Computer Research and Development(Chinese), Vol.39, No.8(2002)pp.913-916
[66] Wolski, R., Plank, J., Brevik, J., et al. Analyzing Market-based Resource Allocation Strategies for the Computationa. Grid. The International Journal of High Performance Computing Applications, Vol. 15, No.3(2001), pp.258-281
[67] Subramoniam, K., Maheswaran, M., toulouse, M. Towards a Micro-Economic Model for Resource Allocation in Grid Computing System. In: Proceedings of the 2002 IEEE Canadian Ccnference on Electrical & Computer Engineering, pp. 782-785
[68] Chee Shin Yeo and Rajkumar Buyya. Pricing for Utility-driven Resource Management and Allocation in Clusters, Proceedings of the 12th International Conference on Advanced Computing and Communication, 2004, Ahmedabad, India. pp.32-41
[69] Chuliang Weng, Xinda Lu, Qianni Deng. A Distributed Approach for Resource Pricing in Grid Environments. Proceeding of the Second International Workshop on Grid and Cooperative Computing 2003, pp. 620-627
[70] 翁楚良，陆鑫达．一种基于市场机制的网格资源调价算法，计算机研究与发展，第41卷第7期，2004年7月，pp．1151-1156
[71] G. Debreu. Theory of Value. Yale University Press, 1959.
[72] Michael R. Werder. Pricing in the Service-Oriented IT World. Master's Thesis in Computer Science, January 2004
[73] 袁春贤．技术商品的价格构成及其影响因素，《中国物价》，1999，11：25-27
[74] 杨叶飞．我国传统自然垄断行业价格管制的比较与改革研究．硕士学位论文，暨南大学，2003年4月
[75] Gary Biglaiser, Michael Riordan. Dynamics of price regulation, RAND Journal of Economics, vol. 31, 4, 2000,12, pp.744-767
[76] 林涛，论我国电信价格上限管制，通信世界，2005年第36期
[77] 潘茂桂，拉格朗日乘数入的意义及经济应用，重庆大学学报，1995年第3期
[78] 王瑛．测算通货膨胀率的几种方法，统计与决策，1995年第6期，42-43
[79] 王娟．通货膨胀率计算方法及西方国家控制通胀率的目标分析，浙江金融，1995年第3期
[80] 陈戈，程文文等．我国物价指数计算方法的分析与改进，华东船舶工业学院学报，1996，10(3)：87-92
[81] Weizhe Zhang, Binxing Fang, Hui He, et al. Multisite resource selection and scheduling algorithm on computational grid, Proc of the 18th Int'l Parallel and Distributed Processing Symposium. Los Alamitos, CA: IEEE Computer Society Press, 2004. pp. 105～115
[82] Xuelian Bin, Yuhai Yang, Shiyao Jin. Optimal Fixed Priority Assignment with Limited Priority Levels, LNCS 2834, Springer-Verlag. 2003, pp. 194-203.
[83] Rashmi Bajaj, Dharma P. Agrawal, Improving Scheduling of Tasks in a Heterogeneous Environment, Parallel and Distributed Systems, IEEE Transactions on, Vol. 15, No. 2.(2004), pp. 107-118.
[84] Taomas Sandholm, Subhash Suri, Andrew, Gilpin. CABOB A Fast Optimal Algorithm for Combinatorial Auctions, In International Joint Conference on Artificial Intelligence(IJCAI-01), Seattle, Washington, USA, 2001, pp. 1102-1108.
[85] Li Chunlin, Li Layuan. A Utility-based Two Level Market Solution For Optimal Resource Allocation In Computational Grid, Proc of the 2005 International Conference on Parallel Processing, 2005, pp.23-30.
[86] S. Jeong, C. Youn, H. Kim,.Optimal file replication schcme(CO-RLS)for data grids., in 6th International Conference on Advanced Communication Technology in Broadband Convergence Network Infrastructure, v 2, 2004, pp. 1055-1059.
[87] Changqin Huang, Guanghua Song, and Yao Zheng. Quality-of-Service Driven Visual Scheduling in Grid Computing, Proceedings of the GCC 2004 International Workshops, 2004, pp.744-752
[88] Siraprapa Wiriyaprasit, Veera Muangsin. The Impact of Local Priority Policies on Grid Scheduling Performance and an Adaptive Policy-based Grid Scheduling Algorithm, Proceedings of the High Performance Computing and Grid in Asia Pacific Region, Seventh International Conference on 2004, Volume 00, pp.343-346
[89] Yang-Suk Kee, D. Logothetis, R. Huang, et al. Efficient resource description and high quality selection for virtual grids. Proceedings of the 5th IEEE Symposium on Cluster Computing and the Grid, 2004, pp.598-606.
[90] 刘敏，李忠诚，石晶林，马建．IPv6网络中基于优先级的可用带宽测量方法，计算机研究与发展，2004，41(8)：1361-1367
[91] RFC-0112 Bundle Repository, OGSi Alliance, http://bundles.osgi.org,February 23, 2006
[92] David C. Parkes. iBundle: An Efficient Ascending Price Bundle Auction, Proc.ACM Conference on Electronic Commerce(EC-99), Denver, November 1999, pp.148-157,
[93] Dmitri A. Dolgov, Edmund H. Durfee. Computationally-efficient combinatorial auctions for resource allocation in weakly-coupled MDPs. AAMAS 2005, pp. 657-664.
[94] Parkes, D.C., Ungar, L.H. Iterative combinatorial auctions: theory and practice. In Proc. 17th National Conference on Artificial Intelligence, 2000, pp.74-81
[95] Wurman, P. R., We(?)lman, M. P. Equilibrium prices in bundle auctions. In Proc. AAAI-99 Workshop on Artificial Intelligence for Electronic Commerce, 1999, pp. 56-61.
