网格市场环境下资源调度机制研究
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摘要
随着网格技术的不断发展,商业网格项目逐渐增多,网格系统逐渐从传统的免费计算资源提供者的角色转变为具有商业用途的互联网资源共享中间件,提供作为公共品的资源与服务,网格进入了网格市场的新发展阶段。网格市场是采用经济学方法进行资源管理与分配的非合作型网格,与传统的网格相比,网格市场依据其独有的激励特性鼓励众多资源提供者与资源消费者加入网格市场,为网格市场带来了丰富的资源与众多的用户,提高了网格效率,降低了社会总成本,为网格进一步发展提供了前进的动力。在国内外,作为开放网络的典型代表,网格市场成为分布式系统方向最活跃的研究领域之一。
由于网格资源交易环境与实体经济环境具有很强的相似性,网格市场资源分配与管理方法也类似于现实社会的经济活动,因此,借助现有的市场经济的管理方法可以有效的解决网格市场环境中资源调度与分配的问题,经济学方法很大程度上促进了网格市场的发展。但与此同时,网格市场资源更为异构、动态与自治的特征,以用户为中心的最优化目标也为网格市场资源调度问题提出了新的挑战。
本文围绕资源调度问题,针对网格市场环境下网格资源规模较大、异构性强、资源动态自治可用性低、用户QoS需求复杂等特征,开展了以下研究工作：
本文首先综述了网格的概念与发展历程,然后给出了网格市场的概念及其特征,并给出了网格市场的研究现状。分析了网格市场环境下网格调度面临的新问题,深入分析了由于网格市场更为异构、动态、自治的特性造成的网格市场中资源的查找效率低下、资源可用性较差以及用户QoS需求无法有效满足的问题,引出本文的研究内容。
在典型调度形式化描述的基础上,本文探讨了网格市场中资源调度的新特征,并分析了这些特征对网格市场资源调度的影响。首先介绍了调度理论的形式化描述与符号集含义；然后介绍了网格调度的分类与调度流程,最后分析了网格市场环境下作业调度与资源分配的新特征,并以此为基础展开以下的研究工作。
针对网格市场环境的分布性、动态性和资源异构性等特点,论文第三章基于超级节点的结构,提出了一种类型感知的多属性资源查找机制。该机制考虑节点资源的多样性,不拘泥于传统的节点分组,依据资源类型和属性相关性将资源划分为若干个资源分组,提高组内资源的“纯”度,提高查找的精确性。同时将资源类型作为资源分组管理节点标识的一部分,快速定位特定类型的资源分组,提高查找的效率。实验表明,该类型感知的多属性资源查找机制能够在一定程度上提高查找的精确性,有效减少查找消息的平均跳数,降低资源查找相应时间,有效降低资源查找引起的消息数,并且随着系统规模的增大,性能仍得以保持。
论文第四章提出了一种网格市场资源可用性风险评价方法,该方法可有效评价网格资源的可用性指标,为网格市场资源调度提供了全新的角度与依据。首次提出了网格资源可用性风险的概念,基于相关资源的作业历史信息,利用概率与统计的方法对资源可用性风险进行预测与评估,提出了单一网格资源与网格资源集合的可用性风险评价方法,并给出了基于资源可用性风险评价的网格调度算法。该算法可有效的确定可用资源集合,降低网格作业失效率,提高网格资源的使用效率。
论文第五章将信任机制融入网格市场,提出了一种基于信任过滤的资源选择方法。该方法利用相关信任模型对网格市场资源进行信任值计算,依据用户信任需求阈值确定信任度较高的可用资源集合；然后,对可用集合资源计算其使用价格与风险价格,计算得到各可用资源的机会成本；最后提出了基于最小机会成本的启发式资源调度算法。该方法能有效的激励供求双方,通过保证信任度高的资源提供者的总收益来激励更多的可用资源加入网格市场,同时,该方法可有效的降低用户作业的失败率,降低用户资源使用的总成本。
论文第六章提出了一种模糊决策的多维QoS的调度方法,该方法可有效解决普通用户无法提供精确QoS需求的问题,提高了用户对资源服务质量的满意度。首先给出了多维QoS网格调度的形式化描述,利用模糊决策理论有效地将用户模糊的QoS需求的映射到网格资源,利用AHP算法确定用户关于多维QoS各维度之间的权重关系,最后给出了一种模糊决策的多维QOS的调度方法。该方法在不需要用户提供精确的QoS参数前提下,有效满足用户QoS需求,具有较好的一次作业完成率,且作业完成率波动较小。
本文从网格市场资源规模较大、异构性强、资源动态自治可用性低、用户QOS需求复杂等特征呈现出的问题出发,深入分析了由于网格市场更为异构、动态、自治、面向用户的特性造成的网格市场中资源的查找效率低下、资源可用性较差与用户QoS需求无法有效满足的问题,提出了网格市场环境中基于类型感知的多属性资源查找机制,提出了网格市场环境中资源的可用性风险评价方法,提出了基于信任过滤的资源选择算法,提出了基于模糊决策的多维QoS的调度方法,为解决网格市场资源调度问题展示了全新的视角和美好的前景。
With the continuous developments of Grid technology, numbers of business Grid projects pop up dramaticaly. As a typical provider with free computing resources, Grid gradually turns into a commercial Internet resources sharing middleware, and provides resources and services as public goods. It means that Grid has already reached a new plane of development in Grid market. In Grid market, it makes full use of Economics to allocate and manage resources, which called the non-cooperative Grid. Comparing with the traditional Grid, Grid market has its own driven characteristics which encourage a number of resource providers and resource consumers to join in. It not only brings a wealth of resources and a large number of users, improves the efficiency of Grid, reduces the total cost of the community, but also provides fresh impetus for the further development of Grid. Both at home and abroad, Grid market, a typical open network representative, has become one of the most active research areas in distributed system.
The Grid resource exchanging environment is strongly similar to real economy environment. Grid resource allocation and management is similar to the real social and economic activities too. Therefore, current market mechanism and management methods can effectively solve the problems of job scheduling and resource allocation in Grid market. Economics largely promotes development of the Grid market. However, the Grid market resources are becoming more heterogeneous, dynamic and autonomous, and the optimized goal changes into customer-centric to challenge the problems of job scheduling in Grid market.
The Grid market has large scale, strong heterogeneous, dynamic, autonomous resources and complex QoS requirements of users. This dissertation focuses on job scheduling and resource allocation in Grid and does the following researches.
In this dissertation, the concept and history of Grid are introduced firstly. Then the concept and characteristics of Grid market are discussed and the status of the Grid market research is given. Main problems in job scheduling and resources allocation are analyzed. Due to the new characteristics of Grid market, such as more heterogeneous, dynamic, autonomous and customer-centric objective, we have deeply investigated the following problems which are also discussed later:low resource discovering efficacy; low resource availability; unsatisfied QoS requirements of users.
