29,225 research outputs found
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
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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
MonALISA : A Distributed Monitoring Service Architecture
The MonALISA (Monitoring Agents in A Large Integrated Services Architecture)
system provides a distributed monitoring service. MonALISA is based on a
scalable Dynamic Distributed Services Architecture which is designed to meet
the needs of physics collaborations for monitoring global Grid systems, and is
implemented using JINI/JAVA and WSDL/SOAP technologies. The scalability of the
system derives from the use of multithreaded Station Servers to host a variety
of loosely coupled self-describing dynamic services, the ability of each
service to register itself and then to be discovered and used by any other
services, or clients that require such information, and the ability of all
services and clients subscribing to a set of events (state changes) in the
system to be notified automatically. The framework integrates several existing
monitoring tools and procedures to collect parameters describing computational
nodes, applications and network performance. It has built-in SNMP support and
network-performance monitoring algorithms that enable it to monitor end-to-end
network performance as well as the performance and state of site facilities in
a Grid. MonALISA is currently running around the clock on the US CMS test Grid
as well as an increasing number of other sites. It is also being used to
monitor the performance and optimize the interconnections among the reflectors
in the VRVS system.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics
(CHEP03), La Jolla, Ca, USA, March 2003, 8 pages, pdf. PSN MOET00
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Distributed simulation and the grid: Position statements
The Grid provides a new and unrivaled technology for large scale distributed simulation as it enables collaboration and the use of distributed computing resources. This panel paper presents the views of four researchers in the area of Distributed Simulation and the Grid. Together we try to identify the main research issues involved in applying Grid technology to distributed simulation and the key future challenges that need to be solved to achieve this goal. Such challenges include not only technical challenges, but also political ones such as management methodology for the Grid and the development of standards. The benefits of the Grid to end-user simulation modelers also are discussed
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