[96] Shand B. Bacon J. Policies in Accountable Contracts. Proceedings of the 3rd International Workshop on Policies for Distributed Systems and Networks, California, USA, 2002, pp. 80-91
[97] Rajkumar Buyya, Manzur Murshed, David Abramson. A Deadline and Budget Constrained Cost-Time Optimisation Algorithm for Scheduling Task Farming Applications on Global Grids. Proc. of the 2002 International Conference on Parallel and Distributed Processing Techniques and Applications, Las Vegas, USA. 2002, pp.602-609
[98]Ian Foster. The Globus toolkit for Grid Computing. First IEEE/ACM International Symposium on Cluster Comput- ing and the Grid, 2004, P. 2 http://www.globus.org,
[99]FosterC. Kesselman et al. The anatomy of the grid: enabling scalable virtual organizations. International Journal of High Performance Computing Applications, 2001, 15(3), pp.200-222.
[100] Stefan Saroiu, Krishna Gummadi P et al. Exploring the design space of distributed and peer-to-peer systems: comparing the Web, TRIAD, and chord/cFs. Stefan SAROIU, P KRISHNA GUMMADI, Steven D GRIBBLE Lecture notes in computer science, Springer, 2002, pp.214-224,
[101] Jetspeed. http: //portals.apache.org/Jetspeed-2
[102] Ken'ichiro Shirose, Satoshi Matsuoka, Hidemoto Nakada, Hirotaka Ogawa, Autonomous Configuration of Grid Monitoring Systems, Proceedings of the 2004 International Symposium on Applications and the Internet (SAINT 2004 Workshops), 2004, pp. 651-657
[103] Ni Guangbao, Ma Jie, Li Bo. GridView. A Dynamic and Visual Grid Monitoring System, In Proc. of the 7th international Conterence on High Performance Computing and Grid in Asia Pacific Region, Cmiya Sonic City, Tokyo Area, Japan, 2004, pp.89-92.
[104] Catalin Dumitrescu, Ian Foster, Mike Wilde, Policy-based Resource Allocation for Virtual Organizations, GriPhyN Technical Report 2003-29.
[105] H. N. Lira Choi Keung, JRD Dyson,et al. Performance evaluation of a grid resource monitoring and discovery service, IEEE Proceedings: Software, 2003, vol. 150, pp. 243-251
[106] Marcia Zangrilli, Bruce Lowekamp, Comparing Passive Network Monitoring of Grid Application Traffic with Active Probes. GRID 2003, pp.84-93.
[107] Andrew W. Cooke, Alasdair JG Gray, Werner Nutt. Stream Integration Techniques for Grid Monitoring. J. Data Semantics 2, 2005, pp. 136-175.
[108] Pu Juhua, Xiong Zhang, Wu Zhenxing. The Research on QoS for Grid Computing. Proceedings of the IEEE International Conference on Communication Technology, 2003.
[109] Kun Yang, Xin Guo, Galis, et al, Network Engineering towards Efficient Resource on Demand in Grid Computing, Proc. of the IEEE International Conference on Communication Technology, 2003, pp. 1715～1718
[110] Chen Hongtu, Maheswaran M. Distributed Dynamic Scheduling of Composite Tasks on Grid Computing Systems. In: 16th International Parallel and Distributed Processing Symposium(IPDPS'02), 2002,pp.88-97
[111] E.Kotsovinos. Distributed resource discovery and management in XenoServers, PhD Thesis of university of CAMBRIDGE, 2002
[112] McGinnis, LF Thigpen, W. Hacker, TJ. Accounting and Accountability for Distributed and Grid Systems. Cluster Computing and the Grid 2nd IEEE/ACM International Symposium, 2002, pp.268～269.
[113] Vijay Subramani, Rajkumar Kettimuthu, Srividya Srinivasan, et al. Distributed Job Scheduling on Computational Grids Using Multiple Simultaneous Requests[C].Proceedings of the l lth IEEE International Symposium on High Performance Distributed Computing, IEEE, Los Alamitos, 2002.359-367.
[114] Csongor Somogyi, Zoltan Laszlo, Imre Szeberenyi: A Resource Accounting and Charging System in Condor Environment. Lecture Notes in Computer Science, Vol. 2700, pp. 417-420
[115] Luigi Catuogno, Pompeo Faruolo, Umberto Ferraro Petrillo, Ivan Visconti: Reliable Accounting in Grid Economic Transactions. GCC Workshops 2004, pp. 514-521
[116] M. Ould-Khaoua, S. Loucif, FA Rabhi. The Use of Economic Agents Under Price Driven Mechanism in Grid Resource Management, Article Journal of Systems Architecture, Volume 50, Issue 9, 1 September 2004, PP.521-535
[117] SHAN Jiulong, CHEN Guoliang, CHEN huaping, et al. Accounting in the Environment of Grid Society, Grid and Cooperative Computing in Lecture Notes in Computer Science, Springer, 2003, pp. 715-718.
[118] Rosario M. Piro, Andrea Guarise, Albert Werbrouck: An Economy-based Accounting Infrastructure for the DataGrid. GRID 2003, pp. 202-204.
[119] B. Chun and D. Culler. User-centric Performance Analysis of Market-based Cluster Batch Schedulers, Proceedings of 2nd IEEE International Symposium on Cluster Computing and the Grid, Berlin, 2002
[120] R. Ranjan, A. Harwood, R. Buyya. Grid Federation: An Economy Based, Scalable Distributed Resource Management System for Large-Scale Resource Coupling, Grid Computing and Distributed Systems Laboratory, University of Melbourne, Australia, 2004.
[121] Singh Munindar P. Trustworthy service composition: challenges and research questions, Lecture Notes in Computer Science,Springer-Verlag, 2003, 2631, pp.39-52.