Based on the formal description of a typical scheduling, we discuss the new characteristics of scheduling problems in Grid market and analyse the effects to job scheduling and resource allocation. Chapter2 introduces the formal description and notions of scheduling, and then describes the framework of Grid scheduling. At last, the new characteristics of job scheduling and resource allocation in Grid market are discussed, which are the bases of the following researches.
Aiming at the resource instinctive characteristic of decentralized, dynamic and heterogeneous, a type-aware multi-attribute resource discovery mechanism based on super nodes is proposed in Chapter 3. Setting aside the traditional nodes partition, the mechanism treats resources as independent entities and partitioned them into several resource groups according to their types and attributes similarity. This partition approach improves the resources'purity'of a group leading to accurately searching. Type is part of the identities of resource group managers, and this makes it possible to quickly locate certain type of resource group, and leads to higher performance of resource discovery. Simulation shows that the type-aware multi-attribute resource discovery mechanism can increase the accuracy of searching to a certain extent. It can effectively decrease average hop counts, response time and messages brought by resource discovering. At the same time, the performance can be preserved when the system scales up.
An accurate evaluation method of resource availability risk is proposed in Chapter 4. It can efficiently evaluate the availability of Grid resources and provide a new point of view for job scheduling in Grid market. The concept of Grid resource availability risk is put forward first and an evaluation approach of availability risk is also proposed based on the historical traces. Based on probability theory and statistic method, we predict and evaluate the availability risk of resource, and propose an accurate evaluation method of resource availability for single resource and resources set. Besides, a Grid job scheduling algorithm based on availability risk evaluation is also proposed. Simulations show the evaluation approach can accurately select available resources set and reduce job failure rate efficiently.
By introducing trust mechanism into Grid market in Chapter 5, a trust-filtered approach for resource selection is proposed. This approach first computes the trust value of Grid market resource based on the trust model, and determines the available resource set based on users'trust requirement. Then we compute the cost and risk cost of available resources to get each opportunity cost. At last, a minimal opportunity cost algorithm is proposed. Simulations show this approach is an efficient incentive for both provider and consumer. It effectively guarantees profit of providers with more reliable resources to encourage more providers to join in Grid market. At the same time, it can efficiently reduce job failure rate and the cost of users.
A fuzzy decision based multi-QoS batch scheduling algorithm is proposed in Chapter 6. The method resolves the problem that the users could not supply accurate QoS requirements information in Grid market and meets users'QoS requirements.A formalization of multi-QoS based batch scheduling is presented first, and it maps fuzzy users'QoS requirements to resources based on fuzzy decision theory to determine the weights of multi-QoS based on AHP algorithm. A fuzzy decision based multi-QoS batch scheduling algorithm is proposed at last. Simulations show the approach can efficiently meet users'QoS requirements without accurate QoS parameters. Comparing with traditional QoS based batch scheduling algorithms; this approach has a better accomplishment ratio of one-time job and lower fluctuation.
By analyzing the characteristics of Grid market such as large-scale, heterogeneity, unreliability and customer-centric, this dissertation gives deeply analysis of the following problems, including low resource discovering efficacy; low resource availability; and unsatisfied users'QoS requirements. To solve these problems, a type-aware multi-attribute resource discovery mechanism, an accurate evaluation of resource availability risk method, a trust-filtered approach for resource selection, a fuzzy decision based multi-QoS batch scheduling algorithm are proposed in this dissertation. They give a new point of view and fine prospect for solving the problems of Grid market scheduling.
由于网格资源交易环境与实体经济环境具有很强的相似性,网格市场资源分配与管理方法也类似于现实社会的经济活动,因此,借助现有的市场经济的管理方法可以有效的解决网格市场环境中资源调度与分配的问题,经济学方法很大程度上促进了网格市场的发展。但与此同时,网格市场资源更为异构、动态与自治的特征,以用户为中心的最优化目标也为网格市场资源调度问题提出了新的挑战。
本文围绕资源调度问题,针对网格市场环境下网格资源规模较大、异构性强、资源动态自治可用性低、用户QoS需求复杂等特征,开展了以下研究工作：
本文首先综述了网格的概念与发展历程,然后给出了网格市场的概念及其特征,并给出了网格市场的研究现状。分析了网格市场环境下网格调度面临的新问题,深入分析了由于网格市场更为异构、动态、自治的特性造成的网格市场中资源的查找效率低下、资源可用性较差以及用户QoS需求无法有效满足的问题,引出本文的研究内容。
在典型调度形式化描述的基础上,本文探讨了网格市场中资源调度的新特征,并分析了这些特征对网格市场资源调度的影响。首先介绍了调度理论的形式化描述与符号集含义；然后介绍了网格调度的分类与调度流程,最后分析了网格市场环境下作业调度与资源分配的新特征,并以此为基础展开以下的研究工作。
针对网格市场环境的分布性、动态性和资源异构性等特点,论文第三章基于超级节点的结构,提出了一种类型感知的多属性资源查找机制。该机制考虑节点资源的多样性,不拘泥于传统的节点分组,依据资源类型和属性相关性将资源划分为若干个资源分组,提高组内资源的“纯”度,提高查找的精确性。同时将资源类型作为资源分组管理节点标识的一部分,快速定位特定类型的资源分组,提高查找的效率。实验表明,该类型感知的多属性资源查找机制能够在一定程度上提高查找的精确性,有效减少查找消息的平均跳数,降低资源查找相应时间,有效降低资源查找引起的消息数,并且随着系统规模的增大,性能仍得以保持。
论文第四章提出了一种网格市场资源可用性风险评价方法,该方法可有效评价网格资源的可用性指标,为网格市场资源调度提供了全新的角度与依据。首次提出了网格资源可用性风险的概念,基于相关资源的作业历史信息,利用概率与统计的方法对资源可用性风险进行预测与评估,提出了单一网格资源与网格资源集合的可用性风险评价方法,并给出了基于资源可用性风险评价的网格调度算法。该算法可有效的确定可用资源集合,降低网格作业失效率,提高网格资源的使用效率。
论文第五章将信任机制融入网格市场,提出了一种基于信任过滤的资源选择方法。该方法利用相关信任模型对网格市场资源进行信任值计算,依据用户信任需求阈值确定信任度较高的可用资源集合；然后,对可用集合资源计算其使用价格与风险价格,计算得到各可用资源的机会成本；最后提出了基于最小机会成本的启发式资源调度算法。该方法能有效的激励供求双方,通过保证信任度高的资源提供者的总收益来激励更多的可用资源加入网格市场,同时,该方法可有效的降低用户作业的失败率,降低用户资源使用的总成本。
论文第六章提出了一种模糊决策的多维QoS的调度方法,该方法可有效解决普通用户无法提供精确QoS需求的问题,提高了用户对资源服务质量的满意度。首先给出了多维QoS网格调度的形式化描述,利用模糊决策理论有效地将用户模糊的QoS需求的映射到网格资源,利用AHP算法确定用户关于多维QoS各维度之间的权重关系,最后给出了一种模糊决策的多维QOS的调度方法。该方法在不需要用户提供精确的QoS参数前提下,有效满足用户QoS需求,具有较好的一次作业完成率,且作业完成率波动较小。
本文从网格市场资源规模较大、异构性强、资源动态自治可用性低、用户QOS需求复杂等特征呈现出的问题出发,深入分析了由于网格市场更为异构、动态、自治、面向用户的特性造成的网格市场中资源的查找效率低下、资源可用性较差与用户QoS需求无法有效满足的问题,提出了网格市场环境中基于类型感知的多属性资源查找机制,提出了网格市场环境中资源的可用性风险评价方法,提出了基于信任过滤的资源选择算法,提出了基于模糊决策的多维QoS的调度方法,为解决网格市场资源调度问题展示了全新的视角和美好的前景。
With the continuous developments of Grid technology, numbers of business Grid projects pop up dramaticaly. As a typical provider with free computing resources, Grid gradually turns into a commercial Internet resources sharing middleware, and provides resources and services as public goods. It means that Grid has already reached a new plane of development in Grid market. In Grid market, it makes full use of Economics to allocate and manage resources, which called the non-cooperative Grid. Comparing with the traditional Grid, Grid market has its own driven characteristics which encourage a number of resource providers and resource consumers to join in. It not only brings a wealth of resources and a large number of users, improves the efficiency of Grid, reduces the total cost of the community, but also provides fresh impetus for the further development of Grid. Both at home and abroad, Grid market, a typical open network representative, has become one of the most active research areas in distributed system.
