一种面向服务的暗标拍卖网格资源分配方法

针对计算网格环境下资源的动态性、异构性和自治性，以及应用经济机制解决资源分配问题的优势，以面向服务的思想，提出了一个基于OGSA的架构的网格服务市场的资源分配框架SBAGRM，在此框架下给出了暗标拍卖的模型，并对暗标拍卖博弈的Bayes均衡点以及系统在均衡状态的效率，策略和效用进行了分析，最后给出了基于道格拉斯效用函数的分配算法。     

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.     

一种基于效用函数的网格资源分配策略

针对网格资源分配中用户需求的异构性问题，提出了一种基于效用函数优化的分配策略。该策略综合考虑用户作业执行费用和执行时间两方面的因素，利用拉格朗日方法解决网格用户效用函数的优化问题，通过二分搜索最优解产生一组优化的用户出价，根据该组出价按比例划分资源的计算能力。该分配策略可对网格资源的价格以及资源的占用时间进行优化，对动态、异构的网格环境具有较好的适　　应性。     

一种基于市场机制的数据网格复制选择策略*

针对数据网格提出了一种基于市场机制的复制选择策略,以一般均衡理论为基础,依靠市场机制实现数据网格的复制选择策略。首先给出了数据网格复制选择的市场模型,其中效用函数用于刻画应用代理与数据所在站点之间进行数据传输的消耗;然后在此基础上根据供需规律提出了副本的自动生成策略以及副本的自动选择策略;最后对本策略对应的算法时间复杂度和空间复杂度进行了分析。     

基于移动Agent的网格计算资源管理模型设计

网格计算是当前高性能计算领域的一个研究热点,由于网格计算的资源具有分布性,异构性,自治性,动态性等特点,因而其资源管理比一般系统的资源管理具有更大的复杂度。文中提出了一种基于Agent的网格计算资源管理模型,并且采用了混合遗传模拟退火算法作为调度策略,满足了网格对调度系统可扩展性和全局最优调度的需求。实验结果证实了该方法的有效性。     

基于n维空间模型的计算网格资源查找方法

提出了描述计算网格资源的空间模型,按网格资源的性质将网格资源组织在n维空间中,并按资源之间的相似程度对资源进行关联,该模型不需建立资源的全局视图,系统复杂度不会随着资源数量的增加而增大。基于资源空间模型的资源查找算法能够保证资源查找沿着正确的方向进行,从而提高资源搜索效率。同时还给出了该算法的时间复杂和空间复杂度分析。     

一种基于市场机制的计算网格资源分配方法

针对计算网格提出了一种基于市场机制的资源分配方法，以一般均衡理论为基础，依靠市场机制，实现计算网格资源的优化分配，首先，描述了基于代理的资源分配框架，它包括3个 层次：资源层、代理层和用户层；接着，给出了计算网络资源分配的市场模型，其中效用函数用于刻画用户对给定资源的满意程度；然后定义了市场模型的均衡状态并证明了均衡状态撮优性，这意味着在均衡状态下资源分配不仅有效而且公平，最后引入了资源代理的迭代算法。     

网格环境下一种有效的资源查找方法

在分布、异构的网格环境下，如何快速进行资源查找定位是影响网格计算性能的重要因素．该文对网格环境下已有资源查找方法进行了分析，指出了这些方法存在的不足，提出了基于路由转发(Routing-Transfer)机制的资源查找算法．该文中对这些资源查找方法进行了时间复杂度和空间复杂度分析，结果表明文中提出的路由转发算法的时间复杂度最小，其空间耗费可以容忍，是网格环境下一种有效的资源查找定位方法．     

基于计算经济的网格资源管理研究

网格是为解决大规模资源密集型问题而提出的新一代计算平台,资源管理是网格的关键技术之一。但是,资源的分布性、异构性、自治性、动态性等使得网格资源的管理变得异常复杂。目前,基于市场的经济资源管理和调度算法非常适合解决网格中的资源管理问题。本文提出了网格环境下基于经济模型的各种代理,给出了一种新的资源管理模型
型,并定义了效用函数,给出了基于效用最优的资源调度算法。为解决网格资源管理的问题提供了一个有效的途径。     

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。     

A distributed multiple dimensional QoS constrained resource scheduling optimization policy in computational grid

This paper is to solve efficient QoS based resource scheduling in computational grid. It defines a set of QoS dimensions with utility function for each dimensions, uses a market model for distributed optimization to maximize the global utility. The user specifies its requirement by a utility function. A utility function can be specified for each QoS dimension. In the grid, grid task agent acted as consumer pay for the grid resource and resource providers get profits from task agents. The task agent' utility can then be defined as a weighted sum of single-dimensional QoS utility function. QoS based grid resource scheduling optimization is decomposed to two subproblems: joint optimization of resource user and resource provider in grid market. An iterative multiple QoS scheduling algorithm that is used to perform optimal multiple QoS based resource scheduling. The grid users propose payment for the resource providers, while the resource providers set a price for each resource. The experiments show that optimal QoS based resource scheduling involves less overhead and leads to more efficient resource allocation than no optimal resource allocation.     

