Quality of Service Provision for Grid Applications via Intelligent Scheduling

网格计算可以定义为在动态、多机构协作中协调资源共享和问题解决。网格基础设施的成功基于许多基本需求，包括提供动态和高效服务的能力。支撑这样一个系统的需要是确保网格基础设施向其用户交付所需的服务质量。服务质量（QoS）是应用程序在一定程度上保证用户需求能够得到满足的能力。它可以被视为用户和资源提供者之间的协议，以预先指定的成本在保证的时间范围内执行应用程序。通常，用户支付的成本越高，资源提供者可以确保的执行时间就越短。提出的项目的新颖贡献是产生一种新型的网格资源代理，它具有高级调度组件，旨在优化资源使用成本和应用程序的执行时间，以加强QoS。它应该结合两种代理类型的特性：以系统为中心和以用户为中心，提供一种满足用户需求的透明方式，同时优化提供者端网格资源的使用。这个建议是及时的，因为它解决了持续开发网格计算基础设施支持的需求。它响应了网格社区对QoS提供的日益关注，以及网格用户在约定的执行时间内以约定的价格获得适当服务的更高期望。我们的研究将充分利用经典调度理论和新兴的网格调度研究成果，并将推进这两个领域的前沿。网格应用程序产生了新的增强调度模型。这些增强的模型通常不能由主要为制造应用程序开发的现有调度技术来处理。它们的特点是具有复杂的附加约束，包括与数据存储和数据传输有关的约束，协调关联任务的执行以及安排所需的数据交换。进一步的挑战与网格系统的动态特性以及资源的可用性和质量的变化有关。QoS提供的新方面给调度带来了额外的复杂性。该项目将利用利兹大学两个已建立的研究小组的专业知识：算法和复杂性小组以及协作架构和性能小组。算法和复杂性组在算法、组合学和优化方面进行多学科研究。除其他外，该小组开发和分析先进的数学技术，以解决复杂的优化问题，包括与调度和最佳资源分配领域相关的问题。协同架构和性能组的研究重点是大规模应用的智能基础设施。特别是，该小组的研究汇集了电子科学，网格和自适应计算系统的研究。

Grid computing can be defined as coordinated resource sharing and problem solving in dynamic, multi-institutional collaborations. The success of a Grid infrastructure is based on a number of fundamental requirements, including the ability to provide dynamic and efficient services. Underpinning such a system is the need to ensure that the Grid infrastructure is delivering the required Quality of Service to its users. Quality of Service (QoS) is the ability of an application to have some level of assurance that users' requirements can be satisfied. It can be seen as an agreement between a user and a resource provider to execute an application within a guaranteed time frame at a pre-specified cost. As a rule, the higher the cost paid by the user, the smaller the execution time a resource provider can ensure. The novel contribution of the proposed project is to produce a new type of Grid resource broker with an advanced scheduling component aimed at optimising both resource usage costs and applications' execution times to enforce QoS. It should combine the features of two types of brokers: system-centric and user-centric providing a transparent means of meeting users' requirements and at the same time optimising the usage of Grid resources on the provider's end. This proposal is timely in that it addresses the need for continued development of infrastructure support for Grid computing. It responds to the increased attention of the Grid community to QoS provision and higher expectations of Grid users to receive adequate services at an agreed price payable for the agreed execution time. Our research will take advantage of the achievements in the classical scheduling theory and the newly emerged Grid scheduling research and will advance the frontiers of both areas. Grid applications give rise to new enhanced scheduling models. These enhanced models generally cannot be handled by the existing scheduling techniques developed mainly for manufacturing applications. They are characterised by complex additional constraints including those related to data storage and data transfer, co-ordinating the execution of linked tasks and arranging the required data interchange. Further challenges are related to the dynamic nature of Grid systems with the changing availability and quality of resources. The new aspects of QoS provision introduce additional complexity to scheduling. The project will draw on expertise of two established research groups at the University of Leeds: Algorithms and Complexity Group and Collaborative Architectures and Performance Group. The Algorithms and Complexity Group performs multidisciplinary research in algorithms, combinatorics and optimisation. Inter alia, the group develops and analyses advanced mathematical techniques for solving complex optimisation problems including those related to the areas of scheduling and optimal resource allocation. Research of the Collaborative Architectures and Performance Group focuses on Intelligent Infrastructures for large-scale applications. In particular, research of the group brings together e-science, Grid and adaptive computing systems research.