Ontology‐based Grid resource management

Grid resources are typically diverse in nature with respect to their software and hardware configurations, resource usage policies and the kind of application they support. Aggregating and monitoring these resources, and discovering suitable resources for the applications become a challenging issue. This is partially due to the representation of Grid metadata supported by the existing Grid middleware which offers limited scope for matching the job requirements that directly affect scheduling decisions. This paper proposes a semantic component in conventional Grid architecture to support ontology‐based representation of Grid metadata and facilitate context‐based information retrieval that complements Grid schedulers for effective resource management. Web Ontology language is used for creating Grid resource ontology and Algernon inference engine has been used for resource discovery. This semantic component has been integrated with conventional Grid schedulers. Several experiments have also been carried out to investigate the performance overhead that arises while integrating this component with Grid schedulers. Copyright © 2009 John Wiley & Sons, Ltd.     

云计算环境下兼顾买卖双方利益的双向拍卖资源分配算法

针对当前云计算环境下的资源分配算法不能充分考虑买卖双方利益的问题,本文提出了一种适用于云计算环境的组合双向拍卖资源分配模型。首先,初始化云经纪人列表和供应商报价列表,拍卖人通知拍卖参与者拍卖开始;然后,根据属性值按升序排序云经纪人请求和云服务供应商报价列表,从而确定投标获胜者;最后,获胜的云经纪人向相关云服务供应商发送任务并支付费用,云服务商执行任务。仿真实验使用CloudSim原型化,在基于Java的仿真云环境中从经济角度进行了效率评估。仿真结果表明,本文模型适用于云环境中的资源分配,在经济上非常有效。相比其他的现有模型,本文模型更能鼓励参与者在买卖双方公平公正的前提下根据真实估值竞购资源。     

Design and implementation of economics-based resource management system in ad hoc grid

The ad hoc grid is a spontaneous organization of cooperating heterogeneous nodes into a logical community without a fixed infrastructure and with only minimal administrative requirements. Resource management for ad hoc grids is challenging due to the participation of heterogeneous, dynamic, autonomous and ephemeral grid nodes. The paper proposes an ad hoc grid resource management system, the producers and consumers of ad hoc grid resource are modeled as the self-interested decision-makers described in microeconomic theory. All market participants in the ad hoc grid environment including grid resources and services can be represented as agents. We apply economic agents to build ad hoc grid resource management, where ad hoc grid resource consumers and providers can buy and sell ad hoc grid resource based on an underlying economic architecture. The main processes involved in ad hoc grid resource management are resource registration, discovery, and resource allocation. The experiments are conducted to compare ad hoc grid resource allocation algorithm with other ad hoc grid resource allocation algorithm. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme.     

A reputation-driven scheduler for autonomic and sustainable resource sharing in Grid computing

The obstacle for the Grid to be prevalent is the difficulty in using, configuring and maintaining it, which needs excessive IT knowledge, workload, and human intervention. At the same time, inter-operation amongst Grids is on track. To be the core of Grid systems, the resource management must be autonomic and inter-operational to be sustainable for future Grid computing. For this purpose, we introduce HOURS, a reputation-driven economic framework for Grid resource management. HOURS is designed to tackle the difficulty of automatic rescheduling, self-protection, incentives, heterogeneous resource sharing, reservation, and SLA in Grid computing. In this paper, we focus on designing a reputation-based resource scheduler, and use emulation to test its performance with real job traces and node failure traces. To describe the HOURS framework completely, a preliminary multiple-currency-based economic model is also introduced in this paper, with which future extension and improvement can be easily integrated into the framework. The results demonstrate that our scheduler can reduce the job failure rate significantly, and the average number of job resubmissions, which is the most important metric in this paper that affects the system performance and resource utilization from the perspective of users, can be reduced from 3.82 to 0.70 compared to simple sequence resource selection.     

Flexible Grid service management through resource partitioning

In this paper, a distributed and scalable Grid service management architecture is presented. The proposed architecture is capable of monitoring task submission behaviour and deriving Grid service class characteristics, for use in performing automated computational, storage and network resource-to-service partitioning. This partitioning of Grid resources amongst service classes (each service class is assigned exclusive usage of a distinct subset of the available Grid resources), along with the dynamic deployment of Grid management components dedicated and tuned to the requirements of a particular service class introduces the concept of Virtual Private Grids. We present two distinct algorithmic approaches for the resource partitioning problem, the first based on Divisible Load Theory (DLT) and the second built on Genetic Algorithms (GA). The advantages and drawbacks of each approach are discussed and their performance is evaluated on a sample Grid topology using NSGrid, an ns-2 based Grid simulator. Results show that the use of this Service Management Architecture in combination with the proposed algorithms improves computational and network resource efficiency, simplifies schedule making decisions, reduces the overall complexity of managing the Grid system, and at the same time improves Grid QoS support (with regard to job response times) by automatically assigning Grid resources to the different service classes prior to scheduling.     