Energy constrained resource allocation optimization for mobile grids

A mobile grid incorporates mobile devices into Grid systems. But mobile devices at present have severe limitations in terms of processing, memory capabilities and energy. Minimizing the energy usage in mobile devices poses significant challenges in mobile grids. This paper presents energy constrained resource allocation optimization for mobile grids. The goal of the paper is not only to reduce energy consumption, but also to improve the application utility in a mobile grid environment with a limited energy charge, ensuring battery lifetime and the deadlines of the grid applications. The application utility not only depends on its allocated resources including computation and communication resources, but also on the consumed energy, this leads to a coupled utility model, where the utilities are functions of allocated resources and consumed energy. Energy constrained resources allocation optimization is formulated as a utility optimization problem, which can be decomposed into two subproblems, the interaction between the two sub-problems is controlled through the use of a pricing variable. The paper proposes a price-based distributed energy constrained resources allocation optimization algorithm. In the simulation, the performance evaluation of our energy constrained resources allocation optimization algorithm is conducted.     

基于竞争机制的网格资源分配方法

针对在网格环境下对资源进行有效管理和调度的复杂性问题,提出一个基于竞争机制的网格资源分配模型,其中包括用户层、代理层及资源层。在该模型的基础上给出资源分配策略及一种费用优化算法。模拟实验表明,该模型能够较好地适应网格环境的动态变化,调整供给和需求的平衡。     

Multi-level scheduling for global optimization in grid computing

The paper presents a multi-level scheduling algorithm for global optimization in grid computing. This algorithm provides a global optimization through a cross-layer optimization realized by decomposing the optimization problem in different sub-problems each of them corresponding to one among the grid layers such as application layer, collective layer and fabric layer. The QoS of an abstraction level is a utility function that assigns at every level a different value and that depends on the kind of task that is executed on the grid. The global QoS is given by processing of the utility function values of the three different levels, using the Lagrangian method. Multi-level QoS scheduling algorithm is evaluated in terms of system efficiency and their economic efficiency, respectively. Economic efficiency includes user utility, service provider’s revenue and grid global utility. System efficiency includes execution success ratio and resource allocation ratio.     

基于合作博弈的虚拟化资源效用分配策略

效用分配是网格虚拟化资源提供者结成联盟完成用户任务时的关键问题。针对资源提供者建立联盟来提高网格整体效用的情况,研究了利用合作博弈论分配网格资源。给出了资源建立联盟的依据,并以基于费用最小化的MIN_COST算法得到了资源的最优化映射方案。在效用分配中,分别从联盟效用的平均分配和Shapley值分配两方面进行了分析,提出了基于Shapley值的资源联盟效用分配策略。算例结果表明,网格资源联盟可以提高任务的执行效率和资源整体收益,而Shapley值法在均衡联盟个体的效用分配方面也是有效可行的。     

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.     

Agent based sensors resource allocation in sensor grid

Sensor enabled grid may combine real time data about physical environment with vast computational resources derived from the grid architecture. One of the major challenges of designing a sensor enabled grid is how to efficiently schedule sensor resource to user jobs across the collection of sensor resources. The paper presents an agent based scheme for assigning sensor resources to appropriate sensor grid users on the basis of negotiation results among agents. The proposed model consists of two types of agents: the sensor resource agents that represent the economic interests of the underlying sensor resource providers of the sensor grid and the sensor user agents that represent the interests of grid user application using the grid to achieve goals. Interactions between the two agent types are mediated by means of market mechanisms. We model sensor allocation problems by introducing the sensor utility function. The goal is to find a sensor resource allocation that maximizes the total profit. This paper proposes a distributed optimal sensor resource allocation algorithm. The performance evaluation of proposed algorithm is evaluated and compared with other resource allocation algorithms for sensor grid. The paper also gives the application example of proposed approach.     

Dynamic scheduling model of computing resource based on MAS cooperation mechanism

Allocation of grid resources aims at improving resource utility and grid application performance. Currently, the algorithms proposed for this purpose do not fit well the autonomic, dynamic, distributive and heterogeneous features of the grid environment. According to MAS (multi-agent system) cooperation mechanism and market bidding game rules, a model of allocating allocation of grid resources based on market economy is introduced to reveal the relationship between supply and demand. This model can make good use of the studying and negotiating ability of consumers’ agent and takes full consideration of the consumer’s behavior, thus rendering the application and allocation of resource of the consumers rational and valid. In the meantime, the utility function of consumer is given; the existence and the uniqueness of Nash equilibrium point in the resource allocation game and the Nash equilibrium solution are discussed. A dynamic game algorithm of allocating grid resources is designed. Experimental results demonstrate that this algorithm diminishes effectively the unnecessary latency, improves significantly the smoothness of response time, the ratio of throughput and resource utility, thus rendering the supply and demand of the whole grid resource reasonable and the overall grid load balanceable. Supported by the Natural Science Foundation of Hunan Province (Grant No. 06JJ2033), and the Society Science Foundation of Hunan Province (Grant No. 07YBB239)