The Grid resource exchanging environment is strongly similar to real economy environment. Grid resource allocation and management is similar to the real social and economic activities too. Therefore, current market mechanism and management methods can effectively solve the problems of job scheduling and resource allocation in Grid market. Economics largely promotes development of the Grid market. However, the Grid market resources are becoming more heterogeneous, dynamic and autonomous, and the optimized goal changes into customer-centric to challenge the problems of job scheduling in Grid market.
The Grid market has large scale, strong heterogeneous, dynamic, autonomous resources and complex QoS requirements of users. This dissertation focuses on job scheduling and resource allocation in Grid and does the following researches.
In this dissertation, the concept and history of Grid are introduced firstly. Then the concept and characteristics of Grid market are discussed and the status of the Grid market research is given. Main problems in job scheduling and resources allocation are analyzed. Due to the new characteristics of Grid market, such as more heterogeneous, dynamic, autonomous and customer-centric objective, we have deeply investigated the following problems which are also discussed later:low resource discovering efficacy; low resource availability; unsatisfied QoS requirements of users.
Based on the formal description of a typical scheduling, we discuss the new characteristics of scheduling problems in Grid market and analyse the effects to job scheduling and resource allocation. Chapter2 introduces the formal description and notions of scheduling, and then describes the framework of Grid scheduling. At last, the new characteristics of job scheduling and resource allocation in Grid market are discussed, which are the bases of the following researches.
Aiming at the resource instinctive characteristic of decentralized, dynamic and heterogeneous, a type-aware multi-attribute resource discovery mechanism based on super nodes is proposed in Chapter 3. Setting aside the traditional nodes partition, the mechanism treats resources as independent entities and partitioned them into several resource groups according to their types and attributes similarity. This partition approach improves the resources'purity'of a group leading to accurately searching. Type is part of the identities of resource group managers, and this makes it possible to quickly locate certain type of resource group, and leads to higher performance of resource discovery. Simulation shows that the type-aware multi-attribute resource discovery mechanism can increase the accuracy of searching to a certain extent. It can effectively decrease average hop counts, response time and messages brought by resource discovering. At the same time, the performance can be preserved when the system scales up.
An accurate evaluation method of resource availability risk is proposed in Chapter 4. It can efficiently evaluate the availability of Grid resources and provide a new point of view for job scheduling in Grid market. The concept of Grid resource availability risk is put forward first and an evaluation approach of availability risk is also proposed based on the historical traces. Based on probability theory and statistic method, we predict and evaluate the availability risk of resource, and propose an accurate evaluation method of resource availability for single resource and resources set. Besides, a Grid job scheduling algorithm based on availability risk evaluation is also proposed. Simulations show the evaluation approach can accurately select available resources set and reduce job failure rate efficiently.
By introducing trust mechanism into Grid market in Chapter 5, a trust-filtered approach for resource selection is proposed. This approach first computes the trust value of Grid market resource based on the trust model, and determines the available resource set based on users'trust requirement. Then we compute the cost and risk cost of available resources to get each opportunity cost. At last, a minimal opportunity cost algorithm is proposed. Simulations show this approach is an efficient incentive for both provider and consumer. It effectively guarantees profit of providers with more reliable resources to encourage more providers to join in Grid market. At the same time, it can efficiently reduce job failure rate and the cost of users.
A fuzzy decision based multi-QoS batch scheduling algorithm is proposed in Chapter 6. The method resolves the problem that the users could not supply accurate QoS requirements information in Grid market and meets users'QoS requirements.A formalization of multi-QoS based batch scheduling is presented first, and it maps fuzzy users'QoS requirements to resources based on fuzzy decision theory to determine the weights of multi-QoS based on AHP algorithm. A fuzzy decision based multi-QoS batch scheduling algorithm is proposed at last. Simulations show the approach can efficiently meet users'QoS requirements without accurate QoS parameters. Comparing with traditional QoS based batch scheduling algorithms; this approach has a better accomplishment ratio of one-time job and lower fluctuation.
By analyzing the characteristics of Grid market such as large-scale, heterogeneity, unreliability and customer-centric, this dissertation gives deeply analysis of the following problems, including low resource discovering efficacy; low resource availability; and unsatisfied users'QoS requirements. To solve these problems, a type-aware multi-attribute resource discovery mechanism, an accurate evaluation of resource availability risk method, a trust-filtered approach for resource selection, a fuzzy decision based multi-QoS batch scheduling algorithm are proposed in this dissertation. They give a new point of view and fine prospect for solving the problems of Grid market scheduling.
引文
曼昆.2003.经济学原理[M].梁小民译.北京：机械工业出版社.
陈晶,孔令富,潘勋.2008.结合预测机制和QoS约束的网格资源调度算法的研究[J].计算机研究与发展,45(z1)
谷清范,吴介一,张飒兵.2006.网格调度机制研究综述[J].计算机应用研究,23(5)：p.1-4.
郭磊涛.2007.对等网络中信任感知的资源交易模型[D].中国科学技术大学博士学位论文.
李茂胜.2006.基于市场的网格资源管理研究[D].中国科学技术大学博士学位论文.
申凯.2006.网格多集群环境和计算市场环境中的作业调度和资源分配研究[D].中国科学技术大学博士学位论文.
谢识予.2002.经济博弈论[M].上海：复旦大学出版社.
徐志伟,冯百明,李伟.2004.网格计算技术[M].北京：电子工业出版社.
亚当.斯密.1981.国富论[M].1981年版：北京商务印书馆.
张瑞.2009.网格市场环境中信任感知的资源交易机制研究[D].中国科学技术大学博士学位论文.
