基于MAS市场机制的动态计算资源调度模型研究

针对动态计算网格资源调度问题,结合多Agent系统(multi agent syste,MAS)协同技术和市场竞价博弈机制,对计算网格资源分配技术进行了深入研究,提出了能够反映供求关系的基于市场经济的网格资源调度模型,该模型一方面能够充分利用消费者Agent的协商能力,另一方面能够充分考虑消费者的行为,使得消费者的资源申请和分配具有较高的合理性和有效性.同时,设计了消费者的效用函数,论证了资源分配博弈中Nash均衡点的存在性和惟一性以及Nash均衡解.基于所提资源调度模型,设计了一种网格资源调度算法.仿真实验表明,资源调度算法能够为消费者的资源数量提供参考,规范消费者竞价,从而使得整个资源的分配趋于合理.     

基于MAS协同的动态资源优化调度策略研究*

目前,围绕着网格中的资源调度方法,虽然已提出了各种调度算法,但是都不能很好地适应网格环境下的自治性、动态性、分布性和异构性等特征。针对动态计算网格资源调度问题,基于多智能体协同技术和市场博弈机制,对计算网格资源分配技术进行了深入研究,提出了能够反映供求关系的基于计算经济机制的网格资源调度模型,建立了消费者的效用函数,给出了资源调度的动态博弈算法。仿真实验说明资源利用率比传统算法好,整个资源的供需合理、负载均衡。     

MAS动态协作任务求解模型与算法

针对网格环境的自治性、动态性、分布性和异构性等特征.提出基于多智能体系统(mutil agent system, MAS) 博弈协作的资源动态分配和任务调度模型,建立了能够反映供求关系的网格资源调度动态任务求解算法,证明了资源分配博弈中Nash均衡点的存在性、惟一性和Nash均衡解.该方法能够利用消费者Agent的学习和协商能力,引入消费者的心理行为,使消费者的资源申请和任务调度具有较高的合理性和有效性.实验结果表明,该方法在响应时间的平滑性、吞吐率及任务求解效率方面比传统算法要好,从而使得整个资源供需合理、满足用户QoS要求.     

Multi economic agent interaction for optimizing the aggregate utility of grid users in computational grid

This paper investigates the interactions between agents representing grid users and the providers of grid resources to maximize the aggregate utilities of all grid users in computational grid. It proposes a price-based resource allocation model to achieve maximized utility of grid users and providers in computational grid. Existing distributed resource allocation schemes assume the resource provider to be capable of measuring user’s resource demand, calculating and communicating price, none of which actually exists in reality. This paper addresses these challenges as follows. First, the grid user utility is defined as a function of the grid user’s the resource units allocated. We formalize resource allocation using nonlinear optimization theory, which incorporates both grid resource capacity constraint and the job complete times. An optimal solution maximizes the aggregate utilities of all grid users. Second, this paper proposes a new optimization-based grid resource pricing algorithm for allocating resources to grid users while maximizing the revenue of grid providers. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme. Li Chunlin received the ME in computer science from Wuhan Transportation University in 2000, and PhD degree in Computer Software and Theory from Huazhong University of Science and Technology in 2003. She now is an associate professor of Computer Science in Wuhan University of Technology. Her research interests include computational grid, distributed computing and mobile agent. She has published over 15 papers in international journals. Li Layuan received the BE degree in Communication Engineering from Harbin Institute of Military Engineering, China in 1970 and the ME degree in Communication and Electrical Systems from Huazhong University of Science and Technology, China in 1982. Since 1982, he has been with the Wuhan University of Technology, China, where he is currently a Professor and PhD tutor of Computer Science, and Editor in Chief of the Journal of WUT. He is Director of International Society of High-Technol and Paper Reviewer of IEEE INFOCOM, ICCC and ISRSDC. His research interests include high speed computer networks, protocol engineering and image processing. Professor Li has published over 150 technical papers and is the author of six books. He also was awarded the National Special Prize by the Chinese Government in 1993.     

一种新的经济网格计算任务调度控制模型

针对动态计算网格资源调度问题,基于多智能体协同技术和市场博弈机制,对计算网格资源分配技术进行了深入研究,提出了基于计算经济的网格资源调度模型,设计了消费者的效用函数,讨论了资源分配博弈中Nash 均衡解,设计了一种网格资源调度算法.仿真实验表明,资源调度算法能够为消费者的资源数量提供参考,规范消费者行为,从而使得整个资源的分配趋于合理,促进交易量.     