[122] L M Camarinha-Matos. In frastructures for virtual organizations-where we are, Proceedings of IEEE Conference of Emerging Technologies and Factory Automation 2003, pp.405～414
[123] G Wasson,M Humphrey. Policy and Enforcement in Virtual Organizations, Proceedings of the Fourth International Workshop on Grid Computing(GRID' 03) , 2003, pp.125～132
[124] Jacek Gomoluch, Michael Schroeder. Performance evaluation of market-based resource allocation for Grid computing. Concurrency-Practice and Experience, 2004, 16, pp. 469-475
[125] C. A. Waldspurger, T. Hogg, B. A. Huberman, J. O. Kephart, and W. S. Stornetta. Spawn: A distributed computational economy. IEEE Trans. Software Engineering, 13(2), 1992, pp.103-117
[126] D. Abramson, R. Buyya, J. Giddy. A Computational Economy for Grid Computing and Its Implementation in the Nimrod-G Resource Broker. Future Generation Computer Systems (FGCS) Journal, 18(8), 2002, pp. 1061-1074
[127] Shoukat Ali, Anthony A. Maciejewsk, Howard Jay Siegel, Jong-Kook Kim: Measuring the Robustness of a Resource Allocation. IEEE Trans. Parallel Distrib. Syst. 15(7), 2004, pp.630-641
[128] Leonidas Georgiadis,Christos Nikolaou,et al.A fair workload allocation policy for heterogeneous systems, Journal of Parallel and Distributed Computing, 2004, 64(1), pp.507-519
[129] Tiberiu Rotaru,Hans-Heinrich Nageli.Dynamic load balancing by diffusion in heterogeneous systems, Journal of Parallel and Distributed Computing, 2004,64(4), pp.481-497
[130] Muhammad Kafil, Ishfaq Ahmad.Optimal task assignment in heterogeneous distributed computing systems[J].IEEE Concurrency on Complex Distributed Systems,1998,6(3), pp.42-51
[131] Dan Gunter, Keith Jackson, David Konerding. Essential Elements for Improved Grid Usability. The Thirteenth IEEE International Symposium on High-Performance Distributed Computing, Honolulu, http://www-library.lbl.gov/docs/LBNL/548/38/PDF/LBNL-54838_Ext_Abs.pdf.
[132] J. Hollingsworth and B. Tierney. Instrumentation and Monitoring in The Grid, Volume 2. Morgan Kaufman, 2003.
[133] Fan, M., Stallaert, J. Whinston, A. B. The Internet and the Future of Financial Markets, Communications of the ACM, 2000, 43(11), pp.82-88,
[134] J. Altmann. A Model for Resource Sharing for Internet Data Center Providers within the Grid," IEEE GECON2004, International Workshop on Grid Economics and Business Models, Seoul, South Korea, 2004, pp. 113-120
[135] R. Wolski, N. T. Spring, and J. Hayes. The Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing. Future Generation Copmuting systems, Metacomputing Issue, 1999, 15(5-6), pp.757-768
[136] M. Quinson. Dynamic Performance Forecasting for Network-Enabled Servers in a Mctacomputing Environment. In International Workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems(PMEO-PDSC2), 2002.
[137] A. Aydt, D. Gunter, W. Smith, B. et al. A Siimple Case Study of a Grid Performance system. Technical Report GWD-Perf-9-3, GGF Performance Working Group, http://www-didc.lbl.gov/GGFPERF/GMA-WG/papers/GWD-GP-9-3.pdf.
[138] R. Biswas, M. Frumkin, W. Smith, et al. Tools and Techniques for Measuring and Improving Grid Performance. In IWDC2002, LNCS 2571,,2002.pp.45-54
[139] Liang Peng, See S., Yueqin Jiang, et al. Performance evaluation in computational grid environments, Proceedings of Seventh International Conference on High Performance Computing and Grid in Asia Pacific Region, 2004
[140] Arya, S., Mount, D. M., Netanyahu, et al. An optimal algorithm for approximate nearest neighbor searching indexed dimensions. In Proc.5th ACM-SIAM Sympos. Discrete Algorithms(1994), pp. 573-582.
[141] Arya, S. Mount. Approximate nearest neighbor queries indexed dimensions. In Proc. 4th ACM-SIAM Sympos. Discrete Algorithms(1993), pp. 271-280.
[142] Clarkson, K. L. 1983. Fast algorithms for the all nearest neighbors problem. In Proc. 24th Ann. IEEE Sympos. on the Found. Comput. Sci.(1983), pp.226-232.
[143] Sunil Arya, David M. Mount, Nathan S. Netanyahu et al. An optimal algorithm for approximate nearest neighbor searching in fixed dimensions. Journal of the ACM, 1998, 45(6)pp.891-923
[144] Rich Wolski, James Plank, John Brevik, Todd Bryan. Grid Resource Allocation and Control Using Computational Economies, in Grid Computing: Making the Global Infrastructure a Reality, Berman, Fox, and Hey, eds. TJ Wiley, 2003, pp. 747-769.
[145] Rich Wolski, James S. Plank, John Brevik and Todd Bryan, "Analyzing Market-based Resource Allocation Strategies for the Computational Grid," International Journal Of High Performance Computing Applications, Sage Science Press, 2001,15(3), pp. 258-281
[146] Y.-S. Kee, D. Logothetis, R. Huang, H. Casanova, and A. Chien. Efficient resource description and high quality selection for virtual grids. Technical Report CS2004-0809, University of California, San Diego, 2004.
[147] LI C,LI L.Competitive proportional resource allocation policy for computational grid. Future Generation Computer Systems,2004.20(6), pp.1041-1054
[148] R. Wolski, J. Plank, J. Brevik, T. Bryan, Analyzing market-based resource allocation strategies for the computational grid international, J. High-perform. Comput, 2001. 15(3), pp.258.-281.
[149] Y. Amir, B. Awerbuch, R. Sean Borgstrom, A cost-benefit framework for online management of a metacomputing system, in: Proceedings of the First international Conference on Information and Computational Economy, Charleston, SC, USA, 1998.
[150] Rodrigo Real, Adenauer C. Yamin, Luciano da Silva, et al. Resource scheduling on grid: handling uncertainty. GRID 2003, pp. 205-207
[151] Hong-Jun Zhang; Qing-Hua Li. You-Lin Ruan, Resource co-allocation via agent-based coalition formation in computational grids, Proceedings of International on Conference Machine Learning and Cybernetics, 2003, Vol.3, pp. 1936-1940
[2] Steve Taylor, Mike Surridge, Darren Marvin. Grid Resources for Industrial Applications. Proceedings of the IEEE International Conference on Web Services(ICWS'04)-Volume 00. IEEE Computer Society, Washington, DC, USA; 2004, P. 402
[3] Jerry Rolia, Jim Pruyne, Xiaoyun Zhu, et al. Grids for Enterprise Applications. Proceedings of the 9 workshop on Job Scheduling Strategies for Parallel Programs. Seattle, June 2003, pp 129-147
[4] Chaitanya K. Survey and Taxonomy of Grid Resource Management Systems. University of Texas, Austin Technical Report, 2003 http:www.cs.utexas.edu/users/browne/cs395f2OO3/projects/KandagatlaReport.pdf.