Abawajy J.H.2005. Fault-tolerant dynamic job scheduling policy [J]. Distributed and Parallel Computing,3719:p.165-173.
AL-Ali R., ShaikhAli A., Rana O., and Walker D.2003. Supporting QoS based discovery in service oriented grids [C]. Proceeding of the Int'l Parallel and Distributed Processing Symp(IPDPS 2003). IEEE Computer Society,101-109.
Anthony S., P. Gokul, B. Rajkumar, et al.2007. On incorporating differentiated levels of network service into GridSim [J]. Future Gener. Comput. Syst.,23(4):p.606-615.
Asano T., et al.1997. Space-filling curves and their use in the design of geometric data structures [M]. Theoretical Computer Science.181(1):p.3-15.
Azougagh D., Y. Jung-Lok, K. Jin-Soo, et al.2005. Resource co-allocation: a complementary technique that enhances performance in grid computing environment [C]. In Parallel and Distributed Systems,2005. Proceedings.11th International Conference on.2005.
Azzedin F. and M. Maheswaran.2002. Towards Trust-Aware Resource Management in Grid Computing Systems [C]. In 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid. p.452-452.
Basu S., et al.2005. NodeWiz: Peer-to-peer resource discovery for Grids [C].2005 IEEE International Symposium on Cluster Computing and the Grid, Vols 1 and 2:p.213-220.
Berten V., J. Goossens, and E. Jeannot.2006. On the distribution of sequential jobs in random brokering for heterogeneous computational grids [J]. Parallel and Distributed Systems, IEEE Transactions on.17(2):p.113-124.
Brent N. Chun, Philip Buonadonna, Alvin AuYoung, et al.2005. A Microeconomic Resource Allocation System for SensorNet Testbeds [C]. In Proceedings of the 2nd IEEE Workshop on Embedded Networked Sensors, May 2005.
Brent N.C. and E.C. David.2002. User-Centric Performance Analysis of Market-Based Cluster Batch Schedulers [C]. Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid. IEEE Computer Society. p.30.
Buyya R.2002. Economic-Based distributed resource management and scheduling for grid computing [D]. Melbourne:Monash University.
Buyya R. et al.2002. Economic models for resource management and scheduling in Grid computing [J], Concurrency and Computation-Practice & Experience.14(13-15):p.1507-1542.
Buyya R., M. Murshed, and D. Abramson.2002. A Deadline and Budget Constrained Cost-Time Optimization Algorithm for Scheduling Task Farming Applications on Global Grids [C]. Proceedings of the 2002 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'02).
Buyya, R., D. Abramson, and S. Venugopal.2005. The Grid Economy [M]. Proceedings of the IEEE,93(3):p.698-714.
Buyya, R., et al.2002. Economic models for resource management and scheduling in Grid computing [M]. Concurrency and Computation-Practice & Experience.14(13-15):p. 1507-1542.
Buyya, R., M. Murshed, and D. Abramson.2002. A Deadline and Budget Constrained Cost-Time Optimization Algorithm for Scheduling Task Farming Applications on Global Grids [C]. Proceedings of the 2002 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'02),2002
C. Waldspurger, T. Hogg, B. Huberman, J. Kephart, and W. Stornetta.1992. Spawn:A Distributed Computational Economy [J]. IEEE Transactions on Software Engineering, Vol.18, No.2, pp 103-117, IEEE CS Press, USA, February 1992.
Cai M., et al.2003. MAAN:A multi-attribute addressable network for grid information services [C]. Fourth International Workshop on Grid Computing, Proceedings:p.184-191.
Chunlin L., L. Layuan, and L. Zhengding.2005. Utility driven dynamic resource allocation using competitive markets in computational grid [J]. Adv. Eng. Softw.,36(6):p.425-434.
Czajkowski K., et al.2001. Grid information services for distributed resource sharing. High Performance Distributed Computing [C]. Proceedings.10th IEEE International Symposium on. 2001.
Ding Q., and Chen G.2001. A benefit function mapping heuristic for a class of meta—tasks in grid environments [C]. Proceedings of the 1st IEEE International Symposium on Cluster Computing and the Grid, Brisbane, Australia,654-658.
Dongarra J, Foster I, Fox G, et al.2002. The sourcebook of parallel computing [M]. ISBN: 1-55860-871-0, San Francisco: Morgan Kaufmann Publishers.
Foster I.2006. Globus Toolkit version 4: Software for service-oriented systems [J]. Journal of Computer Science and Technology.21(4):p.513-520.
Foster I. et al.2002. Grid services for distributed system integration [J], Computer.35(6):p. 37-46.
Foster I., C. Kesselman, J.M. Nick et al.2002. Grid services for distributed system integration [J]. Computer,2002.35(6):p.37-46.
Foster I., Geisler J., Nickless W. et al.1997. Software infrastructure for the I-WAY high performance distributed computing experiment [C]. In proceedings: 5th IEEE Symposium on High Performance Distributed Computing, pp.562-571.
Foster, I. and C. Kesselman.1997. Globus:A metacomputing infrastructure toolkit [C]. The International Journal of Supercomputer Applications and High Performance Computing,11 (2): p.115-128.
Fu Qianfei, Yang Shoubao, Li Maosheng, et al.2005. Transaction Mechanism Design in Decentralized Computational Market [C]. International Conference on Information Technology: Coding and Computing.
Gambetta D.1988. "Can we trust trust?" in Trust:Making and Breaking Cooperative Relations[C]. Basil Blackwell. p.213-237.
GGF.2008. From OGSI to WS-Resource Framework: Refactoring and Evolution. www.globus.org/wsrf/specs/ogsi_to_wsrf_1.0.pdf. Visit date:April 2008.
Gomoluch Jacek and Schroeder Michael.2003. Market-based Resource Allocation for Grid Computing: A Model and Simulation [C]. Proceedings of the 1st Workshop on Middleware for Grid Computing (MGC'03).
Hamscher V., Schwiegelshohn U., Streit A. and Yahyapour R.2000. Evaluation of Job-Scheduling Strategies for Grid Computing [C]. GRID 2000,191-202. Lecture Notes in Computer Science, Springer-Verlag.
Hu Z., Z. Hu, and Z. Liu.2007. Resource Availability Evaluation in Service Grid Environment [C]. In Asia-Pacific Service Computing Conference, The 2nd IEEE.
Hwang S. and C. Kesselman.2003. A Flexible Framework for Fault Tolerance in the Grid [J]. Journal of Grid Computing.1(3):p.251-272.
Ian Foster and Carl Kesselman.1998. The grid: Blueprint for a new computing infrastructure [M]. ISBN: 1558604758, San Francisco:Morgan Kaufmann Publishers.
Ian Foster, Carl Kesselman and S. Tuecke.2001. The anatomy of the grid:Enabling Scalable Virtual Organizations [J], International Journal of Supercomputer Applications,15(3).
Ian Foster.2002. What is the Grid? A Three Point Checklist [M]. Grid Today,1(6).