Utility-driven solution for optimal resource allocation in computational grid

Optimal resource allocation is a complex undertaking due to large-scale heterogeneity present in computational grid. Traditionally, the decision based on certain cost functions has been used in allocating grid resource as a standard method that does not take resource access cost into consideration. In this paper, the utility function is presented as a promising method for grid resource allocation. To tackle the issue of heterogeneous demand, the user's preference is represented by utility function, which is driven by a user-centric scheme rather than system-centric parameters adopted by cost functions. The goal of each grid user is to maximize its own utility under different constraints. In order to allocate a common resource to multiple bidding users, the optimal solution is achieved by searching the equilibrium point of resource price such that the total demand for a resource exactly equals the total amount available to generate a set of optimal user bids. The experiments run on a Java-based discrete-event grid simulation toolkit called GridSim are made to study characteristics of the utility-driven resource allocation strategy under different constraints. Results show that utility optimization under budget constraint outperforms deadline constraint in terms of time spent, whereas deadline constraint outperforms budget constraint in terms of cost spent. The conclusion indicates that the utility-driven method is a very potential candidate for the optimal resource allocation in computational grid.     

网格环境中信任-激励相容的资源分配机制

在网格环境中,多数节点希望能够更多地使用其他节点的资源,而不愿共享本地的资源.每个理性的用户在追求自身利益最大化的同时,严重影响了协作整体的运行效率.在实际应用中,要吸引资源的拥有者加入资源协作,就必须保证其利益和安全.讨论了资源激励机制和分配机制之间的依赖与制约关系,从经济、信任角度提出自适应的信任-激励相容的资源分配机制.在网格环境中,资源供需的变化会引发价格的浮动,基于经济学的一般均衡理论,给出了资源提供者的动态价格调整策略.提供者可根据当前资源的供需和负载状况,制定自适应的信任-激励相容的分配策略ATIM(adaptive trust-incentive compatible resource allocation),遵循多贡献多分配的原则,激励节点共享出有价值的资源,最大化资源的聚合效用.在CROWN(China research and development environment over wider-area network)平台中评估了ATIM机制的效率和性能.     

基于纳什均衡理论的网格资源调度机制

网格环境下资源是分布的、异构的、动态的,由不同的组织拥有,各组织对资源的管理策略以及资源的存取花费各不相同,因此网格资源管理和调度是具有挑战性的问题。文章针对网格资源的特性,提出一种基于经济学理论的资源优化管理机制,描述了基于市场经济的网格资源管理模型,有效地解决了资源的供给和需求。以纳什均衡理论为基础,依靠市场机制,实现基于QoS的网格资源管理和调度。     

异构无线网络中基于非合作博弈论的资源分配和接入控制

对异构无线网络中无线资源分配和呼叫接入控制进行研究.基于非合作博弈理论,提出了不同无线资源的带宽和连接数量分配的理论模型.结合网络连接的效用函数,对非合作博弈的无线资源分配中的纳什均衡点的存在性和唯一性进行论证.而且,进一步对业务量与阻塞率之间的关系进行分析,提出了能够保证通信可靠性的接入控制算法.仿真结果表明,基于非合作博弈论的无线资源分配机制能够有效地解决带宽和连接数量的分配问题,并能在整体上保证分配的合理性和公平性.接入控制算法根据需要能够动态地调整在某一区域分配的连接数量,从而保证通信的可靠性.     

The Proportional-Share Allocation Market for Computational Resources

We study the problem of allocating shared resources, such as bandwidth in computer networks and computational resources in shared clusters, among multiple users by the proportional-share market mechanism. Under this mechanism, each user partitions his budget among the multiple resources and receives a fraction of each resource proportional to his bid. We first formulate the resource allocation game under the proportional-share mechanism and study the efficiency and fairness of the equilibrium in this game. We present analytic and simulation results demonstrating that the proportional-share mechanism achieves a reasonable balance of high degrees of efficiency and fairness at the equilibrium.     

基于Nash平衡点的网络收益优化策略

研究了非合作用户的网络定价问题．将对策论中主从策略的思想应用到定价策略中，首先分析了在Nash平衡态下使主方收益达到最大时价格所满足的条件；然后结合网络市场的供求关系，将Nash平衡点视为供求平衡点，从而确定了相应的价格；最后以数值例子得出Nash平衡态下用户的速率和网络的收益．结果表明，合理的价控策略能够激发用户合理地使用网络资源，同时给管理者带来最优收入．     

基于网格环境的资源管理模型研究

针对目前网格环境下资源管理存在的问题和现状，提出了一种基于市场机制的资源管理模型。该模型以一般均衡理论为基础，计算出资源的市场价格，依靠市场机制，实现计算网格资源的优化分配。     

W^1,2（Ω）- and X^1,2（Ω）-stability of reaction- diffusion cellular neural networks with delay

With Poincare＇s inequality and auxiliary function applied in a class of retarded cellular neural networks with reaction-diffusion, the conditions of the systems＇ W^1,2（Ω）-exponential and X^1,2（Ω）-asmptotic stability are obtained. The stability conditions containing diffusion term are different from those obtained in the previous papers in their exponential stability conditions. One example is given to illustrate the feasibility of this method in the end.     

