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 and Tomáš PITNER

Basic information

Original name

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

Authors

TOVARŇÁK, Daniel (203 Czech Republic, guarantor, belonging to the institution) and Tomáš PITNER (203 Czech Republic, belonging to the institution)

Edition

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

Publisher

SCITEPRESS

Other information

Language

English

Type of outcome

Proceedings paper

Field of Study

20206 Computer hardware and architecture

Country of publisher

Portugal

Confidentiality degree

is not subject to a state or trade secret

Publication form

printed version "print"

RIV identification code

RIV/00216224:14330/14:00076291

Organization unit

Faculty of Informatics

ISBN

978-989-758-036-9

DOI

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

EID Scopus

2-s2.0-84908887647

Keywords in English

Stream Processing; Distributed Architectures; Monitoring; Cloud

Abstract

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.

Links

LG13010, research and development project

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

Investor: Ministry of Education, Youth and Sports of the CR

Cite

TOVARŇÁK, Daniel and 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, p. 470-481. ISBN 978-989-758-036-9. Available from: 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  - CONF
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 and 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, p.~470-481. ISBN~978-989-758-036-9. Available from: https://dx.doi.org/10.5220/0005095504700481.

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