Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00076291" target="_blank" >RIV/00216224:14330/14:00076291 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.5220/0005095504700481" target="_blank" >http://dx.doi.org/10.5220/0005095504700481</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0005095504700481" target="_blank" >10.5220/0005095504700481</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters
Popis výsledku v původním jazyce
The use of stream processing for state monitoring of distributed infrastructures has been advocated by some in order to overcome the issues of traditional monitoring solutions when tasked with complex continuous queries. However, in the domain of behavior monitoring the situation gets more complicated. It is mainly because of the low-quality source of behavior-related monitoring information (natural language computer logs). Existing approaches prevalently rely on indexing and real-time data-mining of the behavior-related data rather than on using event/stream processing techniques and the many corresponding benefits. The goal of this paper is to present a general notion of Distributed Event-Driven Monitoring Architecture that will enable an easy definition of expressive continuous queries over many distributed and heterogeneous streams of behavior-related (and state-related) monitoring data.
Název v anglickém jazyce
Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters
Popis výsledku anglicky
The use of stream processing for state monitoring of distributed infrastructures has been advocated by some in order to overcome the issues of traditional monitoring solutions when tasked with complex continuous queries. However, in the domain of behavior monitoring the situation gets more complicated. It is mainly because of the low-quality source of behavior-related monitoring information (natural language computer logs). Existing approaches prevalently rely on indexing and real-time data-mining of the behavior-related data rather than on using event/stream processing techniques and the many corresponding benefits. The goal of this paper is to present a general notion of Distributed Event-Driven Monitoring Architecture that will enable an easy definition of expressive continuous queries over many distributed and heterogeneous streams of behavior-related (and state-related) monitoring data.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
JC - Počítačový hardware a software
OECD FORD obor
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Návaznosti výsledku
Projekt
<a href="/cs/project/LG13010" target="_blank" >LG13010: Zastoupení ČR v European Research Consortium for Informatics and Mathematics</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2014
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
ICSOFT-EA 2014 - Proceedings of the 9th International Conference on Software Engineering and Applications
ISBN
9789897580369
ISSN
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e-ISSN
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Počet stran výsledku
12
Strana od-do
470-481
Název nakladatele
SCITEPRESS
Místo vydání
Portugalsko
Místo konání akce
Vídeň
Datum konání akce
29. 8. 2014
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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