G-lambda: Coordination of a Grid scheduler and lambda path service over GMPLS

At iGrid2005, we conducted a live demonstration where our Grid scheduling system co-allocated computing and network resources with advance reservation through Web services interfaces using the Grid Resource Scheduler (GRS), the Network Resource Management System (NRM), which is capable of GMPLS network resource management, and a GMPLS-based network test-bed, for the first time. The goal of the G-lambda project is to define a standard Web services interface (GNS-WSI) between GRS and NRM that is acceptable for both application service providers and commercial network operators, and which can be used as a tool for realizing new and emerging commercial services.     

Modeling and analysis of the effects of QoS and reliability on pricing, profitability, and risk management in multiperiod grid-computing networks

In this paper we develop a network equilibrium model for optimal pricing and resource allocation in Computational Grid Network. We consider a general network economy model with Grid Resource Providers, Grid Resource Brokers and Grid Users. The proposed framework allows for the modeling and theoretical analysis of Computational Grid Markets that considers a non-cooperative behavior of decision-makers in the same tier of the grid computing network (such as, for example, Grid Resource Providers) as well as cooperative behavior between tiers (between Resource Providers and Grid Brokers). We introduce risk management into the decision making process by analyzing the decision-marker's reliability and quality of service (QoS) requirement. We analyze resource allocation patterns as well as equilibrium price based on demand, supply, and cost structure of the grid computing market network. We specifically answer the following questions with several numerical examples: How do system reliability levels affect the QoS levels of the service providers and brokers under competition? How do system reliability levels affect the profits of resource providers and brokers in a competitive market? How do system reliability levels influence the pricing of the services in a competitive environment? How do users' service request types, QoS requirements, and timing concerns affect users' behaviors, costs and risks in equilibrium? How does the market mechanism allocate resources to satisfy the demands of users? We find that for users who request same services certain timing flexibility can not only reduce the costs but also lower the risks. The results indicated that the value of QoS can be efficiently priced based on the heterogeneous service demands.     

Reputation-based dependable scheduling of workflow applications in Peer-to-Peer Grids

Grids facilitate creation of wide-area collaborative environment for sharing computing or storage resources and various applications. Inter-connecting distributed Grid sites through peer-to-peer routing and information dissemination structure (also known as Peer-to-Peer Grids) is essential to avoid the problems of scheduling efficiency bottleneck and single point of failure in the centralized or hierarchical scheduling approaches. On the other hand, uncertainty and unreliability are facts in distributed infrastructures such as Peer-to-Peer Grids, which are triggered by multiple factors including scale, dynamism, failures, and incomplete global knowledge.In this paper, a reputation-based Grid workflow scheduling technique is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized Peer-to-Peer Grid environments. The proposed approach builds upon structured peer-to-peer indexing and networking techniques to create a scalable wide-area overlay of Grid sites for supporting dependable scheduling of applications. The scheduling algorithm considers reliability of a Grid resource as a statistical property, which is globally computed in the decentralized Grid overlay based on dynamic feedbacks or reputation scores assigned by individual service consumers mediated via Grid resource brokers. The proposed algorithm dynamically adapts to changing resource conditions and offers significant performance gains as compared to traditional approaches in the event of unsuccessful job execution or resource failure. The results evaluated through an extensive trace driven simulation show that our scheduling technique can reduce the makespan up to 50% and successfully isolate the failure-prone resources from the system.     

A secure information service for monitoring large scale grids

The Grid Information Service (GIS) is a core component in the Grid software infrastructure. It provides diverse information to users or other service components in Grid environments. In this paper, we propose a scalable GIS architecture for information management in a large scale Grid Virtual Organization (VO). This architecture consists of the VO layer, site layer and resource layer: at the resource layer, information agents and pluggable information sensors are deployed on each resource monitored. This information agent and sensor approach provides a flexible framework that enables specific information to be captured; at the site layer, a site information service component with caching capability aggregates and maintains up-to-date information of all the resources monitored within an administrative domain; at the VO layer, a peer-to-peer approach is used to build a virtual network of site information services for information discovery and query in a large scale Grid VO. This decentralized approach makes information management scalable and robust. Furthermore, we propose a security framework for the GIS, which provide security policies for authentication and authorization control of the GIS at both the site and the VO layers. Our GIS has been implemented based on the Globus Toolkit 4 as Web services compliant to Web Services Resource Framework (WSRF) specifications. The experimental results show that the GIS presents satisfactory scalability in handling information for large scale Grids.     

