"Grid" computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high performance orientation. In this article, the authors define this new field. First, they review the "Grid problem," which is defined as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources--what is referred to as virtual organizations. In such settings, unique authentication, authorization, resource access, resource discovery, and other challenges are encountered. It is this class of problem that is addressed by Grid technologies. Next, the authors present an extensible and open Grid architecture, in which protocols, services, application programming interfaces, and software development kits are categorized according to their roles in enabling resource sharing. The authors describe requirements that they believe any such mechanisms must satisfy and discuss the importance of defining a compact set of intergrid protocols to enable interoperability among different Grid systems. Finally, the authors discuss how Grid technologies relate to other contemporary technologies, including enterprise integration, application service provider, storage service provider, and peer-to-peer computing. They maintain that Grid concepts and technologies complement and have much to contribute to these other approaches.

The Anatomy of the Grid: Enabling Scalable Virtual Organizations

Social Network Analysis

"Grid" computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation. In this article, we define this new field. First, we review the "Grid problem," which we define as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources-what we refer to as virtual organizations. In such settings, we encounter unique authentication, authorization, resource access, resource discovery, and other challenges. It is this class of problem that is addressed by Grid technologies. Next, we present an extensible and open Grid architecture, in which protocols, services, application programming interfaces, and software development kits are categorized according to their roles in enabling resource sharing. We describe requirements that we believe any such mechanisms must satisfy, and we discuss the central role played by the intergrid protocols that enable interoperability among different Grid systems. Finally, we discuss how Grid technologies relate to other contemporary technologies, including enterprise integration, application service provider, storage service provider, and peer-to-peer computing. We maintain that Grid concepts and technologies complement and have much to contribute to these other approaches.

The Anatomy of the Grid - Enabling Scalable Virtual Organizations

The Globus system is intended to achieve a vertically integrated treatment of application, middleware, and net work. A low-level toolkit provides basic mechanisms such as communication, authentication, network information, and data access. These mechanisms are used to con struct various higher level metacomputing services, such as parallel programming tools and schedulers. The long- term goal is to build an adaptive wide area resource environment AWARE, an integrated set of higher level services that enable applications to adapt to heteroge neous and dynamically changing metacomputing environ ments. Preliminary versions of Globus components were deployed successfully as part of the I-WAY networking experiment.

/pdf/globus-a-metacomputing-infrastructure-toolkit-3qznymodbn.pdf

Globus: a Metacomputing Infrastructure Toolkit

http://emamispnu.persiangig.com/Projects/Cloud%20Computing/science_2.pdf

Review: A survey on security issues in service delivery models of cloud computing

Large distributed systems such as Computational and Data Grids require a substantial amount of monitoring data be collected for a variety of tasks such as fault detection, performance analysis, performance tuning, performance prediction, and scheduling Some tools are currently available and others are being developed for collecting and forwarding this data The goal of this paper is to describe a common architecture with all the major components and their essential interactions in just enough detail that Grid Monitoring systems that follow the architecture described can easily devise common APIs and wire protocols To aid implementation, we also discuss the performance characteristics of a Grid Monitoring system and identify areas that are critical to proper functioning of the system

/pdf/white-paper-a-grid-monitoring-service-architecture-draft-5c9o949r94.pdf

White Paper: A Grid Monitoring Service Architecture (DRAFT)

The Logistical Computing and Internetworking (LoCI) project is a reflection of the way that the next generation internetworking fundamentally changes our definition of high performance wide area computing. A key to achieving this aim is the development of middleware that can provide reliable, flexible, scalable, and cost-effective delivery of data with quality of service (QoS) guarantees to support high performance applications of all types. The LoCI effort attacks this problem with a simple but innovative strategy. At the base of the LoCI project is a richer view of the use of storage in communication and information sharing.

Logistical computing and internetworking: middleware for the use of storage in communication

In this paper, we present the design of a system that automatically generates application-specific Linux images for scientific applications that execute using batched cluster resources. Key to our approach is the use of recurring patterns in program performance, i.e., phase-behavior, that can be exploited potentially to guide automatic Linux customization and to enable significantly higher levels in program performance. We overview project and present a set of preliminary results that show the potential of our approach.

/pdf/using-phase-behavior-in-scientific-application-to-guide-4crmx71rmt.pdf

Using phase behavior in scientific application to guide Linux operating system customization

Grid schedulers or resource allocators (whether they be human or automatic scheduling programs) must choose the right combination of resources from the available resource pool while the performance and availability characteristics of the individual resources within the pool change from moment to moment. Moreover, the scheduling decision for each application component must be made before the component is executed making scheduling a predictive activity. A Grid scheduler, therefore, must be able to predict what the deliverable resource performance will be for the time period in which a particular application component will eventually use the resource.In this chapter, we describe techniques for dynamically characterizing resources according to their predicted performance response to enable Grid scheduling and resource allocation. These techniques rely on three fundamental capabilities: extensible and non-intrusive performance monitoring, fast prediction models, and a flexible and high-performance reporting interface. We discuss these challenges in the context of the Network Weather Service (NWS) - an on-line performance monitoring and forecasting service developed for Grid environments. The NWS uses adaptive monitoring techniques to control intrusiveness, and non-parametric forecasting methods that are lightweight enough to generate forecasts in real-time. In addition, the service infrastructure used by the NWS is portable among all currently available Grid resources and is compatible with extant Grid middleware such as Globus, Legion, and Condor.

Performance information services for computational Grids

Data deduplication is important for snapshot backup of virtual machines (VMs) because of excessive redundant content. Fingerprint search for source-side duplicate detection is resource intensive when the backup service for VMs is co-located with other cloud services. This paper presents the design and analysis of a fast VM-centric backup service with a tradeoff for a competitive deduplication efficiency while using small computing resources, suitable for running on a converged cloud architecture that cohosts many other services. The design consideration includes VM-centric file system block management for the increased VM snapshot availability. This paper describes an evaluation of this VM-centric scheme to assess its deduplication efficiency, resource usage, and fault tolerance.

Rich Wolski

Papers

White Paper: A Grid Monitoring Service Architecture (DRAFT)

Logistical computing and internetworking: middleware for the use of storage in communication

Using phase behavior in scientific application to guide Linux operating system customization

Performance information services for computational Grids

VM-centric snapshot deduplication for cloud data backup