[5] 何琨，赵勇．网格资源管理与调度研究综述，武汉理工大学学报·信息与管理工程版，第27卷第4期(总第119期)，2005年8月
[6] Karl Czajkowski, Ian Foster et al. A Resource Management Architecture for Metacomputing Systems, Proc. IPPS/SPDP'98 Workshop, on Job Scheduling Strategies for Parallel Processing, 1998, pp. 62-82.
[7] Rajkumar Buyya, David Abramson, Jonathan Giddy. Nimrod/G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid, Distributed, Parallel, and Cluster Computing ACM-class: CO Journal-ref: HPC Asia 2000, IEEE Press.
[8] Wolski, R.,Plank, J.S., Bryan, T., et al. G-commerce: market formulations controlling resource allocation on the computational grid, Parallel and Distributed Processing Symposium., Proceedings 15th International,2001, P 8.http://www.cs.utk.edu/～plank/plank/papers/IPDPS-01.html
[9] Alexander Barmouta, Rajkumar Buyya. GridBank: A Grid Accounting Services Architecture(GASA)Distributed Systems Sharing and Integration, Proceedings of the 17th Annual International Parallel and Distributed Processing Symposium (IPDPS 2003), IEEE Computer Society Press, USA, 2003, Nice, France.
[10] Ian Foster, Alain Roy. A Quality of" Service Architecture that Combines Resource Reservation and Application Adaptation, Proceedings of the Eighth International Workshop on Quality of Service, June, 2000, pp. 181-188.
[11] Det Buaklee. Near-Optimal Adaptive Control of a Large Grid Application, Proc. 16th Annual ACM Int'l. Conf. on Supercomputing(ICS 2002), New York, June 2002. pp. 315-326
[12] Robert S.Pindyck. Volatility and Commodity Price Dynamics. Journal of Futures Market, Vol. 24,. No.11, pp. 1029-1047.
[13] Bill Nitzberg, Jennifer M. Schopf. Current Activities in the Scheduling and Resource Management Area of the Global Grid Forum. JSSPP 2002, Springer-Verlag Berlin Heidelberg. LNCS 2537, 2002. pp. 229-235.
[14] Buyya R. Economic-based Distributed Resource Management and Scheduling for Grid Computing. B.E.(Mysore Univ.)and M.E.(Bangalore Univ.)doctor thesis,http://www.buyya.com
[15] 王效俐，王其藩．中国价格模型研究综述，管理工程学报，1998，12(3)：52-56
[16] Torsten Eymann, Oscar Ardaiz, Michele Catalano. Catallaxy-based Grid Markets. Multiagent and Grid. Systems, Special Issue on Smart Grid Technologies & Market Models, 1(4), 2005.
[17] 徐志伟，冯百明，李伟．网格计算技术，电子工业出版社，2o04年，第一版。
[18] B. Tierney, R. Aydt, D. Gunter, et al. A Grid Monitoring Architecture, GGF Performance Working Group, 2002, http://www-didc.lbl.gov/GGF-PERF/GMA-WG/papers/GWD-GP-16-2.pdf
[19] R. Buyya, D. Abramson, and J. Giddy, An Economy Driven Resource Management Architecture for Global Computational Power Grids, Proceedings of the 2000 International Conference on Parallel and Distributed Processing Techniques and Applications, 2000, Las Vegas, USA, CSREA Press, USA, 2000.
[20] K. Krauter, R. Buyya, and M. Maheswaran, A Taxonomy and Survey of Grid Resource Management Systems for Distributed Computing, International Journal of Software: Practice and Experience(SPE), Wiley Press, New York, USA, 2002(32). pp. 135-164
[21] F. Berman and R. Wolski, The AppLeS Project: A Status Report. Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing [C]. Britain:IEEE, 2001.pp.55-63
[22] J. Frey, T. Tannenbaum, M. Livny, I. Foster, et al. Condor-G: A Computation Management Agent for Multi-Institutional Grids, Proceedings of the Tenth International Symposium on High Performance Distributed Computing (HPDC-10), IEEE CS Press, 2001. Britain: IEEE, 2001.pp.55-63
[23] S. Fitzgerald, I. Foster, C. Kesselman, et al. A Directory Service for Configuring High-Performance Distributed Computations, Proc 6th IEEE Symp on High-Performance Distributed Computing. 1997. pp.365-375.
[24] S. Chapin, J. Karpovich, A. Grimshaw. The Legion Resource Management System, Proceedings of the 5th Workshop on Job Scheduling Strategies for Parallel Processing, San Juan, Puerto Rico, USA, Springer Verlag Press, Germany, 1999.pp.162-178
[25] R. Buyya, D. Abramson, J. Giddy. A Case for Economy Grid Architecture for Service-Oriented Grid Computing, Proceedings of the International Parallel and Distributed Processing Symposium: 10th IEEE International Heterogeneous Computing Workshop (HCW 2001), San Francisco, California, USA, IEEE CS Press, USA, 2001. pp. 4-18
[26] Rajkumar Buyya, Heinz Stockinger, Jonathan Giddy, et al.. Economic Models for Management of Resources in Grid Computing, Technical Track on Commercial Applications for High-Performance Computing, SPIE International Symposium on The Convergence of Information Technologies and Communications (ITCom 2001), August 20-24, 2001, Denver, Colorado, USA.
[27] R. Smith, R. Davis. The Contract Net Protocol: High Level Communication and Control in a Distributed Problem Solver, IEEE Transactions on Computers, Vol. C-29(12),pp.1104-1113.
[28] Yi Chi, Shoubao Yang, Zheng Feng: Grid Monitoring and Data Visualization. Proceedings of Grid and Cooperative Computing, Shanghai, China, 2003, pp.219-222.
[29] S. Smale, Dynamics in general equilibrium theory, American Economic Review, Vol. 66, No. 2, 1976, pp 284-294,
[30] Yong-Han Lee. Market-based Dy(?)mic Resource Control of Distributed Multiple Projects. The Pennsylvania State University. Department of Industrial Engineering. Thesis in. Industrial Engineering.2002.