ON KNOWLEDGE GRID AND GRID INTELLIGENCE: A SURVEY

The next generation Web Intelligence (WI) aims at enabling users to go beyond the existing online information search and knowledge queries functionalities and to gain, from the Web, practical wisdom for problem solving. To support such a Wisdom Web, we envision that a grid-like computing infrastructure with intelligent service agencies is needed, where these agencies can interact, self-organize, learn, and evolve their course of actions, identities, and interrelationships for new knowledge creation, as well as scientific and social evolution. In this paper, we first provide an overview of recent development in WI and Semantic/Knowledge Grid. Then, the fundamental capabilities of the Wisdom Web as well as the conceptual architecture of an intelligent Grid for supporting it are described. Technical challenges for realizing Grid Intelligence are highlighted and the recent advancements in related research areas are reviewed.     

基于事件触发的网格资源监控研究

对于异构的高性能分布式计算环境——网格来说,监控其中每个计算节点获取资源的状态信息是至关重要的。然而传统的资源监控方式需要周期性地读取各个节点的信息,对网格系统资源浪费较大。本文提出一种基于事件触发的方法来降低监控服务开销,准确获取资源状态信息。然后采用该方法在Clobus Toolkit 4下实现网格资源监控系统,并对该系统做出客观评价。     

Service level agreement based adaptive Grid superscheduling

Grid computing brings heterogeneity and decentralization to the world of science and technology. It leverages every bit of idle computing resources and provides a straightforward middleware for integrating cross-domain scientific devices and legacy systems. In a super big Grid, job scheduling is challenging specifically when it needs to have access to vast amount of resources. The process of mapping jobs onto Grid resources requires significant consideration in terms of Grid architecture design, consumer demands and provider revenues. In this paper, we simultaneously utilize the legacy architecture of superscheduling, forwarding strategy, service level, success rate, and service pricing strategies and finally propose a service level agreement based on adaptive superscheduling (SAS) algorithm. SAS algorithm presents unified connectivity via efficient diffusion of jobs through the Grid infrastructure that is fueled from the previous scheduling events across the Grid. Moreover, by enforcing the service level agreement terms from a rich set of ask and bid prices, system performance, and load statistics, SAS successfully boosts revenue and utilization statistics. We perform an extensive experimental analysis for different Grid scales. Based on our experimental result, the SAS algorithm maximizes revenue while guarantees quality of service. More specifically, the quality of service is achieved through a high ratio of completed jobs and remarkable utilization of resources.     

A Market-Oriented Grid Directory Service for Publication and Discovery of Grid Service Providers and their Services

The emergence of Grids as a platform for sharing and aggregation of distributed resources increases the need for mechanisms that allow an efficient management of resources. The Grid economy has been identified as one of the potential solutions as it helps in managing the supply and demand for resources and enables sustained sharing of resources by providing economic incentive for Grid resource providers. An economy based Grid computing environment needs to support an infrastructure that enables the creation of a marketplace for meeting of providers and consumers. This paper presents the Grid Market Directory (GMD) that serves as a registry for publication and discovery of Grid service providers and their services.     

Service Science

This paper is a first exploration of the relationship between service science and Grid computing. Service science is the study of value co-creation interactions among entities, known as service systems. Within the emerging service science community, service is often defined as the application of competences (resources) for the benefit of another. Grid computing is the study of resource sharing among entities, known as virtual organizations, which solve complex business, societal, scientific, and engineering problems. Within the Grid computing community, service is sometimes defined as protocols plus behavior. Both Grid computing and service science are connecting academic, industry, government, and volunteer sector collaborators on a range of projects including eScience, healthcare, environmental sustainability, and more. This paper compares and contrasts the notions of resource, entity, service, interaction, and success criteria for the two areas of study. In conclusion, new areas for collaborative inquiry are proposed.     

