云联盟中收益最优化算法

云联盟环境下,资源提供者旨在协作地向用户提供资源,以获取更多的经济收益。通过联盟博弈研究了云资源提供者的群体合作行为,基于任务执行时间和执行代价最优化问题,定义了资源提供者组建资源联盟的依据,并设计了两种任务调度算法PMTC和TMPC。同时,对联盟收益进行内部分配时,提出了基于Shapley值的联盟收益分配算法,该算法充分考虑了联盟成员对联盟总收益的贡献度,使得联盟总收益在其个体成员间的分配更加均衡与合理。算例分析结果表明,云资源联盟不仅可以改进任务执行效率和资源提供者收益,而且Shapley值可以实现收益的公平分配。     

基于合并与分裂机制的云任务联盟博弈调度

为降低任务执行代价,提高云资源提供者收益,提出一种云计算环境下基于合并与分裂机制的任务调度联盟博弈优化算法。建立基于资源联盟的任务执行模型,定义资源提供者选择建立联盟的依据;给出联盟完成云任务后总收益在其联盟成员间的分配方式,重点阐述如何通过联盟合并与分裂机制产生稳定的联盟结构,分析结盟算法的性能。通过仿真实验,与同类型算法进行性能比较,比较结果表明,联盟博弈算法可以产生稳定的联盟结构,为联盟中的个体成员带来最大化收益。     

基于QoS的云计算资源分配算法

目前,基于云计算的服务越来越具有动态性,资源的分配遇到了前所未有的挑战性,我们不能简单地从成本单一方面来衡量资源分配算法的优劣。针对以上问题,提出了具有QoS限制的资源分配算法,从用户和资源提供者两个方面来考虑资源的分配,在保证用户任务的多维QoS需求的同时,寻求用户满意度和资源利用率的综合效用值的提升。通过仿真实验表明,该资源分配算法,可以减少任务之间对资源的竞争,提高所有任务的全局效用值。     

基于模糊评判的Agent联盟效用分配

多个Agent同时形成任务求解联盟时,联盟效用的分配是一个棘手的问题。已有的平均分配和基于能力大小的分配策略都没有反映出Agent对联盟贡献的差异性,不利于联盟的形成和完成任务的绩效。提出了一种基于模糊评判的联盟效用分配方法。首先模糊评价Agent的各维能力贡献率,然后综合计算出整体贡献因子,并据此完成联盟效用的合理分配,最后通过实例分析说明了此方法的有效性。     

一种基于按劳分配原则的联盟形成策略

联盟形成主要研究如何在联盟内Agent间划分联盟效用,使Agent在决策时愿意形成更优的联盟。但是已有的联盟形成策略对额外效用的平均分配没有考虑到每个Agent对联盟的贡献大小以及加入后的利益,不利于联盟的形成。提出一种基于按劳分配原则的联盟形成策略,该策略运用按能力分配原则对额外效用进行合理分配,体现了“能者多劳,多劳多得”的特点,维护了个体间的利益,优于Shapley值方法和平均分配法,较好地满足了联盟的稳定性和时效性等要求。     

信任驱动的云联盟博弈算法

为了解决云联盟中云资源提供者间的信任问题,提出一种基于信任机制的云联盟算法。算法将多个云资源提供者以合作形式完成用户任务的问题形式化为联盟博弈模型,在建立联盟时兼顾考虑成员间的信任关系及成员收益,使得具有更高信任度的资源提供者能够建立联盟以降低任务执行代价,并确保参与联盟的个体成员收益最大化。同时,证明了该算法求解的联盟结构是稳定的,并且满足Pareto最优性质。实验结果验证了算法的有效性和可行性。     

