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Design of Cloud Monitoring Systems via DAGGTAX: A Case Study
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-6952-1053
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-2898-9570
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-2870-2680
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2017 (English)In: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 109, 424-431 p.Article in journal (Refereed) Published
Abstract [en]

Efficient auto-scaling of cloud resources relies on the monitoring of the cloud, which involves multiple aggregation processes and large amounts of data with various and interdependent requirements. A systematic way of describing the data together with the possible aggregations is beneficial for designers to reason about the properties of these aspects as well as their implications on the design, thus improving quality and lowering development costs. In this paper, we propose to apply DAGGTAX, a feature-oriented taxonomy for organizing common and variable data and aggregation process properties, to the design of cloud monitoring systems. We demonstrate the effectiveness of DAGGTAX via a case study provided by industry, which aims to design a cloud monitoring system that serves auto-scaling for a video streaming system. We design the cloud monitoring system by selecting and composing DAGGTAX features, and reason about the feasibility of the selected features. The case study shows that the application of DAGGTAX can help designers to identify reusable features, analyze trade-offs between selected features, and derive crucial system parameters.

Place, publisher, year, edition, pages
2017. Vol. 109, 424-431 p.
Keyword [en]
data aggregation, information system design, cloud monitoring system design
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-35493DOI: 10.1016/j.procs.2017.05.412ISI: 000414533000053Scopus ID: 2-s2.0-85021817536OAI: oai:DiVA.org:mdh-35493DiVA: diva2:1106838
Conference
The 8th International Conference on Ambient Systems, Networks and Technologies ANT 2017, 16 May 2017, Madeira, Portugal
Projects
DAGGERS - Data aggregation for embedded real-time database systems
Available from: 2017-06-08 Created: 2017-06-08 Last updated: 2017-11-23Bibliographically approved

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Cai, SiminGallina, BarbaraNyström, DagSeceleanu, Cristina

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