[31] He Yanxiang, Chen Yantao, et al. Planning Management of Multiagent-Based distributed Open Computing Environment Model, Operating Systems Review, ACM Press, USA, 1998, 32(1). Pp. 57-64
[32] Azzedin I, Maheswaran M. Integrating Trust into Grid Resource Management Sys ems. In Proceedings of International Conference on Parallel Processing, Vancouver, BC, Canada, 2002, pp.47-54
[33] Rajkumar Buyya, Jonathan Giddy, David Abramson. An Evaluation of Economy-based Resource Trading and Scheduling on Computational Power Grids for Parameter Sweep Applications, The Second Worksnop on Active Middleware Services(AMS 2000), Kluwer Academic Press, Pittsburgh, USA.2000.
[34] LI MaoSheng, YANG ShouBao, FU QianFei, et al. Research on Grid Resource Reliability Model Based on Promise. ITCC(1)2005: 15. pp.310-315.
[35] Bundy A. A Concise Business Guide to Contract Law, Gower Publishing Ltd. UK, 1998.
[36] Smith, J.C. The Law of Contract, 1989, Sweet & Maxwell Ltd.
[37] A Michael Spence. Job Market Signaling. The Quarterly. Journal of Economics, 1973,Vol. 87(3).MIT Press, pp. 355-74.
[38] Henri Casanova. NetSolve: A Network Server for Solving Computational Science Problems, Journal of supercomputer Applications and High Performance Computing, 111(3): pp.212-223
[39] Serafeim Zanikolas, Rizos Sakellariou. A taxonomy of grid monitoring systems, Future Generation Computer Systems, v.21 n. 1, pp. 163-188
[40] A. C., A. Gray, L. Ma, et al. R-gma: An information integration system for grid monitoring, In Proceedings of the 10th International Conference on Cooperative Information Systems, volume 2888 of Lecture Notes in. Computer Science, Springer, 2003. pp.462-481.
[41] J. Gomoluch, M. Schroeder. Performance Evaluation of Market-based Resource Allocation for Grid Computing. Practice and Experience Concurrency Computat.: Pract. Exper. 2004: 16(5), pp.469-475.
[42] Shoukat Ali, Howard Jay Siegel. Measuring the Robustness of a Resource Allocation, IEEE Transactions on Parallel and Distributed System.Vol. 15, No. 7, July 2004, pp.,630-641
[43] Barnett, S., Cameron, RG. Introduction to Mathematical Control Theory, Clarendon Press, Oxford, 1985.4.
[44] Gurmeet Singh Manku. Balanced Binary Trees for ID Management and Load Balance in Distributed Hash Tables, PODC 2004:197-205
[45] F. Azzedin, M. Maheswaran. Evolving and Managing Trust in Grid Computing Systems, IEEE Canadian Conference on Electrical & Computer Engineering(CCECE'02), May 2002, pp. 1424-1429
[46] M. Maheswaran. Quality of Service Driven Resource Management Algorithms for Network Computing, 1999 Int'l Conference on Parallel and Distributed Processing Technologies and Applications(PDPTA'99), June 1999, pp. 1090-1096.
[47] I. Foster, C. Kesselman, G. Tsudik, et al. A security architecture for computational Grids, ACM Conference on Computers and Security, 1998, pp. 83-91.
[48] 魏利明，陈相宁．PKI技术分析，网络安全技术与应用，2005，3：19-21
[49] 北大网研：信用与中国电子商务，http://tech.sina.com.cn/i/c/2002-11-01/1124147406.shtml
[50] Blaze M, Feigenbaum J. et al. Decentralied Trust Management. Proc of 17th Symposium on Security and Privacy,IEEE CS Press, 1996, pp. 164-173
[51] Konurad K.Fuchs G.et al. Trust and Electronic Commerce more than a Technical Problem, Proceedings of the 18th IEEE Symposium on Reliable Distributed Systems, 1999, pp.360-365
[52] Kini A, Choobineh J. Trust in Electronic Commerce: Definition and Theoretical Consideration. Proc. 31. st. International Conference on System Sciences, Annual Hawaii, IEEE, 1998. pp. 51-61
[53] Zacharia, G., Moukas, A., Maes, P. Collaborative Reputation Mechanisms in Electronic Marketplaces. Decision Support Systems, December 2000, Elsevier Science, Amsterdam, Netherlands, Vol. 29(4)pp. 371-388,.
[54] Sonja Buchegger, Jean-Yves Le Boudec. A Robust Reputation System for Mobile ad hoc Networks, Proceedings of P2PEcon, Harvard University, Cambridge MA, 2004. pp.1321-1330
[55] V. Shmatikov, C. Ta'cott. Reputation-based trust management. Journal of Computer Securiy, Volume 13, Issue 1, Special issue on WITS'03, 2005,pp.167-190
[56] Zacharia, G., Maes P. Trust Management Through Reputation Mechanisms, Applied Artificial Intelligence Journal, Taylor and Francis Ltd, London, UK; ISSN: 0883-9514, 2000, Vol. 14:(9), pp. 881-908
[57] Beulah Kurian Alunkal, Ivana Veljkovic, Gregor yon Laszewski,et al. Reputation-Based Grid Resource Selection, Proceedings of the Workshop on Adaptive Grid Middleware(AGridM 2003), September 28, 2003, New Orleans LA, USA.
[58] Global Grid Forum, RUR-Resource Usage Record Working Group, http://www.gridforum.org/3 SRM/
[59] Padovan, B., Sackmann, S., Eymann, T.et al. A Prototype for an Agent-based Secure Electronic Marketplace including Reputation Tracking Mechanisms. Proceedings of the 34th Hawaiian International Conference on Systems Sciences, Outrigger Wailea Resort, Maul: IEEE Computer Society, 2001. pp. 2235-2244 http://www.hicss.hawaii.edu/HICSS 34/PDFs/INBTB06.pdf.
[60] 冷崇总．谈谈价格机制的内容，市场经济管理，1997年8月，第11卷第3期
[61] 李泊溪．经济均衡与非均衡理论，模型和应用，改革出版社，1991
[62] Bergman L. A System of Computable Genaral Equilibrium Models for Small Economy, Mathematical Modelling,1982,3(5).
