共查询到19条相似文献,搜索用时 140 毫秒
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网格市场环境下,用户的服务质量(QoS)需求更加多样化;更多普通用户加入网格市场,难以提供精确的QoS需求信息.因此,基于用户模糊QoS需求的调度算法成为网格市场中研究的热点.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,给出一种模糊决策的多维QoS的调度方法.实验表明,模糊决策的多维QoS批调度算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.与现有的QoS批调度方法相比,该算法具有较好的一次作业完成率,且作业完成率波动较小. 相似文献
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目前应用于网格的一些调度算法过于简单,不能满足对QoS的多样化需求,比如DBC(deadline and budget constrained)调度算法只支持两维的QoS需求,即截止期限(deadline)和预算(budge)。而对于真正的网格应用,用户与系统之间的交互应该加强,用户应能对提交的工作提出多种多样的QoS需求。在对传统DBC算法进行优化的基础上,提出了“多维QoS指导的DBC最优算法”,以确保搜索到所有满足用户需求的资源,不仅包括价格、时间最优,而且满足他们自己定义的专有QoS需求。为了测试这一最优算法,所做的模拟实验是以上海网格环境中各高性能结点的数据信息作为参数。 相似文献
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非凡的服务质量是网格的基本特征,基于QoS的网格任务调度问题已成为国内外研究的热点.由于网格环境的复杂性和用户主观判断的模糊性,传统基于QoS的网格调度算法不能处理具有多个模糊QoS需求的调度问题.用区间值模糊来描述用户的主观QoS需求信息,提出基于D-S理论的区间值模糊多QoS测量方法,对区间值模糊数表达的用户多QoS需求进行融合与处理,再将这些区间值模糊数QoS融合值作为任务的优先级加入到任务调度算法中,提出一种基于D-S理论的网格任务多匹配调度算法.研究结果和仿真实验表明,该算法不仅可以处理区间值模糊不确定性信息,在满足用户多QoS需求的情况下还可大大减小任务调度的时间跨度. 相似文献
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多QoS约束网格作业调度问题的多目标演化算法 总被引:14,自引:2,他引:12
针对网格计算中的多QoS约束网格作业调度问题,以独立作业为研究对象,将其规约为多目标组合最优化问题.通过深入剖析多目标最优化理论及其演化算法,结合网格作业调度自然特征,提出了一种解决多QoS约束网格作业调度问题的多目标演化算法.该算法求解多个QoS维度效用函数指标的非劣解集,尝试解决多管理域间网格用户、资源管理者等网格实体的多目标协同问题.仿真结果表明,在时间维度、可靠性维度、安全性维度QoS效用值等用户级QoS指标,以及丢弃作业数等系统级指标方面该算法与QoS-Min-min和QoS-Sufferage等同类算法相比具有较好的综合性能. 相似文献
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基于效益函数的网格任务调度算法 总被引:1,自引:0,他引:1
在动态、异构、分布广泛的网格环境中,对资源的调度是一个非常复杂而重要且具有挑战性的问题。本文针对网格环境中的动态性特点,特别是用户QoS要求的动态变化性,提出了一种基于效益函数的网格任务调度算法,并采用GridSim模拟器分别对该调度算法和模拟器自带的代价最优和时间最优的网格任务调度算法进行模拟。实验的结果表明:该调度算法更能体现用户对QoS要求的动态变化;在系统完成相同数量的网格任务时,消耗相同时间的情况下,该调度算法在代价上优于基于时间优化的调度算法;而花费相同预算的情况下,在时间上优于基于代价优化的调度算法。 相似文献
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计算网格环境下一个统一的资源映射策略 总被引:48,自引:3,他引:48
由于资源具有广域分布、异构、动态等特性,计算网格环境下资源的管理和调度是一个非常复杂且具有挑战性的问题.提出了计算网格环境下一组相互独立的计算任务(meta-task)的资源映射策略.该策略采用重复映射方法,以更好地适应网格计算环境下的动态性和自治性.算法考虑到任务的输入数据位置对映射效果的影响;通过定义效益函数,该策略在追求较小的任务完成时间的同时兼顾任务的服务质量(QoS)需求.模拟实验结果显示,该映射策略更符合计算网格的复杂环境,能够更好地满足不同用户的实际需要. 相似文献
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基于多QoS需求驱动的网格资源调度研究 总被引:1,自引:0,他引:1
为解决网格用户多QoS需求的资源调度问题,引入了满意度函数模型和经典Min-Min算法。将众多网格QoS分为性能和信任两类,选取性能QoS中的优先级、时效性、精度性和信任QoS中的安全性、可靠性共五个指标,分别构建每一维QoS参数的满意度函数模型并形成QoS综合满意度函数模型,由此设计多QoS约束的网格资源调度(Q-Min-Min)算法,以期将Min-Min算法中按照期待执行时间(ETC)进行调度改为按照服务质量综合满意度(QSM)进行调度。仿真实验表明,改进的Q-Min-Min算法在任务的跨度和成本两项性能指标上均比Min-Min算法更具优势,取得了较为理想的结果,证明了基于多QoS需求驱动的网格资源调度的有效性。 相似文献
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In this paper, we consider multiple QoS based grid resource scheduling. Each of grid task agent's diverse requirements is modeled as a quality of service (QoS) dimension, associated with each QoS dimension is a utility function that defines the benefit that is perceived by a user with respect to QoS choices in that dimension. The objective of multiple QoS based grid resource scheduling is to maximize the global utility of the scheduling system. 相似文献
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《Journal of Computer and System Sciences》2006,72(4):706-726
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. 相似文献
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《Journal of Parallel and Distributed Computing》2006,66(2):181-196
Due to the development of new applications and the increasing number of users with diverse needs who are exposed to heterogeneous computing (HC), providing users with quality of service (QoS) guarantees while executing applications has become a crucial problem that needs to be addressed. Motivated by this fact, this paper investigates the problem of scheduling a set of independent tasks with multiple QoS needs, which may include timeliness, reliability, security, data accuracy, and priority, in a HC system. This problem is referred to as the QoS-based scheduling problem and proved to be NP-hard. In the first part of this study, we formulate the QoS-based scheduling problem by using utility and penalty functions, where a utility function associated with a task is used to measure how much the owner of this task will benefit from a given scheduling decision, while penalty functions associated with resources are used to provide incentives to users to set their QoS requirements in accordance with their needs. In order to solve the QoS-based scheduling problem, a computationally efficient static scheduling algorithm (QSMTS_IP) which assumes time-invariant penalty functions is developed. We later extend the QSMTS_IP to the case where penalty functions are time varying. Furthermore, it is shown that the QSMTS_IP can be modified to run as a dynamic scheduling algorithm. The simulation studies carried out show that the QSMTS_IP is capable of meeting diverse QoS requirements of many users simultaneously, while minimizing the number of users whose tasks cannot be scheduled due to the scarcity of machines. 相似文献
