3,900 research outputs found
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
Resource Brokering in Grid Computing
Grid Computing has emerged in the academia and evolved towards the bases of what is currently known as Cloud Computing and Internet of Things (IoT). The vast collection of resources that provide the nature for Grid Computing environment is very complex; multiple administrative domains control access and set policies to the shared computing resources. It is a decentralized environment with geographically distributed computing and storage resources, where each computing resource can be modeled as an autonomous computing entity, yet collectively can work together. This is a class of Cooperative Distributed Systems (CDS). We extend this by applying characteristic of open environments to create a foundation for the next generation of computing platform where entities are free to join a computing environment to provide capabilities and take part as a collective in solving complex problems beyond the capability of a single entity.
This thesis is focused on modeling “Computing” as a collective performance of individual autonomous fundamental computing elements interconnected in a “Grid” open environment structure. Each computing element is a node in the Grid. All nodes are interconnected through the “Grid” edges. Resource allocation is done at the edges of the “Grid” where the connected nodes are simply used to perform computation.
The analysis put forward in this thesis identifies Grid Computing as a form of computing that occurs at the resource level. The proposed solution, coupled with advancements in technology and evolution of new computing paradigms, sets a new direction for grid computing research. The approach here is a leap forward with the well-defined set of requirements and specifications based on open issues with the focus on autonomy, adaptability and interdependency. The proposed approach examines current model for Grid Protocol Architecture and proposes an extension that addresses the open issues in the diverged set of solutions that have been created
A framework for evolving grid computing systems.
Grid computing was born in the 1990s, when researchers were looking for a way to share expensive computing resources and experiment equipment. Grid computing is becoming increasingly popular because it promotes the sharing of distributed resources that may be heterogeneous in nature, and it enables scientists and engineering professionals to solve large scale computing problems. In reality, there are already huge numbers of grid computing facilities distributed around the world,
each one having been created to serve a particular group of scientists such as weather forecasters, or a group of users such as stock markets. However, the need to extend the functionalities of current grid systems lends itself to the consideration of grid evolution. This allows the combination of many disjunct grids into a single powerful grid that can operate as one vast computational resource, as well as for grid environments to be flexible, to be able to change and to evolve. The rationale for grid evolution is the current rapid and increasing advances in both software and hardware.
Evolution means adding or removing capabilities. This research defines grid evolution as adding new functions and/or equipment and removing unusable resources that affect the performance of some nodes. This thesis produces a new technique for grid evolution, allowing it to be seamless and to operate at run time. Within grid computing, evolution is an integration of software and hardware and can be of two distinct types, external and internal. Internal evolution occurs inside the grid boundary by migrating special resources such as application software from node to node inside the grid. While external evolution occurs between grids.
This thesis develops a framework for grid evolution that insulates users from the complexities of grids. This framework has at its core a resource broker together with a grid monitor to cope with internal and external evolution, advance reservation, fault tolerance, the monitoring of the grid environment, increased resource utilisation and the high availability of grid resources.
The starting point for the present framework of grid evolution is when the grid receives a job whose requirements do not exist on the required node which triggers grid evolution. If the grid has all the requirements scattered across its nodes, internal evolution enabling the grid to migrate the required resources to the required node in order to satisfy job requirements ensues, but if the grid does not have these resources, external evolution enables the grid either to collect them from other grids
(permanent evolution) or to send the job to other grids for execution (just in time) evolution.
Finally a simulation tool called (EVOSim) has been designed, developed and tested. It is written in Oracle 10g and has been used for the creation of four grids, each of which has a different setup including different nodes, application software, data and polices. Experiments were done by submitting jobs to the grid at run time, and then comparing the results and analysing the performance of those grids that use the approach of evolution with those that do not. The results of these experiments have demonstrated that these features significantly improve the performance of grid environments and provide excellent scheduling results, with a decreasing number of rejected jobs
AstroGrid-D: Grid Technology for Astronomical Science
We present status and results of AstroGrid-D, a joint effort of
astrophysicists and computer scientists to employ grid technology for
scientific applications. AstroGrid-D provides access to a network of
distributed machines with a set of commands as well as software interfaces. It
allows simple use of computer and storage facilities and to schedule or monitor
compute tasks and data management. It is based on the Globus Toolkit middleware
(GT4). Chapter 1 describes the context which led to the demand for advanced
software solutions in Astrophysics, and we state the goals of the project. We
then present characteristic astrophysical applications that have been
implemented on AstroGrid-D in chapter 2. We describe simulations of different
complexity, compute-intensive calculations running on multiple sites, and
advanced applications for specific scientific purposes, such as a connection to
robotic telescopes. We can show from these examples how grid execution improves
e.g. the scientific workflow. Chapter 3 explains the software tools and
services that we adapted or newly developed. Section 3.1 is focused on the
administrative aspects of the infrastructure, to manage users and monitor
activity. Section 3.2 characterises the central components of our architecture:
The AstroGrid-D information service to collect and store metadata, a file
management system, the data management system, and a job manager for automatic
submission of compute tasks. We summarise the successfully established
infrastructure in chapter 4, concluding with our future plans to establish
AstroGrid-D as a platform of modern e-Astronomy.Comment: 14 pages, 12 figures Subjects: data analysis, image processing,
robotic telescopes, simulations, grid. Accepted for publication in New
Astronom
Advances in Grid Computing
This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems
Economic-based Distributed Resource Management and Scheduling for Grid Computing
Computational Grids, emerging as an infrastructure for next generation
computing, enable the sharing, selection, and aggregation of geographically
distributed resources for solving large-scale problems in science, engineering,
and commerce. As the resources in the Grid are heterogeneous and geographically
distributed with varying availability and a variety of usage and cost policies
for diverse users at different times and, priorities as well as goals that vary
with time. The management of resources and application scheduling in such a
large and distributed environment is a complex task. This thesis proposes a
distributed computational economy as an effective metaphor for the management
of resources and application scheduling. It proposes an architectural framework
that supports resource trading and quality of services based scheduling. It
enables the regulation of supply and demand for resources and provides an
incentive for resource owners for participating in the Grid and motives the
users to trade-off between the deadline, budget, and the required level of
quality of service. The thesis demonstrates the capability of economic-based
systems for peer-to-peer distributed computing by developing users'
quality-of-service requirements driven scheduling strategies and algorithms. It
demonstrates their effectiveness by performing scheduling experiments on the
World-Wide Grid for solving parameter sweep applications
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