106,500 research outputs found
A monitoring tool for a GRID operation center
WorldGRID is an intercontinental testbed spanning Europe and the US
integrating architecturally different Grid implementations based on the Globus
toolkit. The WorldGRID testbed has been successfully demonstrated during the
WorldGRID demos at SuperComputing 2002 (Baltimore) and IST2002 (Copenhagen)
where real HEP application jobs were transparently submitted from US and Europe
using "native" mechanisms and run where resources were available, independently
of their location. To monitor the behavior and performance of such testbed and
spot problems as soon as they arise, DataTAG has developed the EDT-Monitor tool
based on the Nagios package that allows for Virtual Organization centric views
of the Grid through dynamic geographical maps. The tool has been used to spot
several problems during the WorldGRID operations, such as malfunctioning
Resource Brokers or Information Servers, sites not correctly configured, job
dispatching problems, etc. In this paper we give an overview of the package,
its features and scalability solutions and we report on the experience acquired
and the benefit that a GRID operation center would gain from such a tool.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics
(CHEP03), La Jolla, Ca, USA, March 2003, 3 pages, PDF. PSN MOET00
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An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014
Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems
Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions
Security aspects in cloud based condition monitoring of machine tools
In the modern competitive environments companies must have rapid production systems that are able to deliver parts that satisfy highest quality standards. Companies have also an increased need for advanced machines equipped with the latest technologies in maintenance to avoid any reduction or interruption of production. Eminent therefore is the need to monitor the health status of the manufacturing equipment in real time and thus try to develop diagnostic technologies for machine tools. This paper lays the foundation for the creation of a safe remote monitoring system for machine tools using a Cloud environment for communication between the customer and the maintenance service company. Cloud technology provides a convenient means for accessing maintenance data anywhere in the world accessible through simple devices such as PC, tablets or smartphones. In this context the safety aspects of a Cloud system for remote monitoring of machine tools becomes crucial and is, thus the focus of this pape
Development of Grid e-Infrastructure in South-Eastern Europe
Over the period of 6 years and three phases, the SEE-GRID programme has
established a strong regional human network in the area of distributed
scientific computing and has set up a powerful regional Grid infrastructure. It
attracted a number of user communities and applications from diverse fields
from countries throughout the South-Eastern Europe. From the infrastructure
point view, the first project phase has established a pilot Grid infrastructure
with more than 20 resource centers in 11 countries. During the subsequent two
phases of the project, the infrastructure has grown to currently 55 resource
centers with more than 6600 CPUs and 750 TBs of disk storage, distributed in 16
participating countries. Inclusion of new resource centers to the existing
infrastructure, as well as a support to new user communities, has demanded
setup of regionally distributed core services, development of new monitoring
and operational tools, and close collaboration of all partner institution in
managing such a complex infrastructure. In this paper we give an overview of
the development and current status of SEE-GRID regional infrastructure and
describe its transition to the NGI-based Grid model in EGI, with the strong SEE
regional collaboration.Comment: 22 pages, 12 figures, 4 table
HIL: designing an exokernel for the data center
We propose a new Exokernel-like layer to allow mutually untrusting physically deployed services to efficiently share the resources of a data center. We believe that such a layer offers not only efficiency gains, but may also enable new economic models, new applications, and new security-sensitive uses. A prototype (currently in active use) demonstrates that the proposed layer is viable, and can support a variety of existing provisioning tools and use cases.Partial support for this work was provided by the MassTech Collaborative Research Matching Grant Program, National Science Foundation awards 1347525 and 1149232 as well as the several commercial partners of the Massachusetts Open Cloud who may be found at http://www.massopencloud.or
Visualization & Automation of Shams Dubai Report
Dubai’s Smart Grid strategy includes the implementation of Distributed Energy Resources and Distribution Automation (DA) facilities to continuous monitoring and remote control from DEWA’s Distribution Control Center (DCC) , and, in some cases, automatic control of electric distribution assets operated at 33kV or lower. The increase level of telemetry and automation in the field imposes a greater challenge in monitoring and live data visualization for establishing a decision support system that empowers distribution system operators and enables optimal control of existing and planned assets. This challenge can be overcome through introducing data science tools in the sector of energy. Through imposing certain reporting and visualization tool, the data generated utilization level is improved which will lead to an increase in reliability and efficiency, rise asset utilization, workforce productivity, decision making, thus, increase customer satisfaction.
The use case covered during this capstone proposal is one of the daily reports generated by distribution operation department manually on the daily bases. During this project, data science tools will be benchmarked accordingly to distribution power utility needs of reporting and anticipating certain parameters such as distribution solar generation and key performance indicators (SAIDI, SAIFI, CML, MTTR, MTBF etc.). The selected tool will be utilized to generate live reports/ dashboards and to decrease the level of manpower intervention. This proposal will highlights the background of the project, problem statement, project definition and goals and explains project methodology and evaluation followed by project deliverables & timeline
Technical support for Life Sciences communities on a production grid infrastructure
Production operation of large distributed computing infrastructures (DCI)
still requires a lot of human intervention to reach acceptable quality of
service. This may be achievable for scientific communities with solid IT
support, but it remains a show-stopper for others. Some application execution
environments are used to hide runtime technical issues from end users. But they
mostly aim at fault-tolerance rather than incident resolution, and their
operation still requires substantial manpower. A longer-term support activity
is thus needed to ensure sustained quality of service for Virtual Organisations
(VO). This paper describes how the biomed VO has addressed this challenge by
setting up a technical support team. Its organisation, tooling, daily tasks,
and procedures are described. Results are shown in terms of resource usage by
end users, amount of reported incidents, and developed software tools. Based on
our experience, we suggest ways to measure the impact of the technical support,
perspectives to decrease its human cost and make it more community-specific.Comment: HealthGrid'12, Amsterdam : Netherlands (2012
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