17,319 research outputs found
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A classification of emerging and traditional grid systems
The grid has evolved in numerous distinct phases. It started in the early ’90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late ’90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to “glue” different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings.
However, third-generation grids’ current architecture doesn’t meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systems’ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area
Grid-enabling FIRST: Speeding up simulation applications using WinGrid
The vision of grid computing is to make computational power, storage capacity, data and applications available to users as readily as electricity and other utilities. Grid infrastructures and applications have traditionally been geared towards dedicated, centralized, high performance clusters running on UNIX flavour operating systems (commonly referred to as cluster-based grid computing). This can be contrasted with desktop-based grid computing which refers to the aggregation of non-dedicated, de-centralized, commodity PCs connected through a network and running (mostly) the Microsoft Windowstrade operating system. Large scale adoption of such Windowstrade-based grid infrastructure may be facilitated via grid-enabling existing Windows applications. This paper presents the WinGridtrade approach to grid enabling existing Windowstrade based commercial-off-the-shelf (COTS) simulation packages (CSPs). Through the use of a case study developed in conjunction with Ford Motor Company, the paper demonstrates how experimentation with the CSP Witnesstrade and FIRST can achieve a linear speedup when WinGridtrade is used to harness idle PC computing resources. This, combined with the lessons learned from the case study, has encouraged us to develop the Web service extensions to WinGridtrade. It is hoped that this would facilitate wider acceptance of WinGridtrade among enterprises having stringent security policies in place
Job Monitoring in an Interactive Grid Analysis Environment
The grid is emerging as a great computational resource but
its dynamic behavior makes the Grid environment unpredictable. Systems and networks can fail, and the
introduction of more users can result in resource starvation.
Once a job has been submitted for execution on the grid,
monitoring becomes essential for a user to see that the job is completed in an efficient way, and to detect any problems
that occur while the job is running. In current environments
once a user submits a job he loses direct control over the job and the system behaves like a batch system: the user
submits the job and later gets a result back. The only
information a user can obtain about a job is whether it is
scheduled, running, cancelled or finished. Today users are
becoming increasingly interested in such analysis grid
environments in which they can check the progress of the
job, obtain intermediate results, terminate the job based on
the progress of job or intermediate results, steer the job to
other nodes to achieve better performance and check the
resources consumed by the job. In order to fulfill their
requirements of interactivity a mechanism is needed that
can provide the user with real time access to information
about different attributes of a job. In this paper we present
the design of a Job Monitoring Service, a web service that
will provide interactive remote job monitoring by allowing
users to access different attributes of a job once it has been submitted to the interactive Grid Analysis Environment
Developing interest management techniques in distributed interactive simulation using Java
Bandwidth consumption in distributed real time simulation, or networked real time simulation, is a major problem as the number of participants and the sophistication of joint simulation exercises grow in size. The paper briefly reviews distributed real time simulation and bandwidth reduction techniques and introduces the Generic Runtime Infrastructure for Distributed Simulation (GRIDS) as a research architecture for studying such problems. GRIDS uses Java abstract classes to promote distributed services called thin agents, a novel approach to implementing distributed simulation services, such as user defined bandwidth reduction mechanisms, and to distributing the executable code across the simulation. Thin agents offer the advantages of traditional agents without the overhead imposed by mobility or continuous state, which are unnecessary in this context. We present our implementation and some predicted results from message reduction studies using thin agent
The AliEn system, status and perspectives
AliEn is a production environment that implements several components of the
Grid paradigm needed to simulate, reconstruct and analyse HEP data in a
distributed way. The system is built around Open Source components, uses the
Web Services model and standard network protocols to implement the computing
platform that is currently being used to produce and analyse Monte Carlo data
at over 30 sites on four continents. The aim of this paper is to present the
current AliEn architecture and outline its future developments in the light of
emerging standards.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics
(CHEP03), La Jolla, Ca, USA, March 2003, 10 pages, Word, 10 figures. PSN
MOAT00
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GRIDCC - Providing a real-time grid for distributed instrumentation
The GRIDCC project is extending the use of Grid computing to include access to and control of distributed instrumentation.
Access to the instruments will be via an interface to a Virtual Instrument Grid Service (VIGS). VIGS is a new concept and its design and implementation, together
with middleware that can provide the appropriate Quality of Service (QoS), is a key part of the GRIDCC development plan. An overall architecture for GRIDCC has been
defined and some of the application areas, which include distributed power systems, remote control of an accelerator and the remote monitoring of a large particle physics
experiment, are briefly discussed.E
Polish grid infrastructure for science and research
Structure, functionality, parameters and organization of the computing Grid
in Poland is described, mainly from the perspective of high-energy particle
physics community, currently its largest consumer and developer. It represents
distributed Tier-2 in the worldwide Grid infrastructure. It also provides
services and resources for data-intensive applications in other sciences.Comment: Proceeedings of IEEE Eurocon 2007, Warsaw, Poland, 9-12 Sep. 2007,
p.44
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