Iosup A., M. Jan, O. Sonmez, et al.2007. On the dynamic resource availability in grids, in Grid Computing[C],2007 8th IEEE/ACM International Conference on.
Irwin D.E., L.E. Grit, and J.S. Chase.2004. Balancing risk and reward in a market-based task service [C]. IEEE International Symposium on High Performance Distributed Computing, Proceedings:p.160-169.
Jennifer M.S.2004. Ten actions when Grid scheduling: the user as a Grid scheduler, in Grid resource management: state of the art and future trends [M]. Kluwer Academic Publishers. p. 15-23.
Jia Yu, Rajkumar Buyya, and Chen Khong Tham.2005. QoS-based scheduling of workflow applications on service grids [C]. Proceedings of the 1st IEEE International Conference on e-Science and Grid Computing, Melbourne, Australia,1-9.
Kobra Etminani, and M Naghibzadeh.2007. A min-min max-min selective algorithm for grid task scheduling [C].3rd IEEE/IFIP International Conference in Central Asia:1-7.
L. He, S. A. Jarvis, D. P. Spooner, X. Chen, and G. R. Nudd.2004. Dynamic Scheduling of Parallel Jobs with QoS Demands in Multiclusters and Grids [C]. Pittsburgh, USA. In 5th IEEE/ACM International Workshop on Grid Computing (Grid2004),2004.
Li D., et al.2007. IPBGA:A hybrid P2P Based Grid Architecture by using information pool protocol [J]. Algorithms and Architectures for Parallel Processing, Proceedings.4494: p. 356-367.
Ligang H., et al.2004. Dynamic Scheduling of Parallel Jobs with QoS Demands in Multiclusters and Grids [C]. In Proceedings of the Fifth IEEE/ACM International Workshop on Grid Computing. IEEE Computer Society, p.402-409.
Ligang H., et al.2004. Dynamic Scheduling of Parallel Jobs with QoS Demands in Multiclusters and Grids [C]. Proceedings of the Fifth IEEE/ACM International Workshop on Grid Computing. IEEE Computer Society, p.402-409.
Linguo G, S. Xian-He, and F.W. Edward.2002. Performance Modeling and Prediction of Nondedicated Network Computing [J]. IEEE Trans. Comput,51(9):p.1041-1055.
Lu L. et al.2006. Design and simulation of resource scheduling system for grid environment based on dynamic pricing [J], Journal of System Simulation,18(4):p.932-937.
Maheswaran M.1999. Quality of service driven resource management algorithms for network computing [C]. Proceedings of the International Conference on Parallel and Distributed Processing Technology, Nevada, USA,1090-1096.
Maozhen Li and Mark Baker.2005. The grid core technologies [M]. ISBN:7-302-14117-7, USA: John Wiley & Sons, Inc.
Mastroianni C., D. Talia, and O. Verta.2005. A super-peer model for resource discovery services in large-scale Grids [J]. Future Generation Computer Systems.21(8):p.1235-1248.
Mastroianni C., D. Talia, and O. Verta.2008. Designing an information system for Grids: Comparing hierarchical, decentralized P2P and super-peer models [J]. Parallel Computing. 34(10):p.593-611.
Michael Pinedo.2000. Scheduling:Theory, Algorithms, and Systems [M].2nd edition, Pearson Education, Inc., publishing as Prentice-Hall, Inc. ISBN 978-7-302-15310-8.
Muthucumaru M., A. Shoukat, S. Howard Jay, et al.1999a. Dynamic Matching and Scheduling of a Class of Independent Tasks onto Heterogeneous Computing Systems [C]. Proceedings of the Eighth Heterogeneous Computing Workshop. IEEE Computer Society.
Muthucumaru M., A. Shoukat, S. Howard Jay, et al.1999b. Dynamic mapping of a class of independent tasks onto heterogeneous computing systems [J]. J. Parallel Distrib. Comput,59(2): p.107-131.
Muthucumaru M., A. Shoukat, S. Howard Jay, et al.1999. Dynamic mapping of a class of independent tasks onto heterogeneous computing systems [J]. J. Parallel Distrib. Comput.,59(2): p.107-131.
N. Nisan, S. London, O. Regev, and N. Camiel.1998. Globally Distributed computation over the Internet:The POPCORN project [C]. International Conference on Distributed Computing Systems (ICDCS'98), May 26-29,1998, Amsterdam, The Netherlands, IEEE CS Press, USA.
Ori R. and N. Noam.1998. The POPCORN market:An online market for computational resources [C]. Proceedings of the first international conference on Information and computation economies[J]. ACM:Charleston, South Carolina, United States, p.148-157.
Peter A.D. and R.O.H. David.1999. An Evaluation of Linear Models for Host Load Prediction [C]. In Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing. IEEE Computer Society.
Plissonneau L, Costeux JL, Brown P.2005. Analysis of Peer-to-Peer Traffic on ADSL [C]. In: Dovrolis C, ed. Proc. of PAM 2005, LNCS 3431, Heidelberg:Springer-Verlag,2005.69-82.
Quema V., R. Lachaize, and E. Cecchet.2004. An asynchronous middleware for Grid resource monitoring [J], Concurrency Computation Practice and Experience.16(5):p.523-534.
R. Buyya and M. Murshed.2002. GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing, Technical Report, Monash University, Nov.2001. To appear in the Journal of Concurrency and Computation: Practice and Experience (CCPE), 1-32pp, Wiley Press, May 2002.
R. Buyya, D. Abramson, and J. Giddy.2000. Nimrod-G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid [C]. The 4th International Conference on High Performance Computing in Asia-Pacific Region (HPC Asia 2000), May 2000, Beijing, China, IEEE Computer Society Press, USA.
Ratnasamy S., et al.2001. A scalable Content-Addressable Network [J]. Computer Communication Review.31(4):p.161-172.
Ren X., S. Lee, R. Eigenmann, et al.2007. Prediction of Resource Availability in Fine-Grained Cycle Sharing Systems Empirical Evaluation [J]. Journal of Grid Computing,2007.5(2):p. 173-195.
Rich Wolski, James S. Plank and Todd Bryan.2001. G-commerce: Market Formulations Controlling Resource Allocation on the Computational Grid [C]. Proceedings of the 15th International Parallel and Distributed Processing Symposium (IPDPS'01). IEEE Computer Society:Vol.1.
Runfang Z. and H. Kai.2006. Trust overlay networks for global reputation aggregation in P2P grid computing [C]. In 20th International Parallel and Distributed Processing Symposium, p.10 pp.
Schopf J.M., et al.2006. Monitoring the grid with the globus toolkit MDS4 [J]. SciDAC 2006: Scientific Discovery Through Advanced Computing.46:p.521-525.
Shaofeng L.2007. User-Centric Resource Allocation Hierarchy in Grid Computing [C]. Proceedings of the Sixth International Conference on Grid and Cooperative Computing. IEEE Computer Society. p.228-235.