An optimization-based adaptive resource management framework for economic Grids: A switching mechanism

The application of Grid computing has been broadening day by day. An increasing number of users has led to the requirement of a job scheduling process, which can benefit them through optimizing their utility functions. On the other hand, resource providers are exploring strategies suitable for economically efficient resource allocation so that they can maximize their profit through satisfying more users. In such a scenario, economic-based resource management strategies (economic models) have been found to be compelling to satisfy both communities. However, existing research has identified that different economic models are suitable for different scenarios in Grid computing. The Grid application and resource models are typically very dynamic, making it challenging for a particular model for delivering stable performance all the time. In this work, our focus is to develop an adaptive resource management architecture capable of dealing with multiple models based on the models’ domains of strengths (DOS). Our preliminary results show promising outcomes if we consider multiple models rather than relying on a single model throughout the life cycle of a Grid.     

网格计算任务的资源管理算法

计算任务管理贯穿于整个网格计算的全生命周期,目标是运用既有规律又经济的方法对计算进行高效率的计划、组织、指导和控制,实现时间、费用和技术效果上的动态优化。该文对计算任务的资源管理进行研究,对资源管理指标进行形式化分析,对计算时耗、成本和资源平衡这3个目标进行综合决策,提出了一种网格计算任务的资源管理算法。仿真实验证明算法是可行有效的。     

基于计算期望的网格资源管理模型

网格环境下的计算资源具有分布性,异构性,动态性的特征,并分别属于不同的组织,使网格资源管理相对分布式计算环境或集群环境下的资源管理更加复杂.在计算经济模型的基础上,提出了一种基于计算期望的网格资源管理模型.模型将计算任务抽象成对计算期望的描述,以实现灵活高效的网格资源管理和调度.通过可变价格策略,反映了网格内资源的供求关系,并对基于预留的Qos保证进行了初步的讨论.     

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。     

Analysis and Provision of QoS for Distributed Grid Applications

Grid computing provides the infrastructure necessary to access and use distributed resources as part of virtual organizations. When used in this way, Grid computing makes it possible for users to participate in collaborative and distributed applications such as tele-immersion, visualization, and computational simulation. Some of these applications operate in a collaborative mode, requiring data to be stored and delivered in a timely manner. This class of applications must adhere to stringent real-time constraints and Quality-of-Service (QoS) requirements. A QoS management approach is therefore required to orchestrate and guarantee the timely interaction between such applications and services. We discuss the design and a prototype implementation of a QoS system, and demonstrate how we enable Grid applications to become QoS compliant. We validate this approach through a case study of an image processing task derived from a nanoscale structures application.     

基于蚁群遗传算法的网格资源调度研究

传统的资源调度算法在网格环境下存在一定缺陷,如不能很好地平衡资源节点的负载,不能很好满足用户服务质量需求等.为了提高网络质量,应用遗传算法全局快速收敛的优点,将遗传算法融入到蚁群算法的每一次迭代中,使之具有很强的全局搜索能力,以加快算法的收敛速度,提出了在价格机制驱动下,应用蚁群遗传算法进行网格资源调度的算法.仿真实验结果表明,在价格机制驱动下,应用蚁群遗传算法进行网格资源调度可以减少系统总执行时间和任务完成时间,系统负载均衡度好,提高了资源调度效率,在网格环境下,算法具有稳定性和高效性.     

Online algorithms for advance resource reservations

We consider the problem of providing QoS guarantees to Grid users through advance reservation of resources. Advance reservation mechanisms provide the ability to allocate resources to users based on agreed-upon QoS requirements and increase the predictability of a Grid system, yet incorporating such mechanisms into current Grid environments has proven to be a challenging task due to the resulting resource fragmentation. We use concepts from computational geometry to present a framework for tackling the resource fragmentation, and for formulating a suite of scheduling strategies. We also develop efficient implementations of the scheduling algorithms that scale to large Grids. We conduct a comprehensive performance evaluation study using simulation, and we present numerical results to demonstrate that our strategies perform well across several metrics that reflect both user- and system-specific goals. Our main contribution is a timely, practical, and efficient solution to the problem of scheduling resources in emerging on-demand computing environments.     