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Task scheduling in heterogeneous environments such as cloud data centers is considered to be an NP-complete problem. Efficient task scheduling will lead to balance the load on the virtual machines (VMs) thereby achieving effective resource utilization. Hence there is a need for a new scheduling framework to perform load balancing amid considering multiple quality of service (QoS) metrics such as makespan, response time, execution time, and task priority. Multi-core Web server is difficult to achieve dynamic balance in the process of remote dynamic request scheduling, so it is necessary to improve it based on the traditional scheduling algorithm to enhance the actual effect of the algorithm. This article do research on the multi-core Web server, Focusing on multi-core Web server queuing model. On this basis, the author draws the drawbacks of the multi-core Web server in the remote dynamic request scheduling algorithm, and improves the traditional algorithm with the demand analysis. Not only it overcomes the drawbacks of traditional algorithms, but also promotes the system threads carrying the same amount of tasks, and promotes the server being always in a dynamic balance. On the basis of this, it achieves an effective solution to customer requests. 相似文献
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The paper presents quality of service (QoS) optimisation strategy for multi-criteria scheduling on the grid, based on a mathematical QoS model and a distributed iterative algorithm. Three QoS criteria are considered, namely payment, deadline and reliability, which are formulated as utility function. The optimisation problem is split into two parts: task optimisation performed on behalf of the user and resource optimisation performed on behalf of the grid. The strategy employs three types of agents: task agents responsible for task optimisation, computation resource and network resource agents responsible for resource optimisation. The agents apply economic models for optimisation purposes. Dynamic programming is used to optimise the total system utility function in terms of an iterative algorithm. The objective of multi-criteria scheduling is to maximise the global utility of the system. This paper proposes an iterative scheduling algorithm that is used to perform QoS optimisation-based multi-criteria scheduling. The proposed QoS optimisation-based multi-criteria scheduling problem solution has been practically examined by simulation experiments. 相似文献
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针对目前网格资源管理中任务与资源匹配问题的不足,基于信任效益函数与匹配概念,提出了信任驱动的网格调度匹配算法。在调度中同时还考虑了任务和资源效益值,对已经提出的两种信任驱动的网格调度算法进行改进。结果证明:该算法较传统基于的信任驱动调度算法而言,信任效益值,资源效益值,负载平衡和失效服务数等方面有较好的综合性能。 相似文献
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云资源的动态变化和不确定性给资源管理及任务调度带来了很大的困难.为了准确地掌握资源动态负载和可用能力信息,提出一种基于熵优化和动态加权的资源评估模型,其中,熵优化模型利用最大熵和熵增原理的目标函数及约束条件,筛选出满足用户 QoS 和系统最大化的资源,实现最优调度,保障用户 QoS.对筛选后的资源再进行动态加权负载评估,对负载过重及长期不可用资源进行迁移、释放等,可减少能耗,实现负载均衡和提高系统利用率.设计了仿真实验,以验证所提评估模型的性能.实验结果表明,熵优化模型对用户 QoS 和系统最大化有很好的效果,动态加权负载评估有利于均衡负载,提高系统利用率.该评估模型实现了用户QoS保障、减少能耗、负载均衡以及提高系统利用率等多目标的优化. 相似文献
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This paper presents an optimization approach for decentralized Quality of Service (QoS)‐based scheduling based on utility and pricing in Grid computing. The paper assumes that the quality dimensions can be easily formulated as utility functions to express quality preferences for each task agent. The utility values are calculated by the user‐supplied utility function that can be formulated with the task parameters. The QoS constraint Grid resource scheduling problem is formulated into a utility optimization problem. The QoS‐based Grid resource scheduling optimization is decomposed into two subproblems by applying the Lagrangian method. In the Grid, a Grid task agent acts as a consumer paying for the Grid resource and the resource providers receive profits from task agents. A pricing‐based QoS scheduling algorithm is used to perform optimally decentralized QoS‐based resource scheduling. The experiments investigate the effect of the QoS metrics on the global utility and compare the performance of the proposed algorithm with other economical Grid resource scheduling algorithms. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献