"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

A 2001 IBM manifesto observed that a looming software complexity crisis -caused by applications and environments that number into the tens of millions of lines of code - threatened to halt progress in computing. The manifesto noted the almost impossible difficulty of managing current and planned computing systems, which require integrating several heterogeneous environments into corporate-wide computing systems that extend into the Internet. Autonomic computing, perhaps the most attractive approach to solving this problem, creates systems that can manage themselves when given high-level objectives from administrators. Systems manage themselves according to an administrator's goals. New components integrate as effortlessly as a new cell establishes itself in the human body. These ideas are not science fiction, but elements of the grand challenge to create self-managing computing systems.

The vision of autonomic computing

http://cloud.pubs.dbs.uni-leipzig.de/sites/cloud.pubs.dbs.uni-leipzig.de/files/Brandic2008CloudcomputingandemergingITplatformsVisionhypeand.pdf

Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility

物件導向軟體之架構(Object-Oriented Software Construction)探討

Cloud computing is a recent advancement wherein IT infrastructure and applications are provided as ‘services’ to end-users under a usage-based payment model. It can leverage virtualized services even on the fly based on requirements (workload patterns and QoS) varying with time. The application services hosted under Cloud computing model have complex provisioning, composition, configuration, and deployment requirements. Evaluating the performance of Cloud provisioning policies, application workload models, and resources performance models in a repeatable manner under varying system and user configurations and requirements is difficult to achieve. To overcome this challenge, we propose CloudSim: an extensible simulation toolkit that enables modeling and simulation of Cloud computing systems and application provisioning environments. The CloudSim toolkit supports both system and behavior modeling of Cloud system components such as data centers, virtual machines (VMs) and resource provisioning policies. It implements generic application provisioning techniques that can be extended with ease and limited effort. Currently, it supports modeling and simulation of Cloud computing environments consisting of both single and inter-networked clouds (federation of clouds). Moreover, it exposes custom interfaces for implementing policies and provisioning techniques for allocation of VMs under inter-networked Cloud computing scenarios. Several researchers from organizations, such as HP Labs in U.S.A., are using CloudSim in their investigation on Cloud resource provisioning and energy-efficient management of data center resources. The usefulness of CloudSim is demonstrated by a case study involving dynamic provisioning of application services in the hybrid federated clouds environment. The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns. Copyright © 2010 John Wiley & Sons, Ltd.

https://beloglazov.info/papers/2010-cloudsim-spe.pdf

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

Computational grids are becoming an increasingly important and powerful platform for the execution of large-scale, resource-intensive applications. However, it remains a challenge for applications to tap into the potential of grid resources in order to achieve performance. In this paper, we illustrate how work queue applications can leverage grids to achieve performance through coallocation. We describe our experiences in developing a scheduling strategy for a production tomography application targeted at grids that contain both workstations and parallel supercomputers. Our strategy uses dynamic information exported by a supercomputer's batch scheduler to simultaneously schedule tasks on workstations and immediately-available supercomputer nodes. This strategy is of great practical interest because it combines resources that are available in a typical research laboratory: time-shared workstations and CPU time in remote space-shared supercomputers. We show that this strategy improves the performance of the tomography application compared to traditional scheduling strategies, which target the application to either type of resource alone.

/pdf/combining-workstations-and-supercomputers-to-support-grid-4vpqp1r7pw.pdf

Combining workstations and supercomputers to support grid applications: the parallel tomography experience

Publisher Summary This chapter provides an overview of the purpose, evolution, architecture, and implementation of Grid systems. Grid technologies provide mechanisms for sharing and coordinating the use of diverse resources and thus, enable the creation, from geographically and organizationally distributed components, of virtual computing systems that are sufficiently integrated to deliver the desired qualities of service. These technologies include security solutions that support the management of credentials and policies when computations span multiple institutions; resource management protocols and services that support secure remote access to computing and data resources and the co-allocation of multiple resources; information query protocols and services that provide configuration and status information about resources, organizations, and services; and data management services that locate and transport data sets between storage systems and applications.

Concepts and Architecture

Proceedings of the 16th International Conference on Scientific and Statistical Database Management (SSDBM’04)

Earthquake engineers have traditionally investigated the behavior of structures with either computational simulations or physical experiments. Recently, a new hybrid approach has been proposed that allows tests to be decomposed into independent substructures that can be located at different test facilities, tested separately, and integrated via a computational simulation. We describe a grid-based architecture for performing such novel distributed hybrid computational/physical experiments. We discuss the requirements that underlie this extremely challenging application of grid technologies, describe our architecture and implementation, and discuss our experiences with the application of this architecture within an unprecedented earthquake engineering test that coupled large-scale physical experiments in Illinois and Colorado with a computational simulation. Our results point to the remarkable impacts that grid technologies can have on the practice of engineering, and also contribute to our understanding of how to build and deploy effective grid applications.

/pdf/distributed-hybrid-earthquake-engineering-experiments-3owpdz16ro.pdf

Distributed hybrid earthquake engineering experiments: experiences with a ground-shaking grid application

Our increased ability to model and measure a wide variety of phenomena has left us awash in data. In the immediate future, the authors anticipate collecting data at the rate of terabytes per day from many classes of applications, including simulations running on teraFLOPS-class computers and experimental data produced by increasingly more sensitive and accurate instruments, such as telescopes, microscopes, particle accelerators and satellites. Generating or acquiring data is not an end in itself but a vehicle for obtaining insights. While data analysis and reduction have a role to play, in many situations we achieve understanding only when a human being interprets the data. Visualization has emerged as an important tool for extracting meaning from the large volumes of data that scientific instruments and simulations produce. The authors describe an online system that supports 3D tomographic image reconstruction-and subsequent collaborative analysis-of data from remote scientific instruments.

/pdf/distance-visualization-data-exploration-on-the-grid-4zv0bsz58m.pdf

Carl Kesselman

Papers

Combining workstations and supercomputers to support grid applications: the parallel tomography experience

Concepts and Architecture

Proceedings of the 16th International Conference on Scientific and Statistical Database Management (SSDBM’04)

Distributed hybrid earthquake engineering experiments: experiences with a ground-shaking grid application

Distance visualization: data exploration on the grid