基于经济模型的网格资源调度算法研究

基于经济模型的网格资源调度算法是目前网格环境中非常重要的调度算法.介绍基于经济模型调度算法的基本思想和体系结构,对4种基于经济模型的调度算法做了详细的阐述,并在GridSim上的模拟结果做了分析与比较.     

网络资源管理的Grid和P2P集成方案及其关键技术分析

网格计算(Grid)偏重通用协议,考虑共享的基础设施以及互操作问题;对等计算(P2P)则关注垂直集成解决方案.而开放网格服务体系结构(OGSA)为网格与P2P的集成提供了一个框架,使网格与P2P能更好地聚合在一起,从而更有利于网格的扩展性、自治性和动态性.对此,全面介绍了网络资源管理的Grid与P2P集成方案的常见模型,分析了这些模型中的几个关键问题,并指出了今后的研究方向.     

Grid resource brokering algorithms enabling advance reservations and resource selection based on performance predictions

We present algorithms, methods, and software for a Grid resource manager, that performs resource brokering and job scheduling in production Grids. This decentralized broker selects computational resources based on actual job requirements, job characteristics, and information provided by the resources, with the aim to minimize the total time to delivery for the individual application. The total time to delivery includes the time for program execution, batch queue waiting, and transfer of executable and input/output data to and from the resource. The main features of the resource broker include two alternative approaches to advance reservations, resource selection algorithms based on computer benchmark results and network performance predictions, and a basic adaptation facility. The broker is implemented as a built-in component of a job submission client for the NorduGrid/ARC middleware.     

基于ESA的网格资源管理模型

提出了基于ESA的网格资源管理模型。该模型以Service-Agent为基础,结合了Agent动态自主性和服务的松散耦合优点,运用经济学的市场机制和交易理论,提出该模型的资源发现机制、分配选择机制和交易机制,以及基于议价交易机制的Bargaining_Min_min算法,实现资源的优化管理,使资源提供者和使用者满足各自利益,达到网格市场上的双赢。     

网格实例与关键技术分析

Grid computing technology is developing in an impressing speed these years. This paper is going to do some detailed analysis on two of the major Grid projects, Globus and Legion, in order to find out the key technologies of Grid computing. In this paper, three key technologies will be discussed: Grid Architecture, Grid Data and Resource Services, and Grid Security Services. Different implementation of these technologies will be discussed and compared with each other, some new ideas about these technologies will be proposed as well.     

Key management for Smart Grid based on asymmetric key-wrapping

Cyber security is considered as a critical issue which must be addressed early during the transition from the current aging electric power grid into the expected Smart Grid. Key management is the fundamental supporting cryptographic technologies for Smart Grid cyber security. This paper focuses on remote key generation and distribution for Smart Grid, especially computation-saving mechanisms for meters. Specifically, we specialize asymmetric key-wrapping to the Smart Grid application scenario, and further suggest an instantiation of remotely generating and distributing keys for Smart Grid, which is an issue raised by National Institute of Standards and Technology. In this way, we achieve a key-wrapping adapter, retrofitting an encryption system to work with an incompatible key-management architecture and seamlessly supporting different options of cryptosystems for smart meters. The proposed scheme has low computational cost at weak smart meters, because of the weaker security assumption of the wrapping algorithm and the transfer of computational cost from meters to servers.     

Grid resource management policies for load-balancing and energy-saving by vacation queuing theory

The resource management is the central component of grid system. The analysis of the workload log file of LCG including the job arrival and the resource utilization daily cycle shows that the idle sites in the Grid are the source of load imbalance and energy waste. Here we focus on these two issues: balancing the workload by transferring jobs to idle sites at prime time to minimize the response time and maximize the resource utilization; power management by switch the idle sites to sleeping mode at non-prime time to minimize the energy consume. We form the M/G/1 queue model with server vacations, startup and closedown to analysis the performance metrics to instruct the design of load-balancing and energy-saving policies. We provide our Adaptive Receiver Initiated (ARI) load-balancing strategy and power-management policy for energy-saving. The simulation experiments prove the accuracy of our analysis and the comparisons results indicate our policies are largely suitable for large-scale heterogeneous grid environment.     

Application execution management on the InteGrade opportunistic grid middleware

The InteGrade project is a multi-university effort to build a novel grid computing middleware based on the opportunistic use of resources belonging to user workstations. The InteGrade middleware currently enables the execution of sequential, bag-of-tasks, and parallel applications that follow the BSP or the MPI programming models.