Song S.S., K. Hwang, and Y.K. Kwok.2006. Risk-resilient heuristics and genetic algorithms for security-assured grid job scheduling [J], IEEE Transactions on Computers.55(6):p.703-719.
Srinivasan S., Kettimuthu R., Subramani V. and Sadayappan P.2002. Characterization of Backfilling Strategies for Parallel Job Scheduling [C]. ICPP Workshops,514-522, Vancouver, BC, Canada.
Steve J.C., et al.1999. The Legion Resource Management System [J]. Proceedings of the Job Scheduling Strategies for Parallel Processing. Springer-Verlag. p.162-178.
Stoica I. et al.2001. Chord:A scalable peer-to-peer lookup service for Internet applications [J]. Computer Communication Review.31(4):p.149-160.
Subramoniam K, Maheswaran M, and Toulouse M.2002. Towards a micro-economic model for resource allocation in grid computing systems [C]. In Proc. of the 2002 IEEE Canadian Conf. on Electrical and Computer Engineering. Manitoba:IEEE Press.
Subramoniam K., Maheswaran, M.,Toulouse, M..Towards.2002. A micro-economic model for resource allocation in Grid computing systems [C]. Electrical and Computer Engineering,2002. IEEE CCECE 2002. Canadian Conference on.
Sulistio A. et al.2007. On Incorporating Differentiated Levels of Network Service into GridSim [J], Future Generation Computer Systems (FGCS),23(4):p.606-615.
TL Saaty.2008. Decision making with the analytic hierarchy process [J].International Journal of Services Sciences.
Weng C. and Lu X.2005. Heuristic scheduling for bag-of-tasks applications in combination with QoS in the computational grid [J]. Future Generation Computer Systems,21(2):271-280.
Wu M, Shu W, Zhang H.2000. Segmented min-min:A static mapping algorithm for meta-tasks on heterogeneous computing systems [C]. Cancun, Mexico:Proc of the 9th Heterogeneous Computing Workshop:375-385.
X. He, X. Sun, G. von Laszewski.2003. A QoS guided scheduling algorithm for grid computing [J]. Journal of Computer Science and Technology,18(4):442-451.
XiaoShan H., S. XianHe, and L. Gregor von.2003. QoS guided min-min heuristic for grid task scheduling [J]. J. Comput. Sci. Technol.18(4):p.442-451.
XiaoShan H., S. XianHe, and L. Gregor von.2003. QoS guided min-min heuristic for grid task scheduling [J]. J. Comput. Sci. Technol.,18(4):p.442-451.
Xuechai Z., J.L. Freschl, and J.M. Schopf.2003. A performance study of monitoring and information services for distributed systems [C]. High Performance Distributed Computing. Proceedings.12th IEEE International Symposium on 2003.
Yichuan S. and S. Derong.2008. HilbertChord: A Kind of Method for Managing Service Resources in P2P [C]. Computer Science and Software Engineering,2008 International Conference.
Zhu X., J.Z. Luo and A.B. Song.2008. A Grid Information Services Architecture Based on Structured P2P Systems [J]. Computer Supported Cooperative Work in Design Iv.5236:p. 374-383.
陈晶,孔令富,潘勋.2008.结合预测机制和QoS约束的网格资源调度算法的研究[J].计算机研究与发展,45(z1)
谷清范,吴介一,张飒兵.2006.网格调度机制研究综述[J].计算机应用研究,23(5)：p.1-4.
郭磊涛.2007.对等网络中信任感知的资源交易模型[D].中国科学技术大学博士学位论文.
李茂胜.2006.基于市场的网格资源管理研究[D].中国科学技术大学博士学位论文.
申凯.2006.网格多集群环境和计算市场环境中的作业调度和资源分配研究[D].中国科学技术大学博士学位论文.
谢识予.2002.经济博弈论[M].上海：复旦大学出版社.
徐志伟,冯百明,李伟.2004.网格计算技术[M].北京：电子工业出版社.
亚当.斯密.1981.国富论[M].1981年版：北京商务印书馆.
张瑞.2009.网格市场环境中信任感知的资源交易机制研究[D].中国科学技术大学博士学位论文.
Abawajy J.H.2005. Fault-tolerant dynamic job scheduling policy [J]. Distributed and Parallel Computing,3719:p.165-173.
AL-Ali R., ShaikhAli A., Rana O., and Walker D.2003. Supporting QoS based discovery in service oriented grids [C]. Proceeding of the Int'l Parallel and Distributed Processing Symp(IPDPS 2003). IEEE Computer Society,101-109.
Anthony S., P. Gokul, B. Rajkumar, et al.2007. On incorporating differentiated levels of network service into GridSim [J]. Future Gener. Comput. Syst.,23(4):p.606-615.
Asano T., et al.1997. Space-filling curves and their use in the design of geometric data structures [M]. Theoretical Computer Science.181(1):p.3-15.
Azougagh D., Y. Jung-Lok, K. Jin-Soo, et al.2005. Resource co-allocation: a complementary technique that enhances performance in grid computing environment [C]. In Parallel and Distributed Systems,2005. Proceedings.11th International Conference on.2005.
Azzedin F. and M. Maheswaran.2002. Towards Trust-Aware Resource Management in Grid Computing Systems [C]. In 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid. p.452-452.
Basu S., et al.2005. NodeWiz: Peer-to-peer resource discovery for Grids [C].2005 IEEE International Symposium on Cluster Computing and the Grid, Vols 1 and 2:p.213-220.
Berten V., J. Goossens, and E. Jeannot.2006. On the distribution of sequential jobs in random brokering for heterogeneous computational grids [J]. Parallel and Distributed Systems, IEEE Transactions on.17(2):p.113-124.
Brent N. Chun, Philip Buonadonna, Alvin AuYoung, et al.2005. A Microeconomic Resource Allocation System for SensorNet Testbeds [C]. In Proceedings of the 2nd IEEE Workshop on Embedded Networked Sensors, May 2005.
Brent N.C. and E.C. David.2002. User-Centric Performance Analysis of Market-Based Cluster Batch Schedulers [C]. Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid. IEEE Computer Society. p.30.
Buyya R.2002. Economic-Based distributed resource management and scheduling for grid computing [D]. Melbourne:Monash University.
Buyya R. et al.2002. Economic models for resource management and scheduling in Grid computing [J], Concurrency and Computation-Practice & Experience.14(13-15):p.1507-1542.
Buyya R., M. Murshed, and D. Abramson.2002. A Deadline and Budget Constrained Cost-Time Optimization Algorithm for Scheduling Task Farming Applications on Global Grids [C]. Proceedings of the 2002 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'02).
Buyya, R., D. Abramson, and S. Venugopal.2005. The Grid Economy [M]. Proceedings of the IEEE,93(3):p.698-714.
Buyya, R., et al.2002. Economic models for resource management and scheduling in Grid computing [M]. Concurrency and Computation-Practice & Experience.14(13-15):p. 1507-1542.
