3,122 research outputs found
High-Performance Cloud Computing: A View of Scientific Applications
Scientific computing often requires the availability of a massive number of
computers for performing large scale experiments. Traditionally, these needs
have been addressed by using high-performance computing solutions and installed
facilities such as clusters and super computers, which are difficult to setup,
maintain, and operate. Cloud computing provides scientists with a completely
new model of utilizing the computing infrastructure. Compute resources, storage
resources, as well as applications, can be dynamically provisioned (and
integrated within the existing infrastructure) on a pay per use basis. These
resources can be released when they are no more needed. Such services are often
offered within the context of a Service Level Agreement (SLA), which ensure the
desired Quality of Service (QoS). Aneka, an enterprise Cloud computing
solution, harnesses the power of compute resources by relying on private and
public Clouds and delivers to users the desired QoS. Its flexible and service
based infrastructure supports multiple programming paradigms that make Aneka
address a variety of different scenarios: from finance applications to
computational science. As examples of scientific computing in the Cloud, we
present a preliminary case study on using Aneka for the classification of gene
expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape
BEHAVIORAL CHARACTERIZATION OF ATTACKS ON THE REMOTE DESKTOP PROTOCOL
The Remote Desktop Protocol (RDP) is popular for enabling remote access and administration of Windows systems; however, attackers can take advantage of RDP to cause harm to critical systems using it. Detection and classification of RDP attacks is a challenge because most RDP traffic is encrypted, and it is not always clear which connections to a system are malicious after manual decryption of RDP traffic. In this research, we used open-source tools to generate and analyze RDP attack data using a power-grid honeypot under our control. We developed methods for detecting and characterizing RDP attacks through malicious signatures, Windows event log entries, and network traffic metadata. Testing and evaluation of our characterization methods on actual attack data collected by four instances of our honeypot showed that we could effectively delineate benign and malicious RDP traffic and classify the severity of RDP attacks on unprotected or misconfigured Windows systems. The classification of attack patterns and severity levels can inform defenders of adversarial behavior in RDP attacks. Our results can also help protect national critical infrastructure, including Department of Defense systems.DOE, Washington DC 20805Civilian, SFSApproved for public release. Distribution is unlimited
Grids and the Virtual Observatory
We consider several projects from astronomy that benefit from the Grid paradigm and
associated technology, many of which involve either massive datasets or the federation
of multiple datasets. We cover image computation (mosaicking, multi-wavelength
images, and synoptic surveys); database computation (representation through XML,
data mining, and visualization); and semantic interoperability (publishing, ontologies,
directories, and service descriptions)
Exploring the Design Space of Immersive Urban Analytics
Recent years have witnessed the rapid development and wide adoption of
immersive head-mounted devices, such as HTC VIVE, Oculus Rift, and Microsoft
HoloLens. These immersive devices have the potential to significantly extend
the methodology of urban visual analytics by providing critical 3D context
information and creating a sense of presence. In this paper, we propose an
theoretical model to characterize the visualizations in immersive urban
analytics. Further more, based on our comprehensive and concise model, we
contribute a typology of combination methods of 2D and 3D visualizations that
distinguish between linked views, embedded views, and mixed views. We also
propose a supporting guideline to assist users in selecting a proper view under
certain circumstances by considering visual geometry and spatial distribution
of the 2D and 3D visualizations. Finally, based on existing works, possible
future research opportunities are explored and discussed.Comment: 23 pages,11 figure
A review of software project testing
In this article a review of software projects based on a taxonomy project is established, allowing the development team or testing personnel to identify the tests to which the project must be subjected for validation. The taxonomy is focused on identifying software projects according to their technology. To establish the taxonomy, a development method comprised of 5 phases was applied
PFS: A Productivity Forecasting System For Desktop Computers To Improve Grid Applications Performance In Enterprise Desktop Grid
An Enterprise Desktop Grid (EDG) is a low cost platform that gathers desktop computers spread over different institutions. This platform uses desktop computers idle time to run Grid applications. We argue that computers in these environments have a predictable productivity that affects a Grid application execution time. In this paper, we propose a system called PFS for computer productivity forecasting that improves Grid applications performance. We simulated 157.500 applications and compared the performance achieved by our proposal against two recent strategies. Our experiments show that a Grid scheduler based on PFS runs applications faster than schedulers based on other selection strategies.Fil: Salinas, Sergio Ariel. Universidad Nacional de Cuyo; ArgentinaFil: Garcia Garino, Carlos Gabriel. Universidad Nacional de Cuyo; ArgentinaFil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentin
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