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.
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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
Original 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
Keywords in English Stream Processing; Distributed Architectures; Monitoring; Cloud
Tags best1, firank_B
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 27/4/2015 04:04.
Abstract
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 projectName: Zastoupení ČR v European Research Consortium for Informatics and Mathematics (Acronym: ERCIM-CZ)
Investor: Ministry of Education, Youth and Sports of the CR
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