Buyya, R., M. Murshed, and D. Abramson.2002. A Deadline and Budget Constrained Cost-Time Optimization Algorithm for Scheduling Task Farming Applications on Global Grids [C]. Proceedings of the 2002 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'02),2002
C. Waldspurger, T. Hogg, B. Huberman, J. Kephart, and W. Stornetta.1992. Spawn:A Distributed Computational Economy [J]. IEEE Transactions on Software Engineering, Vol.18, No.2, pp 103-117, IEEE CS Press, USA, February 1992.
Cai M., et al.2003. MAAN:A multi-attribute addressable network for grid information services [C]. Fourth International Workshop on Grid Computing, Proceedings:p.184-191.
Chunlin L., L. Layuan, and L. Zhengding.2005. Utility driven dynamic resource allocation using competitive markets in computational grid [J]. Adv. Eng. Softw.,36(6):p.425-434.
Czajkowski K., et al.2001. Grid information services for distributed resource sharing. High Performance Distributed Computing [C]. Proceedings.10th IEEE International Symposium on. 2001.
Ding Q., and Chen G.2001. A benefit function mapping heuristic for a class of meta—tasks in grid environments [C]. Proceedings of the 1st IEEE International Symposium on Cluster Computing and the Grid, Brisbane, Australia,654-658.
Dongarra J, Foster I, Fox G, et al.2002. The sourcebook of parallel computing [M]. ISBN: 1-55860-871-0, San Francisco: Morgan Kaufmann Publishers.
Foster I.2006. Globus Toolkit version 4: Software for service-oriented systems [J]. Journal of Computer Science and Technology.21(4):p.513-520.
Foster I. et al.2002. Grid services for distributed system integration [J], Computer.35(6):p. 37-46.
Foster I., C. Kesselman, J.M. Nick et al.2002. Grid services for distributed system integration [J]. Computer,2002.35(6):p.37-46.
Foster I., Geisler J., Nickless W. et al.1997. Software infrastructure for the I-WAY high performance distributed computing experiment [C]. In proceedings: 5th IEEE Symposium on High Performance Distributed Computing, pp.562-571.
Foster, I. and C. Kesselman.1997. Globus:A metacomputing infrastructure toolkit [C]. The International Journal of Supercomputer Applications and High Performance Computing,11 (2): p.115-128.
Fu Qianfei, Yang Shoubao, Li Maosheng, et al.2005. Transaction Mechanism Design in Decentralized Computational Market [C]. International Conference on Information Technology: Coding and Computing.
Gambetta D.1988. "Can we trust trust?" in Trust:Making and Breaking Cooperative Relations[C]. Basil Blackwell. p.213-237.
GGF.2008. From OGSI to WS-Resource Framework: Refactoring and Evolution. www.globus.org/wsrf/specs/ogsi_to_wsrf_1.0.pdf. Visit date:April 2008.
Gomoluch Jacek and Schroeder Michael.2003. Market-based Resource Allocation for Grid Computing: A Model and Simulation [C]. Proceedings of the 1st Workshop on Middleware for Grid Computing (MGC'03).
Hamscher V., Schwiegelshohn U., Streit A. and Yahyapour R.2000. Evaluation of Job-Scheduling Strategies for Grid Computing [C]. GRID 2000,191-202. Lecture Notes in Computer Science, Springer-Verlag.
Hu Z., Z. Hu, and Z. Liu.2007. Resource Availability Evaluation in Service Grid Environment [C]. In Asia-Pacific Service Computing Conference, The 2nd IEEE.
Hwang S. and C. Kesselman.2003. A Flexible Framework for Fault Tolerance in the Grid [J]. Journal of Grid Computing.1(3):p.251-272.
Ian Foster and Carl Kesselman.1998. The grid: Blueprint for a new computing infrastructure [M]. ISBN: 1558604758, San Francisco:Morgan Kaufmann Publishers.
Ian Foster, Carl Kesselman and S. Tuecke.2001. The anatomy of the grid:Enabling Scalable Virtual Organizations [J], International Journal of Supercomputer Applications,15(3).
Ian Foster.2002. What is the Grid? A Three Point Checklist [M]. Grid Today,1(6).
Iosup A., M. Jan, O. Sonmez, et al.2007. On the dynamic resource availability in grids, in Grid Computing[C],2007 8th IEEE/ACM International Conference on.
Irwin D.E., L.E. Grit, and J.S. Chase.2004. Balancing risk and reward in a market-based task service [C]. IEEE International Symposium on High Performance Distributed Computing, Proceedings:p.160-169.
Jennifer M.S.2004. Ten actions when Grid scheduling: the user as a Grid scheduler, in Grid resource management: state of the art and future trends [M]. Kluwer Academic Publishers. p. 15-23.
Jia Yu, Rajkumar Buyya, and Chen Khong Tham.2005. QoS-based scheduling of workflow applications on service grids [C]. Proceedings of the 1st IEEE International Conference on e-Science and Grid Computing, Melbourne, Australia,1-9.
Kobra Etminani, and M Naghibzadeh.2007. A min-min max-min selective algorithm for grid task scheduling [C].3rd IEEE/IFIP International Conference in Central Asia:1-7.
L. He, S. A. Jarvis, D. P. Spooner, X. Chen, and G. R. Nudd.2004. Dynamic Scheduling of Parallel Jobs with QoS Demands in Multiclusters and Grids [C]. Pittsburgh, USA. In 5th IEEE/ACM International Workshop on Grid Computing (Grid2004),2004.
Li D., et al.2007. IPBGA:A hybrid P2P Based Grid Architecture by using information pool protocol [J]. Algorithms and Architectures for Parallel Processing, Proceedings.4494: p. 356-367.
Ligang H., et al.2004. Dynamic Scheduling of Parallel Jobs with QoS Demands in Multiclusters and Grids [C]. In Proceedings of the Fifth IEEE/ACM International Workshop on Grid Computing. IEEE Computer Society, p.402-409.
Ligang H., et al.2004. Dynamic Scheduling of Parallel Jobs with QoS Demands in Multiclusters and Grids [C]. Proceedings of the Fifth IEEE/ACM International Workshop on Grid Computing. IEEE Computer Society, p.402-409.
Linguo G, S. Xian-He, and F.W. Edward.2002. Performance Modeling and Prediction of Nondedicated Network Computing [J]. IEEE Trans. Comput,51(9):p.1041-1055.
Lu L. et al.2006. Design and simulation of resource scheduling system for grid environment based on dynamic pricing [J], Journal of System Simulation,18(4):p.932-937.
Maheswaran M.1999. Quality of service driven resource management algorithms for network computing [C]. Proceedings of the International Conference on Parallel and Distributed Processing Technology, Nevada, USA,1090-1096.
Maozhen Li and Mark Baker.2005. The grid core technologies [M]. ISBN:7-302-14117-7, USA: John Wiley & Sons, Inc.
Mastroianni C., D. Talia, and O. Verta.2005. A super-peer model for resource discovery services in large-scale Grids [J]. Future Generation Computer Systems.21(8):p.1235-1248.