物流资源整合系统的两阶段利益分配策略研究

为获取公平合理的利益分配方案,提出了基于物流资源稀缺性和任务绩效的物流资源整合系统两阶段利益分配模型。第一阶段考虑物流资源稀缺性,针对一般资源提供商和战略资源提供商分别采用一级密封价格拍卖、Shapley值法的分配策略,获取初始利益分配方案;第二阶段考虑物流资源提供商完成物流子任务的绩效对初始利益分配方案进行修正,建立物流子任务的绩效评价指标体系,利用模糊综合评价法计算物流子任务的绩效系数,获得最终的利益分配方案。以商品车配送任务为例验证该利益分配模型不仅有助于实现物流资源的优化配置,而且激励物流资源提供商提高物流任务绩效水平。     

基于云重心Shapley值法的电子商务声誉联盟利益分配策略

由于电子商务声誉联盟的声誉能力、声誉风险和声誉成本三个主要分配因素存在模糊性和随机性的缺点,难以得到量化,以及Shapley值法本身存在的局限性,因此利用云重心评判法对Shapley值法进行修正。云理论主要体现定性与定量之间的不确定性转换,有效地解决概念的模糊性和随机性。修正后的Shapley分配法有效地提高了联盟分配的准确性,并通过算例证实了此方法的合理性和适用性,为电子商务声誉联盟的收益分配问题提供依据。     

FAHP改进Shapley值法进行工程科技创新收益分配

从合作博弈论视角分析了工程科技合作创新收益合理分配的问题,运用Shapley值法对创新联盟的收益进行初次分配;基于模糊综合评价法（FAHP）从科技创新角色重要性、合作意识、成本投入、企业实力、承担风险等量化评价各创新成员的实际贡献率,据此修正初次分配Shapley值。用工程实际创新案例进行了计算分析,结果表明改进的分配方法合理地提高了核心创新单位和承担风险大的单位的收益,分配结果与成员在联盟中的价值相匹配,有利于创新联盟的稳定,具有可操作性和实用性,可为合作创新收益分配提供理论依据与方法。     

基于收益率门槛限制考虑的网格资源拍卖问题

基于收益率门槛限制的视角,通过建立效用函数模型并结合动态博弈理论,对网格资源的拍卖问题进行了探讨.在对网格资源提供者与竞标网格资源使用者的动态博弈过程进行分析时发现,网格资源提供者的最优策略选择决定于其对货币收益与非货币收益的偏好程度,以及网格资源使用者的最高报价.在收益率门槛给定的条件下,当参与竞标的网格资源使用者具有较低的生产利润或付出较高的努力成本时,网格资源使用者将会选择价格较低的投标策略.研究结果表明收益率门槛机制的引入,在一定程度上可以使得参与双方的效用达到最大化.     

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.     

An efficient resource allocation for maximizing benefit of users and resource providers in ad hoc grid environment

Ad hoc grids allow a group of individuals to accomplish a mission that involves computation and communication among the grid components, often without fixed structure. In an ad hoc grid, every node in the network can spontaneously arise as a resource consumer or a resource producer at any time when it needs a resource or it possesses an idle resource. At the same time, the node in ad hoc grid is often energy constrained. The paper proposes an efficient resource allocation scheme for grid computing marketplace where ad hoc grid users can buy usage of memory and CPU from grid resource providers. The ad hoc grid user agents purpose to obtain the optimized quality of service to accomplish their tasks on time with a given budget, and the goal of grid resource providers as profit-maximization. Combining perspectives of both ad hoc grid users and resource providers, the paper present ad hoc grid resource allocation algorithm to maximize the global utility of the ad hoc grid system which are beneficial for both grid users and grid resource providers. Simulations are conducted to compare the performance of the algorithms with related work.     

Optimum profit allocation in coalitional VoD service

Although video-on-demand (VoD) services are provided by many ISPs, the amount of content provided by each VoD service is one order smaller than that provided by rental video services, so the limited content count is one of the obstacles to widespread VoD services. To solve this problem, ISPs can form a coalition with other ISPs and use content owned by other ISPs. However, to form a coalition among multiple ISPs, ISPs need to rationally allocate the profit obtained by the coalition to convince all ISPs participating in the coalition. We propose using the Shapley value of the coalitional game as the rational allocation of profit. Assuming that all but one ISP has the same number of users or (and) the same number of rare content, we derive the Shapley value in closed form and clarify the influence of the numbers of users and rare content on the coalition. We also compare the Shapley value with three general allocation models and show that the Shapley value agrees with the allocation when the profit obtained by each content delivery is equally shared by two ISPs, one that accommodates the receiving user and the other that owns the delivered content.     