[63] Drazen A. Recent Dcvelopments in Macroeconomic Disequilibrium Theory, Econometrica, 1980, 48, pp.283-306.
[64] Portes R. Macroecomomic Equilibrium and Disequilibriumin Centrally Planned Economics. Economics Inquiry, 1981; 19(Oct)
[65] Cao, H. Xiao, N. Lu, X. et al. A Market-based Approach to Allocate Resources for Computational Grids. Computer Research and Development(Chinese), Vol.39, No.8(2002)pp.913-916
[66] Wolski, R., Plank, J., Brevik, J., et al. Analyzing Market-based Resource Allocation Strategies for the Computationa. Grid. The International Journal of High Performance Computing Applications, Vol. 15, No.3(2001), pp.258-281
[67] Subramoniam, K., Maheswaran, M., toulouse, M. Towards a Micro-Economic Model for Resource Allocation in Grid Computing System. In: Proceedings of the 2002 IEEE Canadian Ccnference on Electrical & Computer Engineering, pp. 782-785
[68] Chee Shin Yeo and Rajkumar Buyya. Pricing for Utility-driven Resource Management and Allocation in Clusters, Proceedings of the 12th International Conference on Advanced Computing and Communication, 2004, Ahmedabad, India. pp.32-41
[69] Chuliang Weng, Xinda Lu, Qianni Deng. A Distributed Approach for Resource Pricing in Grid Environments. Proceeding of the Second International Workshop on Grid and Cooperative Computing 2003, pp. 620-627
[70] 翁楚良，陆鑫达．一种基于市场机制的网格资源调价算法，计算机研究与发展，第41卷第7期，2004年7月，pp．1151-1156
[71] G. Debreu. Theory of Value. Yale University Press, 1959.
[72] Michael R. Werder. Pricing in the Service-Oriented IT World. Master's Thesis in Computer Science, January 2004
[73] 袁春贤．技术商品的价格构成及其影响因素，《中国物价》，1999，11：25-27
[74] 杨叶飞．我国传统自然垄断行业价格管制的比较与改革研究．硕士学位论文，暨南大学，2003年4月
[75] Gary Biglaiser, Michael Riordan. Dynamics of price regulation, RAND Journal of Economics, vol. 31, 4, 2000,12, pp.744-767
[76] 林涛，论我国电信价格上限管制，通信世界，2005年第36期
[77] 潘茂桂，拉格朗日乘数入的意义及经济应用，重庆大学学报，1995年第3期
[78] 王瑛．测算通货膨胀率的几种方法，统计与决策，1995年第6期，42-43
[79] 王娟．通货膨胀率计算方法及西方国家控制通胀率的目标分析，浙江金融，1995年第3期
[80] 陈戈，程文文等．我国物价指数计算方法的分析与改进，华东船舶工业学院学报，1996，10(3)：87-92
[81] Weizhe Zhang, Binxing Fang, Hui He, et al. Multisite resource selection and scheduling algorithm on computational grid, Proc of the 18th Int'l Parallel and Distributed Processing Symposium. Los Alamitos, CA: IEEE Computer Society Press, 2004. pp. 105～115
[82] Xuelian Bin, Yuhai Yang, Shiyao Jin. Optimal Fixed Priority Assignment with Limited Priority Levels, LNCS 2834, Springer-Verlag. 2003, pp. 194-203.
[83] Rashmi Bajaj, Dharma P. Agrawal, Improving Scheduling of Tasks in a Heterogeneous Environment, Parallel and Distributed Systems, IEEE Transactions on, Vol. 15, No. 2.(2004), pp. 107-118.
[84] Taomas Sandholm, Subhash Suri, Andrew, Gilpin. CABOB A Fast Optimal Algorithm for Combinatorial Auctions, In International Joint Conference on Artificial Intelligence(IJCAI-01), Seattle, Washington, USA, 2001, pp. 1102-1108.
[85] Li Chunlin, Li Layuan. A Utility-based Two Level Market Solution For Optimal Resource Allocation In Computational Grid, Proc of the 2005 International Conference on Parallel Processing, 2005, pp.23-30.
[86] S. Jeong, C. Youn, H. Kim,.Optimal file replication schcme(CO-RLS)for data grids., in 6th International Conference on Advanced Communication Technology in Broadband Convergence Network Infrastructure, v 2, 2004, pp. 1055-1059.
[87] Changqin Huang, Guanghua Song, and Yao Zheng. Quality-of-Service Driven Visual Scheduling in Grid Computing, Proceedings of the GCC 2004 International Workshops, 2004, pp.744-752
[88] Siraprapa Wiriyaprasit, Veera Muangsin. The Impact of Local Priority Policies on Grid Scheduling Performance and an Adaptive Policy-based Grid Scheduling Algorithm, Proceedings of the High Performance Computing and Grid in Asia Pacific Region, Seventh International Conference on 2004, Volume 00, pp.343-346
[89] Yang-Suk Kee, D. Logothetis, R. Huang, et al. Efficient resource description and high quality selection for virtual grids. Proceedings of the 5th IEEE Symposium on Cluster Computing and the Grid, 2004, pp.598-606.
[90] 刘敏，李忠诚，石晶林，马建．IPv6网络中基于优先级的可用带宽测量方法，计算机研究与发展，2004，41(8)：1361-1367
[91] RFC-0112 Bundle Repository, OGSi Alliance, http://bundles.osgi.org,February 23, 2006
[92] David C. Parkes. iBundle: An Efficient Ascending Price Bundle Auction, Proc.ACM Conference on Electronic Commerce(EC-99), Denver, November 1999, pp.148-157,
[93] Dmitri A. Dolgov, Edmund H. Durfee. Computationally-efficient combinatorial auctions for resource allocation in weakly-coupled MDPs. AAMAS 2005, pp. 657-664.
[94] Parkes, D.C., Ungar, L.H. Iterative combinatorial auctions: theory and practice. In Proc. 17th National Conference on Artificial Intelligence, 2000, pp.74-81
[95] Wurman, P. R., We(?)lman, M. P. Equilibrium prices in bundle auctions. In Proc. AAAI-99 Workshop on Artificial Intelligence for Electronic Commerce, 1999, pp. 56-61.