QoS guided Min-Min heuristic for grid task scheduling

Task scheduling is an integrated component of computing.With the emergence of Grid and ubiquitous computing,new challenges appear in task scheduling based on properties such as security,quality of service,and lack of central control within distributed administrative domains.A Grid task scheduling framework must be able to deal with these issues.One of the goals of Grid task scheduling is to achivev high system throughput while matching applications with the available computing resources.This matching of resources in a non-deterministically shared heterogeneous environment leads to concerns over Quality of Service (QoS).In this paper a novel QoS guided task scheduling algorithm for Grid computing is introduced.The proposed novel algorithm is based on a general adaptive scheduling heuristics that includes QoS guidance.The algorithm is evaluated within a simulated Grid environment.The experimental results show that the nwe QoS guided Min-Min heuristic can lead to significant performance gain for a variety of applications.The approach is compared with others based on the quality of the prediction formulated by inaccurate information.     

面向服务的电信宽带网格研究与设计

本文首先从网格技术的发展历程出发,阐述了网格技术从计算和数据网格向服务网格发展的重要趋势。由宽带业务发展产生的新需求展开分析,指明了新型的服务网格技术对于宽带业务模式革新具有重大的支撑作用。从我们的研究课题出发,提出了面向服务的电信宽带网格整体技术架构,然后主要阐述了该架构应用服务层和应用基础架构层两个层次的主要功能和实现机制,具体包括内容分发服务网格、多媒体在线游戏服务网格、宽带小区协同服务网格三个应用和资源,用户,安全,业务管理等基础服务机制。最后总结了服务网格给电信宽带业务模式转变带来的重大革新价值和未来的发展方向。     

CWS服务平台的设计与实现——一个基于Web服务技术的计算资源共享系统

Web服务和网格计算技术,出现了日益融合的趋势,网格计算已经进入了服务为中心的新阶段。在这种情况下,就可以在具有良好跨平台性和互操作性的Web服务框架上实现计算资源的共享。论文提出了CWS服务和支撑CWS服务注册发布和共享运行的平台系统。在平台系统实现的过程中解决了几个关键问题。目前,已在北京大学计算机系的校园网内搭建了CWS服务平台,成功运行了多个服务实例。     

Portfolio and investment risk analysis on global grids

The financial services industry today produces and consumes huge amounts of data and the processes involved in analysing these data have large and complex resource requirements. The need to analyse the data using such processes and get meaningful results in time, can be met only up to a certain extent by current computer systems. Most service providers attempt to increase efficiency and quality of their service offerings by stacking up more hardware and employing better algorithms for data processing. However, there is a limit to the gains achieved by using such an approach. One viable alternative would be to use emerging technologies such as the Grid. Grid computing and its application to various domains have been actively studied by many groups for more than a decade now. In this paper we explore the use of the Grid in the financial services domain; an area which we believe has not been adequately looked into.     

Enhancing Availability of Grid Computational Services to Ubiquitous Computing Applications

The Grid is an integrated infrastructure that can play the dual roles of a coordinated resource consumer as well as a donator in distributed computing environments. The enormous growth in the use of mobile and embedded devices in ubiquitous computing environment and their interaction with human beings produces a huge amount of data that need to be processed efficiently anytime anywhere. However, such devices often have limited resources in terms of CPU, storage, battery power, and communication bandwidth. Thus, there is a need to transfer ubiquitous computing application services to more powerful computational resources. In this paper, we investigate the use of the Grid as a candidate for provisioning computational services to applications in ubiquitous computing environments. In particular, we present a competitive model that describes the possible interaction between the competing resources in the Grid Infrastructure as service providers and ubiquitous applications as subscribers. The competition takes place in terms of quality of service (QoS) and cost offered by different Grid Service Providers (GSPs). We also investigate the job allocation of different GSPs by exploiting the noncooperativeness among the strategies. We present the equilibrium behavior of our model facing global competition under stochastic demand and estimate guaranteed QoS assurance level by efficiently satisfying the requirement of ubiquitous application. We have also performed extensive experiments over Distributed Parallel Computing Cluster (DPCC) and studied overall job execution performance of different GSPs under a wide range of QoS parameters using different strategies. Our model and performance evaluation results can serve as a valuable reference for designing appropriate strategies in a practical grid environment.     