基于市场竞标机制的网格资源管理模型

网格资源管理是网格计算首要解决的核心问题。现行的网格资源管理模型通常需要在网格系统中建立一个高于其他节点的自身庞大的管理体系,以掌握全网格内资源动态信息,实现全局资源调配,这种模式的主要问题是管理成本高且资源配置效率低。文章基于市场经济中的招投标机理,提出了一种新的网格资源管理模型,本模型的资源分配机制是根据网格内资源供需关系和资源的市场价格通过招投标方式来决定。网格内站点是否参与网格计算交易活动,完全由站点自主地根据自身资源现状和资源的市场价格来确定而不需要一个高于自己的管理机构,本模型是一个完全的市场经济的资源分配模型。     

Interacting oligopolistic and oligopsonistic Cournot markets

This paper considers the model of several interacting Cournot markets. Some of them are final goods markets, while the others are resource markets. The markets interact by sharing the same set of economic agents (producers), so that the latter are oligopsonists on resource markets and simultaneously oligopolists on goods markets. Each producer strategically chooses its supply volumes on each goods market and its purchase volume of resources in accordance with technology and expected supply effects on prices. We prove that in the case of linear demand and supply functions the model of interacting Cournot markets is reduced to a potential game; hence, the Nash equilibrium problem is equivalent to a mathematical programming problem. We also discuss the advantages and special features of such a representation of interacting oligopolistic and oligopsonistic markets.     

协作式云资源博弈分配

针对用户对云资源的异构性需求和竞争问题,提出了一种协作式资源分配博弈策略。建立了资源分配的协作式博弈模型,定义了协作博弈的用户效用函数和评估函数,证明了在该效用函数下协作博弈存在唯一Nash均衡,并讨论了用户组建联盟对协作特征函数和整体效用的影响。实验结果表明,在该协作博弈策略下,个体用户通过组建联盟集体出价的方式,能够为联盟用户带来更大效用,以收敛方式实现Pareto改进。     

Modelling inter-supply chain competition with resource limitation and demand disruption

This paper proposes a comprehensive model for studying supply chain versus supply chain competition with resource limitation and demand disruption. We assume that there are supply chains with heterogeneous supply network structures that compete at multiple demand markets. Each supply chain is comprised of internal and external firms. The internal firms are coordinated in production and distribution and share some common but limited resources within the supply chain, whereas the external firms are independent and do not share the internal resources. The supply chain managers strive to develop optimal strategies in terms of production level and resource allocation in maximising their profit while facing competition at the end market. The Cournot–Nash equilibrium of this inter-supply chain competition is formulated as a variational inequality problem. We further study the case when there is demand disruption in the plan-execution phase. In such a case, the managers need to revise their planned strategy in order to maximise their profit with the new demand under disruption and minimise the cost of change. We present a bi-criteria decision-making model for supply chain managers and develop the optimal conditions in equilibrium, which again can be formulated by another variational inequality problem. Numerical examples are presented for illustrative purpose.     

一种基于序贯博弈的网格资源分配策略

网格环境中资源的负载预测是实现资源优化分配的关键任务之一,而网格资源的动态性和异构性使得准确判断资源的负载状态十分困难.针对已有的分配策略对资源负载评估的不足,提出了一种基于序贯博弈的优化用户时间的网格资源分配策略.该策略将正比例资源共享的网格环境中多用户竞争同一计算资源的问题形式化为一个多人序贯博弈,通过寻求该序贯博弈中各个阶段博弈的纳什均衡解来预测资源负载;然后利用此负载信息生成所有用户的最优出价组合和资源的优化价格;最后根据各用户出价,按比例分配资源的计算能力.通过对网格模拟器GridSim的实验研究,结果表明,该策略能够得到合理的用户出价,降低资源占用时间,从而弥补了Bredin提出的优化策略中未考虑资源未来负载变化的缺陷,实现了资源的优化分配.其结论说明运用序贯博弈方法预测资源负载是可行的,且能更好地适应网格环境下异构资源的动态性.     

基于非合作博弈的变电站无线网络资源研究

无线资源管理对实现资源的有效利用起着至关重要的作用.针对变电站中无线网络资源分配问题,提出了基于非合作博弈的变电站无线网络资源的优化管理算法,解决了全双工系统的无线电资源分配问题.将下行链路与上行链路的联合速率最大化问题建模成为上下行链路信道之间的非合作博弈,提出了基于非合作博弈的迭代算法.该算法有效的实现最佳上行链路与下行链路的资源分配,直到达到纳什均衡.仿真结果表明,该算法实现了快速收敛,与同等资源分配方法相比,可以显著提高全双工的性能.     

一种基于Bayes均衡的网格资源调度算法

针对经济网格提出了一种基于市场机制的资源分配方法:以Bayes均衡理论为基础,依靠市场机制,实现网格资源的优化分配。首先给出了资源交易的经济模型:双边叫价拍卖模型;接着给出了网格资源分配的市场模型:基于Bayse均衡的市场模型;最后引入了网格资源管理的调度流程和算法。