Mastroianni C., D. Talia, and O. Verta.2008. Designing an information system for Grids: Comparing hierarchical, decentralized P2P and super-peer models [J]. Parallel Computing. 34(10):p.593-611.
Michael Pinedo.2000. Scheduling:Theory, Algorithms, and Systems [M].2nd edition, Pearson Education, Inc., publishing as Prentice-Hall, Inc. ISBN 978-7-302-15310-8.
Muthucumaru M., A. Shoukat, S. Howard Jay, et al.1999a. Dynamic Matching and Scheduling of a Class of Independent Tasks onto Heterogeneous Computing Systems [C]. Proceedings of the Eighth Heterogeneous Computing Workshop. IEEE Computer Society.
Muthucumaru M., A. Shoukat, S. Howard Jay, et al.1999b. Dynamic mapping of a class of independent tasks onto heterogeneous computing systems [J]. J. Parallel Distrib. Comput,59(2): p.107-131.
Muthucumaru M., A. Shoukat, S. Howard Jay, et al.1999. Dynamic mapping of a class of independent tasks onto heterogeneous computing systems [J]. J. Parallel Distrib. Comput.,59(2): p.107-131.
N. Nisan, S. London, O. Regev, and N. Camiel.1998. Globally Distributed computation over the Internet:The POPCORN project [C]. International Conference on Distributed Computing Systems (ICDCS'98), May 26-29,1998, Amsterdam, The Netherlands, IEEE CS Press, USA.
Ori R. and N. Noam.1998. The POPCORN market:An online market for computational resources [C]. Proceedings of the first international conference on Information and computation economies[J]. ACM:Charleston, South Carolina, United States, p.148-157.
Peter A.D. and R.O.H. David.1999. An Evaluation of Linear Models for Host Load Prediction [C]. In Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing. IEEE Computer Society.
Plissonneau L, Costeux JL, Brown P.2005. Analysis of Peer-to-Peer Traffic on ADSL [C]. In: Dovrolis C, ed. Proc. of PAM 2005, LNCS 3431, Heidelberg:Springer-Verlag,2005.69-82.
Quema V., R. Lachaize, and E. Cecchet.2004. An asynchronous middleware for Grid resource monitoring [J], Concurrency Computation Practice and Experience.16(5):p.523-534.
R. Buyya and M. Murshed.2002. GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing, Technical Report, Monash University, Nov.2001. To appear in the Journal of Concurrency and Computation: Practice and Experience (CCPE), 1-32pp, Wiley Press, May 2002.
R. Buyya, D. Abramson, and J. Giddy.2000. Nimrod-G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid [C]. The 4th International Conference on High Performance Computing in Asia-Pacific Region (HPC Asia 2000), May 2000, Beijing, China, IEEE Computer Society Press, USA.
Ratnasamy S., et al.2001. A scalable Content-Addressable Network [J]. Computer Communication Review.31(4):p.161-172.
Ren X., S. Lee, R. Eigenmann, et al.2007. Prediction of Resource Availability in Fine-Grained Cycle Sharing Systems Empirical Evaluation [J]. Journal of Grid Computing,2007.5(2):p. 173-195.
Rich Wolski, James S. Plank and Todd Bryan.2001. G-commerce: Market Formulations Controlling Resource Allocation on the Computational Grid [C]. Proceedings of the 15th International Parallel and Distributed Processing Symposium (IPDPS'01). IEEE Computer Society:Vol.1.
Runfang Z. and H. Kai.2006. Trust overlay networks for global reputation aggregation in P2P grid computing [C]. In 20th International Parallel and Distributed Processing Symposium, p.10 pp.
Schopf J.M., et al.2006. Monitoring the grid with the globus toolkit MDS4 [J]. SciDAC 2006: Scientific Discovery Through Advanced Computing.46:p.521-525.
Shaofeng L.2007. User-Centric Resource Allocation Hierarchy in Grid Computing [C]. Proceedings of the Sixth International Conference on Grid and Cooperative Computing. IEEE Computer Society. p.228-235.
Song S.S., K. Hwang, and Y.K. Kwok.2006. Risk-resilient heuristics and genetic algorithms for security-assured grid job scheduling [J], IEEE Transactions on Computers.55(6):p.703-719.
Srinivasan S., Kettimuthu R., Subramani V. and Sadayappan P.2002. Characterization of Backfilling Strategies for Parallel Job Scheduling [C]. ICPP Workshops,514-522, Vancouver, BC, Canada.
Steve J.C., et al.1999. The Legion Resource Management System [J]. Proceedings of the Job Scheduling Strategies for Parallel Processing. Springer-Verlag. p.162-178.
Stoica I. et al.2001. Chord:A scalable peer-to-peer lookup service for Internet applications [J]. Computer Communication Review.31(4):p.149-160.
Subramoniam K, Maheswaran M, and Toulouse M.2002. Towards a micro-economic model for resource allocation in grid computing systems [C]. In Proc. of the 2002 IEEE Canadian Conf. on Electrical and Computer Engineering. Manitoba:IEEE Press.
Subramoniam K., Maheswaran, M.,Toulouse, M..Towards.2002. A micro-economic model for resource allocation in Grid computing systems [C]. Electrical and Computer Engineering,2002. IEEE CCECE 2002. Canadian Conference on.
Sulistio A. et al.2007. On Incorporating Differentiated Levels of Network Service into GridSim [J], Future Generation Computer Systems (FGCS),23(4):p.606-615.
TL Saaty.2008. Decision making with the analytic hierarchy process [J].International Journal of Services Sciences.
Weng C. and Lu X.2005. Heuristic scheduling for bag-of-tasks applications in combination with QoS in the computational grid [J]. Future Generation Computer Systems,21(2):271-280.
Wu M, Shu W, Zhang H.2000. Segmented min-min:A static mapping algorithm for meta-tasks on heterogeneous computing systems [C]. Cancun, Mexico:Proc of the 9th Heterogeneous Computing Workshop:375-385.
X. He, X. Sun, G. von Laszewski.2003. A QoS guided scheduling algorithm for grid computing [J]. Journal of Computer Science and Technology,18(4):442-451.
XiaoShan H., S. XianHe, and L. Gregor von.2003. QoS guided min-min heuristic for grid task scheduling [J]. J. Comput. Sci. Technol.18(4):p.442-451.
XiaoShan H., S. XianHe, and L. Gregor von.2003. QoS guided min-min heuristic for grid task scheduling [J]. J. Comput. Sci. Technol.,18(4):p.442-451.
Xuechai Z., J.L. Freschl, and J.M. Schopf.2003. A performance study of monitoring and information services for distributed systems [C]. High Performance Distributed Computing. Proceedings.12th IEEE International Symposium on 2003.
Yichuan S. and S. Derong.2008. HilbertChord: A Kind of Method for Managing Service Resources in P2P [C]. Computer Science and Software Engineering,2008 International Conference.
Zhu X., J.Z. Luo and A.B. Song.2008. A Grid Information Services Architecture Based on Structured P2P Systems [J]. Computer Supported Cooperative Work in Design Iv.5236:p. 374-383.