[96] Shand B. Bacon J. Policies in Accountable Contracts. Proceedings of the 3rd International Workshop on Policies for Distributed Systems and Networks, California, USA, 2002, pp. 80-91
[97] Rajkumar Buyya, Manzur Murshed, David Abramson. A Deadline and Budget Constrained Cost-Time Optimisation Algorithm for Scheduling Task Farming Applications on Global Grids. Proc. of the 2002 International Conference on Parallel and Distributed Processing Techniques and Applications, Las Vegas, USA. 2002, pp.602-609
[98]Ian Foster. The Globus toolkit for Grid Computing. First IEEE/ACM International Symposium on Cluster Comput- ing and the Grid, 2004, P. 2 http://www.globus.org,
[99]FosterC. Kesselman et al. The anatomy of the grid: enabling scalable virtual organizations. International Journal of High Performance Computing Applications, 2001, 15(3), pp.200-222.
[100] Stefan Saroiu, Krishna Gummadi P et al. Exploring the design space of distributed and peer-to-peer systems: comparing the Web, TRIAD, and chord/cFs. Stefan SAROIU, P KRISHNA GUMMADI, Steven D GRIBBLE Lecture notes in computer science, Springer, 2002, pp.214-224,
[101] Jetspeed. http: //portals.apache.org/Jetspeed-2
[102] Ken'ichiro Shirose, Satoshi Matsuoka, Hidemoto Nakada, Hirotaka Ogawa, Autonomous Configuration of Grid Monitoring Systems, Proceedings of the 2004 International Symposium on Applications and the Internet (SAINT 2004 Workshops), 2004, pp. 651-657
[103] Ni Guangbao, Ma Jie, Li Bo. GridView. A Dynamic and Visual Grid Monitoring System, In Proc. of the 7th international Conterence on High Performance Computing and Grid in Asia Pacific Region, Cmiya Sonic City, Tokyo Area, Japan, 2004, pp.89-92.
[104] Catalin Dumitrescu, Ian Foster, Mike Wilde, Policy-based Resource Allocation for Virtual Organizations, GriPhyN Technical Report 2003-29.
[105] H. N. Lira Choi Keung, JRD Dyson,et al. Performance evaluation of a grid resource monitoring and discovery service, IEEE Proceedings: Software, 2003, vol. 150, pp. 243-251
[106] Marcia Zangrilli, Bruce Lowekamp, Comparing Passive Network Monitoring of Grid Application Traffic with Active Probes. GRID 2003, pp.84-93.
[107] Andrew W. Cooke, Alasdair JG Gray, Werner Nutt. Stream Integration Techniques for Grid Monitoring. J. Data Semantics 2, 2005, pp. 136-175.
[108] Pu Juhua, Xiong Zhang, Wu Zhenxing. The Research on QoS for Grid Computing. Proceedings of the IEEE International Conference on Communication Technology, 2003.
[109] Kun Yang, Xin Guo, Galis, et al, Network Engineering towards Efficient Resource on Demand in Grid Computing, Proc. of the IEEE International Conference on Communication Technology, 2003, pp. 1715～1718
[110] Chen Hongtu, Maheswaran M. Distributed Dynamic Scheduling of Composite Tasks on Grid Computing Systems. In: 16th International Parallel and Distributed Processing Symposium(IPDPS'02), 2002,pp.88-97
[111] E.Kotsovinos. Distributed resource discovery and management in XenoServers, PhD Thesis of university of CAMBRIDGE, 2002
[112] McGinnis, LF Thigpen, W. Hacker, TJ. Accounting and Accountability for Distributed and Grid Systems. Cluster Computing and the Grid 2nd IEEE/ACM International Symposium, 2002, pp.268～269.
[113] Vijay Subramani, Rajkumar Kettimuthu, Srividya Srinivasan, et al. Distributed Job Scheduling on Computational Grids Using Multiple Simultaneous Requests[C].Proceedings of the l lth IEEE International Symposium on High Performance Distributed Computing, IEEE, Los Alamitos, 2002.359-367.
[114] Csongor Somogyi, Zoltan Laszlo, Imre Szeberenyi: A Resource Accounting and Charging System in Condor Environment. Lecture Notes in Computer Science, Vol. 2700, pp. 417-420
[115] Luigi Catuogno, Pompeo Faruolo, Umberto Ferraro Petrillo, Ivan Visconti: Reliable Accounting in Grid Economic Transactions. GCC Workshops 2004, pp. 514-521
[116] M. Ould-Khaoua, S. Loucif, FA Rabhi. The Use of Economic Agents Under Price Driven Mechanism in Grid Resource Management, Article Journal of Systems Architecture, Volume 50, Issue 9, 1 September 2004, PP.521-535
[117] SHAN Jiulong, CHEN Guoliang, CHEN huaping, et al. Accounting in the Environment of Grid Society, Grid and Cooperative Computing in Lecture Notes in Computer Science, Springer, 2003, pp. 715-718.
[118] Rosario M. Piro, Andrea Guarise, Albert Werbrouck: An Economy-based Accounting Infrastructure for the DataGrid. GRID 2003, pp. 202-204.
[119] B. Chun and D. Culler. User-centric Performance Analysis of Market-based Cluster Batch Schedulers, Proceedings of 2nd IEEE International Symposium on Cluster Computing and the Grid, Berlin, 2002
[120] R. Ranjan, A. Harwood, R. Buyya. Grid Federation: An Economy Based, Scalable Distributed Resource Management System for Large-Scale Resource Coupling, Grid Computing and Distributed Systems Laboratory, University of Melbourne, Australia, 2004.
[121] Singh Munindar P. Trustworthy service composition: challenges and research questions, Lecture Notes in Computer Science,Springer-Verlag, 2003, 2631, pp.39-52.
