Master data

Title: Proactive SLA-aware Application Placement in the Computing Continuum
Subtitle:
Abstract:

The accelerating growth of modern distributed applications with low delivery deadlines leads to a paradigm shift towards the multi-tier computing continuum. However, the geographical dispersion, heterogeneity, and availability of the continuum resources may result in failures and quality of service degradation, significantly negating its advantages and lowering users’ satisfaction. We propose in this paper a proactive application placement (PROS) method relying on distributed coordination to prevent the quality of service violations through service-level agreements on the computing continuum. PROS employs a sigmoid function with adaptive weights for the different parameters to predict the service level agreement assurance of devices based on their past credentials and current capabilities. We evaluate PROS using two application workloads with different traffic stress levels up to 90 million services on a real testbed with 600 heterogeneous instances deployed over eight geographical locations. The results show that PROS increases the success rate by 7%–33%, reduces the response time by 16%–38%, and increases the deadline satisfaction rate by 19%–42% compared to two related work methods. A comprehensive simulation study with 1000 devices and a workload of up to 670 million services confirm the scalability of the results.

Keywords: Computing continuum, application placement, SLA assurance, network partitioning, adaptive weight
Publication type: Article in Proceedings (Authorship)
Publication date: 05.2023 (Print)
Published by: IPDPS 2023 Proceedings of the IEEE International Parallel and Distributed Processing Symposium
IPDPS 2023 Proceedings of the IEEE International Parallel and Distributed Processing Symposium
to publication
 ( IEEE Xplore Digital Library; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 468 - 479

Versionen

Keine Version vorhanden
Publication date: 05.2023
ISBN:
  • 979-8-3503-3766-2
ISSN: 1530-2075
Homepage: https://ieeexplore.ieee.org/document/10177411
Publication date: 18.07.2023
ISBN (e-book): -
eISSN: 1530-2075
DOI: http://dx.doi.org/10.1109/ipdps54959.2023.00054
Homepage: https://ieeexplore.ieee.org/document/10177411
Open access
  • Available online (not open access)

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Austria
   martina.steinbacher@aau.at
http://itec.aau.at/
To organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Categorisation

Subject areas
  • 1020 - Computer Sciences
Research Cluster No research Research Cluster selected
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: I)
Classification raster of the assigned organisational units:
working groups
  • Verteilte Systeme

Cooperations

No partner organisations selected

Articles of the publication

No related publications