Survey on Grid Resource Allocation Mechanisms

Grid is a distributed high performance computing paradigm that offers various types of resources (like computing, storage, communication) to resource-intensive user tasks. These tasks are scheduled to allocate available Grid resources efficiently to achieve high system throughput and to satisfy user requirements. The task scheduling problem has become more complex with the ever increasing size of Grid systems. Even though selecting an efficient resource allocation strategy for a particular task helps in obtaining a desired level of service, researchers still face difficulties in choosing a suitable technique from a plethora of existing methods in literature. In this paper, we explore and discuss existing resource allocation mechanisms for resource allocation problems employed in Grid systems. The work comprehensively surveys Gird resource allocation mechanisms for different architectures (centralized, distributed, static or dynamic). The paper also compares these resource allocation mechanisms based on their common features such as time complexity, searching mechanism, allocation strategy, optimality, operational environment and objective function they adopt for solving computing- and data-intensive applications. The comprehensive analysis of cutting-edge research in the Grid domain presented in this work provides readers with an understanding of essential concepts of resource allocation mechanisms in Grid systems and helps them identify important and outstanding issues for further investigation. It also helps readers to choose the most appropriate mechanism for a given system/application.     

Quality of Service Negotiation for Commercial Medical Grid Services

The GEMSS project has developed a service-oriented Grid that supports the provision of medical simulation services by service providers to clients such as hospitals. We outline the GEMSS architecture, legal framework and the security features that characterise the GEMSS infrastructure. High levels of quality of service are required and we describe a reservation-based approach to quality of service, employing a quality of service management system that iteratively finds suitable reservations and uses application specific performance models. The GEMSS Grid is a commercial environment so we support flexible pricing models and a FIPA reverse English auction protocol. Signed Web Service Level Agreement contracts are exchanged to commit parties to a quality of service agreement before job execution occurs. We run four experiments across European countries using high performance computing resources running advanced resource reservation schedulers. These experiments provide evidence for our Grid’s rational behaviour, both at the level of service provider quality of service management and at the higher level of the client choosing between competing service providers. The results lend support to our economic model and the technology we use for our medical application domain.     

网格资源模型综述

网格计算将广域网上的各种计算资源、信息资源、设备资源等集成起来,以统一的方式向用户提供服务,是当前网络计算领域的研究热点.其中资源模型是关系到广域分布式环境中资源共享和协同工作效率的关键.本文介绍了网格中的资源模型的主要研究内容,以及国内外相关领域的研究现状.     

Entropic Grid Scheduling

Computational Grids (CGs) are large scale dynamical networks of geographically distributed peer resource clusters. These clusters are independent but cooperating computing systems bound by a management framework for the provision of computing services, called Grid Services. In its basic form, the Grid scheduling problem consists in finding at least one cluster that has the capacity to handle, within the constraints of a specified quality of service, a user service request submitted to the CG. Since CGs span distinct management domains, the scheduling process has to be decentralized. Furthermore, it has to account for the ubiquitous uncertainty on the state of the CG. In this paper, we propose a scalable distributed Entropy-based scheduling approach that utilizes a Markov chain model to capture the dynamics of the service capacity state. An entropy-based quantification of the uncertainty on the service capacity information is developed and explicitly integrated within the proposed Grid scheduling approach. The performance of the proposed scheduling strategy is validated, through simulation, against a random delegation scheme and a load balancing-based scheduling strategy with respect to throughput, exploitation and convergence speed, respectively.