High Performance Graphical Data Trending in a Distributed System
Identifieur interne : 000B06 ( Main/Exploration ); précédent : 000B05; suivant : 000B07High Performance Graphical Data Trending in a Distributed System
Auteurs : Cristián Maureira [Chili] ; Arturo Hoffstadt [Chili] ; Joao Lopez [Chili] ; Nicolás Troncoso [Chili] ; Rodrigo Tobar [Allemagne] ; Horst H. Von Brand [Chili]Source :
- Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2010.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Langage de programmation.
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Abstract
Trending near real-time data is a complex task, specially in distributed environments. This problem was typically tackled in financial and transaction systems, but it now applies to its utmost in other contexts, such as hardware monitoring in large-scale projects. Data handling requires subscription to specific data feeds that need to be implemented avoiding replication, and rate of transmission has to be assured. On the side of the graphical client, rendering needs to be fast enough so it may be perceived as real-time processing and display. ALMA Common Software (ACS) provides a software infrastructure for distributed projects which may require trending large volumes of data. For theses requirements ACS offers a Sampling System, which allows sampling selected data feeds at different frequencies. Along with this, it provides a graphical tool to plot the collected information, which needs to perform as well as possible. Currently there are many graphical libraries available for data trending. This imposes a problem when trying to choose one: It is necessary to know which has the best performance, and which combination of programming language and library is the best decision. This document analyzes the performance of different graphical libraries and languages in order to present the optimal environment when writing or re-factoring an application using trending technologies in distributed systems. To properly address the complexity of the problem, a specific set of alternative was pre-selected, including libraries in Java and Python, languages which are part of ACS. A stress benchmark will be developed in a simulated distributed environment using ACS in order to test the trending libraries.
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(AUI), Santiago, Chile; Universidad Técnica Federico Santa Maria</s1><s2>Valparaiso</s2><s3>CHL</s3><sZ>4 aut.</sZ></inist:fA14><country>Chili</country><wicri:noRegion>Valparaiso</wicri:noRegion></affiliation></author><author><name sortKey="Tobar, Rodrigo" sort="Tobar, Rodrigo" uniqKey="Tobar R" first="Rodrigo" last="Tobar">Rodrigo Tobar</name><affiliation wicri:level="1"><inist:fA14 i1="03"><s1>European Southern Observatory</s1><s2>Garching bei München</s2><s3>DEU</s3><sZ>5 aut.</sZ></inist:fA14><country>Allemagne</country><wicri:noRegion>Garching bei München</wicri:noRegion><wicri:noRegion>European Southern Observatory</wicri:noRegion><wicri:noRegion>European Southern Observatory</wicri:noRegion></affiliation></author><author><name sortKey="Von Brand, Horst H" sort="Von Brand, Horst H" uniqKey="Von Brand H" first="Horst H." last="Von Brand">Horst H. Von Brand</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Computer Systems Research Group, Universidad Técnica Federico Santa Maria</s1><s2>Valparaíso</s2><s3>CHL</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>6 aut.</sZ></inist:fA14><country>Chili</country><wicri:noRegion>Valparaíso</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">Proceedings of SPIE, the International Society for Optical Engineering</title><title level="j" type="abbreviated">Proc. SPIE Int. Soc. Opt. Eng.</title><idno type="ISSN">0277-786X</idno><imprint><date when="2010">2010</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Proceedings of SPIE, the International Society for Optical Engineering</title><title level="j" type="abbreviated">Proc. SPIE Int. Soc. Opt. Eng.</title><idno type="ISSN">0277-786X</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Data handling</term><term>Distributed algorithm</term><term>Distributed system</term><term>Graphical language</term><term>High performance</term><term>JAVA language</term><term>Monitoring</term><term>Processing time</term><term>Programming language</term><term>Real time</term><term>Replication</term><term>Sampling</term><term>Software infrastructure</term><term>Transaction processing</term><term>Transmission rate</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Haute performance</term><term>Système réparti</term><term>Temps réel</term><term>Traitement transaction</term><term>Monitorage</term><term>Maniement donnée</term><term>Réplication</term><term>Temps traitement</term><term>Infrastructure logiciel</term><term>Langage programmation</term><term>Langage graphique</term><term>Langage JAVA</term><term>Taux transmission</term><term>Algorithme réparti</term><term>Echantillonnage</term><term>.</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Langage de programmation</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Trending near real-time data is a complex task, specially in distributed environments. This problem was typically tackled in financial and transaction systems, but it now applies to its utmost in other contexts, such as hardware monitoring in large-scale projects. Data handling requires subscription to specific data feeds that need to be implemented avoiding replication, and rate of transmission has to be assured. On the side of the graphical client, rendering needs to be fast enough so it may be perceived as real-time processing and display. ALMA Common Software (ACS) provides a software infrastructure for distributed projects which may require trending large volumes of data. For theses requirements ACS offers a Sampling System, which allows sampling selected data feeds at different frequencies. Along with this, it provides a graphical tool to plot the collected information, which needs to perform as well as possible. Currently there are many graphical libraries available for data trending. This imposes a problem when trying to choose one: It is necessary to know which has the best performance, and which combination of programming language and library is the best decision. This document analyzes the performance of different graphical libraries and languages in order to present the optimal environment when writing or re-factoring an application using trending technologies in distributed systems. To properly address the complexity of the problem, a specific set of alternative was pre-selected, including libraries in Java and Python, languages which are part of ACS. A stress benchmark will be developed in a simulated distributed environment using ACS in order to test the trending libraries.</div></front></TEI><affiliations><list><country><li>Allemagne</li><li>Chili</li></country></list><tree><country name="Chili"><noRegion><name sortKey="Maureira, Cristian" sort="Maureira, Cristian" uniqKey="Maureira C" first="Cristián" last="Maureira">Cristián Maureira</name></noRegion><name sortKey="Hoffstadt, Arturo" sort="Hoffstadt, Arturo" uniqKey="Hoffstadt A" first="Arturo" last="Hoffstadt">Arturo Hoffstadt</name><name sortKey="Lopez, Joao" sort="Lopez, Joao" uniqKey="Lopez J" first="Joao" last="Lopez">Joao Lopez</name><name sortKey="Troncoso, Nicolas" sort="Troncoso, Nicolas" uniqKey="Troncoso N" first="Nicolás" last="Troncoso">Nicolás Troncoso</name><name sortKey="Von Brand, Horst H" sort="Von Brand, Horst H" uniqKey="Von Brand H" first="Horst H." last="Von Brand">Horst H. Von Brand</name></country><country name="Allemagne"><noRegion><name sortKey="Tobar, Rodrigo" sort="Tobar, Rodrigo" uniqKey="Tobar R" first="Rodrigo" last="Tobar">Rodrigo Tobar</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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