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Design of Cloud Monitoring Systems via DAGGTAX: A Case Study
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-6952-1053
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0003-2898-9570
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0003-2870-2680
Vise andre og tillknytning
2017 (engelsk)Inngår i: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 109, s. 424-431Artikkel i tidsskrift (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
2017. Vol. 109, s. 424-431
Emneord [en]
data aggregation, information system design, cloud monitoring system design
HSV kategori
Identifikatorer
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, id: diva2:1106838
Konferanse
The 8th International Conference on Ambient Systems, Networks and Technologies ANT 2017, 16 May 2017, Madeira, Portugal
Prosjekter
DAGGERS - Data aggregation for embedded real-time database systemsTilgjengelig fra: 2017-06-08 Laget: 2017-06-08 Sist oppdatert: 2017-11-23bibliografisk kontrollert

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Cai, SiminGallina, BarbaraNyström, DagSeceleanu, Cristina

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