一种基于Agent联盟的网格资源分配方法

网格资源分配是网格计算中的关键问题之一,引起网格研究者越来越多的关注。网格资源分配的过程就是任务与资源映射的过程。在分析已有的网格资源分配方法的基础上,首先提出了一种基于Agent的网格资源管理模型,主要由用户层、客户服务层、信息服务层、区域管理层和资源层组成。在此基础上对基于Agent联盟的网格资源分配方法进行了研究,最后给出了实例分析。     

Allocating the fixed cost based on data envelopment analysis in view of the Shapley value

This paper considers fixed cost allocation in view of cooperative game theory and proposes an approach based on data envelopment analysis while incorporating the perspectives of coalition efficiency and the Shapley value. To do this, we first build two models to evaluate coalition efficiencies before and after cost allocation, and we prove that all coalitions can be efficient after fixed cost allocation. Then, following the premise that each coalition makes itself efficient without reducing the efficiencies of other decision-making units' preallocation efficiency, we propose a model that determines the acceptable range of each coalition's allocated fixed cost. Furthermore, a model is constructed to determine the final cost allocation based on three principles: efficiency, monotonicity, and similarity. Moreover, the Shapley value is employed to obtain the cost allocated to each decision-making unit (DMU). The proposed approach considers the relationships among DMUs across their forming coalitions to determine their interaction types and then generates a fixed cost allocation result that possesses the features of the Shapley value. This process makes the fixed cost allocation more acceptable. Finally, a simple numerical example and an empirical case are provided to illustrate the calculation process of the proposed approach and compare our approach with the traditional methods.     

具有交流结构的区间模糊联盟合作对策

当前具有模糊联盟的合作对策研究主要基于任意局中人可自由结盟的基本假设,但现实结盟活动中,局中人普遍受到资源或地位等因素的限制,其合作往往具有交流结构限制。因此,基于Choquet模糊延拓研究了具有交流结构的区间模糊多人合作对策,给出了相应区间模糊联盟平均树解,并通过公理化体系对此解进行了研究。通过供应链纵向合作创新收益分配实例应用,并与区间模糊联盟合作对策的Shapley值进行比较,说明该方法的现实有效性。     

基于Agent联盟机制的网格资源协同分配

在网格计算环境，许多应用的执行经常需要同时协同分配多个资源以满足性能需求。文中提出了一种新的基于Agent联盟机制的资源协同分配方法。首先，对Globus和Legion的资源协同分配的方法进行了比较。然后，描述了一个基于Agent的网格资源管理结构。最后，设计了一个Agent联盟机制用于有效的资源协同分配。     

The stability of cooperative sourcing coalitions ‐ game theoretical analysis and experiment

Cooperative sourcing is when multiple firms form a coalition to merge similar processes using shared-service processing in order to leverage economies of scale and skill. This paper discusses how coalition partners should allocate coalition costs and benefits to ensure a stable coalition which minimizes the incentives for current or future coalition partners to withdraw from the coalition. The paper develops a formal cost allocation and benefit model which is then used in game theoretical analyses and bargaining experiments. The results show that proportional cost allocation is key to avoiding unstable coalitions. However, if coalition partners do not disclose their cost structures to facilitate a cooperative decision in favor of proportional cost allocation, but rather negotiate shared costs based on “closed books”, proportional cost allocation is rarely achieved. In such cases, the Shapley value has high predictive power and negotiators are in danger of making poor decisions that can lead to instable coalitions. These findings help sensitize managers to the structural threats inherent to multilateral negotiations of cooperative sourcing coalitions.     

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.