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Cloud Application Predictability through Integrated Load-Balancing and Service Time Control

Nylander, Tommi LU ; Thelander Andrén, Marcus LU ; Årzén, Karl-Erik LU and Maggio, Martina LU (2018) 15th IEEE International Conference on Autonomic Computing
Abstract
Cloud computing provides the illusion of infinite capacity to application developers. However, data center provisioning is complex and it is still necessary to handle the risk of capacity shortages. To handle capacity shortages, graceful degradation techniques sacrifice user experience for predictability. In all these cases, the decision making policy that determines the degradation interferes with other decisions happening at the infrastructure level, like load-balancing choices. Here, we reconcile the two approaches, developing a load-balancing strategy that also handles capacity shortages and graceful degradation when necessary. The proposal is based on a sound control-theoretical approach. The design of the approach avoids the pitfalls... (More)
Cloud computing provides the illusion of infinite capacity to application developers. However, data center provisioning is complex and it is still necessary to handle the risk of capacity shortages. To handle capacity shortages, graceful degradation techniques sacrifice user experience for predictability. In all these cases, the decision making policy that determines the degradation interferes with other decisions happening at the infrastructure level, like load-balancing choices. Here, we reconcile the two approaches, developing a load-balancing strategy that also handles capacity shortages and graceful degradation when necessary. The proposal is based on a sound control-theoretical approach. The design of the approach avoids the pitfalls of interfering control decisions. We describe the technique and provide evidence that it allows us to achieve higher performance in terms of emergency management and user experience. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Cloud computing, Graceful degradation, Load balancing
host publication
Proceedings of the 15th IEEE International Conference on Autonomic Computing
pages
10 pages
publisher
IEEE Computer Society
conference name
15th IEEE International Conference on Autonomic Computing
conference location
Trento, Italy
conference dates
2018-09-04 - 2018-09-06
external identifiers
  • scopus:85061304418
ISBN
978-153865139-1
DOI
10.1109/ICAC.2018.00015
language
English
LU publication?
yes
id
b936307f-5e69-4eb0-9534-d6961de1ecf7
date added to LUP
2018-09-13 16:12:07
date last changed
2019-03-19 03:59:26
@inproceedings{b936307f-5e69-4eb0-9534-d6961de1ecf7,
  abstract     = {Cloud computing provides the illusion of infinite capacity to application developers. However, data center provisioning is complex and it is still necessary to handle the risk of capacity shortages. To handle capacity shortages, graceful degradation techniques sacrifice user experience for predictability. In all these cases, the decision making policy that determines the degradation interferes with other decisions happening at the infrastructure level, like load-balancing choices. Here, we reconcile the two approaches, developing a load-balancing strategy that also handles capacity shortages and graceful degradation when necessary. The proposal is based on a sound control-theoretical approach. The design of the approach avoids the pitfalls of interfering control decisions. We describe the technique and provide evidence that it allows us to achieve higher performance in terms of emergency management and user experience.},
  author       = {Nylander, Tommi and Thelander Andrén, Marcus and Årzén, Karl-Erik and Maggio, Martina},
  isbn         = {978-153865139-1},
  keyword      = {Cloud computing,Graceful degradation,Load balancing},
  language     = {eng},
  location     = {Trento, Italy},
  pages        = {10},
  publisher    = {IEEE Computer Society},
  title        = {Cloud Application Predictability through Integrated Load-Balancing and Service Time Control},
  url          = {http://dx.doi.org/10.1109/ICAC.2018.00015},
  year         = {2018},
}