"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

We describe how the Grid enables new research possibilities in astronomy through multi-wavelength images. To see sky images in the same pixel space, they must be projected to that space, a computer-intensive process. There is thus a virtual data space induced that is defined by an image and the applied projection. This virtual data can be created and replicated with Planners and Replica catalog technology developed under the GriPhyN project. We plan to deploy our system (MONTAGE) on the U.S. Teragrid. Grid computing is also needed for ingesting data—computing background correction on each image—which forms a separate virtual data space. Multi-wavelength images can be used for pushing source detection and statistics by an order of magnitude from current techniques; for optimization of multi-wavelength image registration for detection and characterization of extended sources; and for detection of new classes of essentially multi-wavelength astronomical phenomena. The paper discusses both the Grid architecture and the scientific goals.

/pdf/multi-wavelength-image-space-another-grid-enabled-science-15hf5z4e7v.pdf

Multi-Wavelength Image Space: Another Grid-Enabled Science

One of the hallmarks of current science experiments is the large volume of data that must be managed. For example, next generation particle physics experiments will generate petabytes of data per year. These data sets form important community resources, so not only must be manage to store and process this data, but we must be able to share it as well. In this talk, I will introduce the concept of data grids, a distributed grid infrastructure for sharing and managing large data sets. Using several examples, I will present a data grid architecture and illustrate how it can be used to address a number of current applications.

Data Grids for Next Generation Problems in Science and Engineering

A growing gap between progress in biological knowledge and improved health outcomes inspired the new discipline of translational medicine, in which the application of new knowledge is an explicit part of a research plan. Abramson and Parashar argue that a similar gap between complex computational technologies and ever-more-challenging applications demands an analogous discipline of translational computer science, in which the deliberate movement of research results into large-scale practice becomes a central research focus rather than an afterthought. We revisit from this perspective the development and application of grid computing from the mid-1990s onwards, and find that a translational framing is useful for understanding the technology's development and impact. We discuss how the development of grid computing infrastructure, and the Globus Toolkit, in particular, benefited from a translational approach. We identify lessons learned that can be applied to other translational computer science initiatives.

Translating the Grid: How a Translational Approach Shaped the Development of Grid Computing

Proceedings of the 16th International Symposium on High-Performance Distributed Computing (HPDC-16 2007), 25-29 June 2007, Monterey, California, USA

The scientific paradigms of the Semantic Web, Web Services,
Agents, Peer-to-Peer Networks and Grid Computing are currently
receiving a lot of attention in the research community, and are
producing solutions to important problems ranging from e-science
to e-business. The United States DAML program, the European
Commission and other organisations have also been investing
heavily in these technologies. This Dagstuhl Seminar brought
together world-leading experts from the diverse organizations and
research areas. It strengthened the international collaboration
with the aim to realize the vision of the Semantic Grid.

Carl Kesselman

Papers

Multi-Wavelength Image Space: Another Grid-Enabled Science

Data Grids for Next Generation Problems in Science and Engineering

Translating the Grid: How a Translational Approach Shaped the Development of Grid Computing

Proceedings of the 16th International Symposium on High-Performance Distributed Computing (HPDC-16 2007), 25-29 June 2007, Monterey, California, USA

05271 - Report on the Dagstuhl Seminar on Semantic Grid - Convergence of Technologies