Continuous Queries over Distributed Streams of Heterogeneous
Monitoring Data in Cloud Datacenters

D 2014

Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters

TOVARŇÁK, Daniel a Tomáš PITNER

Základní údaje

Originální název

Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters

Autoři

TOVARŇÁK, Daniel (203 Česká republika, garant, domácí) a Tomáš PITNER (203 Česká republika, domácí)

Vydání

Portugalsko, ICSOFT-EA 2014 - Proceedings of the 9th International Conference on Software Engineering and Applications, od s. 470-481, 12 s. 2014

Nakladatel

SCITEPRESS

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

20206 Computer hardware and architecture

Stát vydavatele

Portugalsko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Kód RIV

RIV/00216224:14330/14:00076291

Organizační jednotka

Fakulta informatiky

ISBN

978-989-758-036-9

DOI

http://dx.doi.org/10.5220/0005095504700481

Klíčová slova anglicky

Stream Processing; Distributed Architectures; Monitoring; Cloud

Štítky

best1, core_B, firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 27. 4. 2015 04:04, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

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.

Návaznosti

LG13010, projekt VaV

Název: Zastoupení ČR v European Research Consortium for Informatics and Mathematics (Akronym: ERCIM-CZ)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Zastoupení ČR v European Research Consortium for Informatics and Mathematics

Citovat

TOVARŇÁK, Daniel a Tomáš PITNER. Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters. In Andreas Holzinger, Therese Libourel, Leszek Maciaszek and Stephen Mellor. ICSOFT-EA 2014 - Proceedings of the 9th International Conference on Software Engineering and Applications. Portugalsko: SCITEPRESS, 2014, s. 470-481. ISBN 978-989-758-036-9. Dostupné z: https://dx.doi.org/10.5220/0005095504700481.

@inproceedings{1196552,
   author = {Tovarňák, Daniel and Pitner, Tomáš},
   address = {Portugalsko},
   booktitle = {ICSOFT-EA 2014 - Proceedings of the 9th International Conference on Software Engineering and Applications},
   doi = {http://dx.doi.org/10.5220/0005095504700481},
   editor = {Andreas Holzinger, Therese Libourel, Leszek Maciaszek and Stephen Mellor},
   keywords = {Stream Processing; Distributed Architectures; Monitoring; Cloud},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Portugalsko},
   isbn = {978-989-758-036-9},
   pages = {470-481},
   publisher = {SCITEPRESS},
   title = {Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters},
   year = {2014}
}

TY  - JOUR
ID  - 1196552
AU  - Tovarňák, Daniel - Pitner, Tomáš
PY  - 2014
TI  - Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters
PB  - SCITEPRESS
CY  - Portugalsko
SN  - 9789897580369
KW  - Stream Processing
KW  - Distributed Architectures
KW  - Monitoring
KW  - Cloud
N2  - 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.
ER  -

TOVARŇÁK, Daniel a Tomáš PITNER. Continuous Queries over Distributed Streams of Heterogeneous Monitoring Data in Cloud Datacenters. In Andreas Holzinger, Therese Libourel, Leszek Maciaszek and Stephen Mellor. \textit{ICSOFT-EA 2014 - Proceedings of the 9th International Conference on Software Engineering and Applications}. Portugalsko: SCITEPRESS, 2014, s.~470-481. ISBN~978-989-758-036-9. Dostupné z: https://dx.doi.org/10.5220/0005095504700481.

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