<div class="csl-bib-body">
<div class="csl-entry">Borkowski, M., Hochreiner, C., & Schulte, S. (2019). Minimizing Cost by Reducing Scaling Operations in Distributed Stream Processing. In L. Chen & F. Özcan (Eds.), <i>Proceedings of the 45th International Conference on Very Large Data Bases</i> (Vols. 12, 7, pp. 724–737). https://doi.org/10.14778/3317315.3317316</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/86877
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dc.description.abstract
Elastic distributed stream processing systems are able to dynamically adapt to changes in the workload. Often, these systems react to the rate of incoming data, or to the level of resource utilization, by scaling up or down. The goal is to optimize the system's resource usage, thereby reducing its operational cost. However, such scaling operations consume resources on their own, introducing a certain overhead of resource usage, and therefore cost, for every scaling operation. In addition, migrations caused by scaling operations inevitably lead to brief processing gaps. Therefore, an excessive number of scaling operations should be avoided.
We approach this problem by preventing unnecessary scaling operations and over-compensating reactions to short-term changes in the workload. This allows to maintain elasticity, while also minimizing the incurred overhead cost of scaling operations. To achieve this, we use advanced filtering techniques from the field of signal processing to pre-process raw system measurements, thus mitigating superfluous scaling operations. We perform a real-world testbed evaluation verifying the effects, and provide a break-even cost analysis to show the economic feasibility of our approach.
en
dc.language.iso
en
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dc.relation.ispartofseries
Proceedings of the VLDB Endowment
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dc.subject
General Medicine
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dc.title
Minimizing Cost by Reducing Scaling Operations in Distributed Stream Processing
en
dc.type
Beitrag in Tagungsband
de
dc.type
Inproceedings
en
dc.relation.issn
2150-8097
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dc.description.startpage
724
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dc.description.endpage
737
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings of the 45th International Conference on Very Large Data Bases
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tuw.container.volume
12, 7
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tuw.peerreviewed
true
-
tuw.publication.orgunit
E194-02 - Forschungsbereich Distributed Systems
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tuw.publisher.doi
10.14778/3317315.3317316
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dc.description.numberOfPages
14
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tuw.event.name
45th International Conference on Very Large Data Bases
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tuw.event.startdate
26-08-2019
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tuw.event.enddate
30-08-2019
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Los Angeles
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tuw.event.country
US
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tuw.event.presenter
Borkowski, Michael
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wb.sciencebranch
Informatik
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wb.sciencebranch.oefos
1020
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wb.facultyfocus
Information Systems Engineering (ISE)
de
wb.facultyfocus
Information Systems Engineering (ISE)
en
wb.facultyfocus.faculty
E180
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item.fulltext
no Fulltext
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item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
-
item.languageiso639-1
en
-
item.openairetype
conference paper
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item.grantfulltext
none
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crisitem.author.dept
E194-02 - Forschungsbereich Distributed Systems
-
crisitem.author.dept
E184 - Institut für Informationssysteme
-
crisitem.author.dept
E194-02 - Forschungsbereich Distributed Systems
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crisitem.author.orcid
0000-0001-6828-9945
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.author.parentorg
E180 - Fakultät für Informatik
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering