Cloud Application Predictability through Integrated Load-Balancing and Service Time Control
(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:
https://lup.lub.lu.se/record/b936307f-5e69-4eb0-9534-d6961de1ecf7
- author
- Nylander, Tommi LU ; Thelander Andrén, Marcus LU ; Årzén, Karl-Erik LU and Maggio, Martina LU
- organization
- publishing date
- 2018
- 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
- project
- Control-based resource management in the distributed cloud
- LCCC
- WASP: Autonomous Cloud
- Event-Based Control of Stochastic Systems with Application to Server Systems
- language
- English
- LU publication?
- yes
- id
- b936307f-5e69-4eb0-9534-d6961de1ecf7
- date added to LUP
- 2018-09-13 16:12:07
- date last changed
- 2022-05-11 01:25:59
@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}}, booktitle = {{Proceedings of the 15th IEEE International Conference on Autonomic Computing}}, isbn = {{978-153865139-1}}, keywords = {{Cloud computing; Graceful degradation; Load balancing}}, language = {{eng}}, publisher = {{IEEE Computer Society}}, title = {{Cloud Application Predictability through Integrated Load-Balancing and Service Time Control}}, url = {{https://lup.lub.lu.se/search/files/51135731/tommi_icac_2018_final.pdf}}, doi = {{10.1109/ICAC.2018.00015}}, year = {{2018}}, }