[122] L M Camarinha-Matos. In frastructures for virtual organizations-where we are, Proceedings of IEEE Conference of Emerging Technologies and Factory Automation 2003, pp.405～414
[123] G Wasson,M Humphrey. Policy and Enforcement in Virtual Organizations, Proceedings of the Fourth International Workshop on Grid Computing(GRID' 03) , 2003, pp.125～132
[124] Jacek Gomoluch, Michael Schroeder. Performance evaluation of market-based resource allocation for Grid computing. Concurrency-Practice and Experience, 2004, 16, pp. 469-475
[125] C. A. Waldspurger, T. Hogg, B. A. Huberman, J. O. Kephart, and W. S. Stornetta. Spawn: A distributed computational economy. IEEE Trans. Software Engineering, 13(2), 1992, pp.103-117
[126] D. Abramson, R. Buyya, J. Giddy. A Computational Economy for Grid Computing and Its Implementation in the Nimrod-G Resource Broker. Future Generation Computer Systems (FGCS) Journal, 18(8), 2002, pp. 1061-1074
[127] Shoukat Ali, Anthony A. Maciejewsk, Howard Jay Siegel, Jong-Kook Kim: Measuring the Robustness of a Resource Allocation. IEEE Trans. Parallel Distrib. Syst. 15(7), 2004, pp.630-641
[128] Leonidas Georgiadis,Christos Nikolaou,et al.A fair workload allocation policy for heterogeneous systems, Journal of Parallel and Distributed Computing, 2004, 64(1), pp.507-519
[129] Tiberiu Rotaru,Hans-Heinrich Nageli.Dynamic load balancing by diffusion in heterogeneous systems, Journal of Parallel and Distributed Computing, 2004,64(4), pp.481-497
[130] Muhammad Kafil, Ishfaq Ahmad.Optimal task assignment in heterogeneous distributed computing systems[J].IEEE Concurrency on Complex Distributed Systems,1998,6(3), pp.42-51
[131] Dan Gunter, Keith Jackson, David Konerding. Essential Elements for Improved Grid Usability. The Thirteenth IEEE International Symposium on High-Performance Distributed Computing, Honolulu, http://www-library.lbl.gov/docs/LBNL/548/38/PDF/LBNL-54838_Ext_Abs.pdf.
[132] J. Hollingsworth and B. Tierney. Instrumentation and Monitoring in The Grid, Volume 2. Morgan Kaufman, 2003.
[133] Fan, M., Stallaert, J. Whinston, A. B. The Internet and the Future of Financial Markets, Communications of the ACM, 2000, 43(11), pp.82-88,
[134] J. Altmann. A Model for Resource Sharing for Internet Data Center Providers within the Grid," IEEE GECON2004, International Workshop on Grid Economics and Business Models, Seoul, South Korea, 2004, pp. 113-120
[135] R. Wolski, N. T. Spring, and J. Hayes. The Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing. Future Generation Copmuting systems, Metacomputing Issue, 1999, 15(5-6), pp.757-768
[136] M. Quinson. Dynamic Performance Forecasting for Network-Enabled Servers in a Mctacomputing Environment. In International Workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems(PMEO-PDSC2), 2002.
[137] A. Aydt, D. Gunter, W. Smith, B. et al. A Siimple Case Study of a Grid Performance system. Technical Report GWD-Perf-9-3, GGF Performance Working Group, http://www-didc.lbl.gov/GGFPERF/GMA-WG/papers/GWD-GP-9-3.pdf.
[138] R. Biswas, M. Frumkin, W. Smith, et al. Tools and Techniques for Measuring and Improving Grid Performance. In IWDC2002, LNCS 2571,,2002.pp.45-54
[139] Liang Peng, See S., Yueqin Jiang, et al. Performance evaluation in computational grid environments, Proceedings of Seventh International Conference on High Performance Computing and Grid in Asia Pacific Region, 2004
[140] Arya, S., Mount, D. M., Netanyahu, et al. An optimal algorithm for approximate nearest neighbor searching indexed dimensions. In Proc.5th ACM-SIAM Sympos. Discrete Algorithms(1994), pp. 573-582.
[141] Arya, S. Mount. Approximate nearest neighbor queries indexed dimensions. In Proc. 4th ACM-SIAM Sympos. Discrete Algorithms(1993), pp. 271-280.
[142] Clarkson, K. L. 1983. Fast algorithms for the all nearest neighbors problem. In Proc. 24th Ann. IEEE Sympos. on the Found. Comput. Sci.(1983), pp.226-232.
[143] Sunil Arya, David M. Mount, Nathan S. Netanyahu et al. An optimal algorithm for approximate nearest neighbor searching in fixed dimensions. Journal of the ACM, 1998, 45(6)pp.891-923
[144] Rich Wolski, James Plank, John Brevik, Todd Bryan. Grid Resource Allocation and Control Using Computational Economies, in Grid Computing: Making the Global Infrastructure a Reality, Berman, Fox, and Hey, eds. TJ Wiley, 2003, pp. 747-769.
[145] Rich Wolski, James S. Plank, John Brevik and Todd Bryan, "Analyzing Market-based Resource Allocation Strategies for the Computational Grid," International Journal Of High Performance Computing Applications, Sage Science Press, 2001,15(3), pp. 258-281
[146] Y.-S. Kee, D. Logothetis, R. Huang, H. Casanova, and A. Chien. Efficient resource description and high quality selection for virtual grids. Technical Report CS2004-0809, University of California, San Diego, 2004.
[147] LI C,LI L.Competitive proportional resource allocation policy for computational grid. Future Generation Computer Systems,2004.20(6), pp.1041-1054
[148] R. Wolski, J. Plank, J. Brevik, T. Bryan, Analyzing market-based resource allocation strategies for the computational grid international, J. High-perform. Comput, 2001. 15(3), pp.258.-281.
[149] Y. Amir, B. Awerbuch, R. Sean Borgstrom, A cost-benefit framework for online management of a metacomputing system, in: Proceedings of the First international Conference on Information and Computational Economy, Charleston, SC, USA, 1998.
[150] Rodrigo Real, Adenauer C. Yamin, Luciano da Silva, et al. Resource scheduling on grid: handling uncertainty. GRID 2003, pp. 205-207
[151] Hong-Jun Zhang; Qing-Hua Li. You-Lin Ruan, Resource co-allocation via agent-based coalition formation in computational grids, Proceedings of International on Conference Machine Learning and Cybernetics, 2003, Vol.3, pp. 1936-1940