Improving Cloud Service Resilience using Brownout-Aware Load-Balancing
(2014) 33rd IEEE International Symposium on Reliable Distributed Systems p.31-40- Abstract
- We focus on improving resilience of cloud services (e.g., e-commerce website), when correlated or cascading failures lead to computing capacity shortage. We study how to extend the classical cloud service architecture composed of a load-balancer and replicas with a recently proposed self-adaptive paradigm called brownout. Such services are able to reduce their capacity requirements by degrading user experience (e.g., disabling recommendations).
Combining resilience with the brownout paradigm is to date an open practical problem. The issue is to ensure that replica self-adaptivity would not confuse the load-balancing algorithm, overloading replicas that are already struggling with capacity shortage. For example, load-balancing... (More) - We focus on improving resilience of cloud services (e.g., e-commerce website), when correlated or cascading failures lead to computing capacity shortage. We study how to extend the classical cloud service architecture composed of a load-balancer and replicas with a recently proposed self-adaptive paradigm called brownout. Such services are able to reduce their capacity requirements by degrading user experience (e.g., disabling recommendations).
Combining resilience with the brownout paradigm is to date an open practical problem. The issue is to ensure that replica self-adaptivity would not confuse the load-balancing algorithm, overloading replicas that are already struggling with capacity shortage. For example, load-balancing strategies based on response times are not able to decide which replicas should be selected, since the response times are already controlled by the brownout paradigm.
In this paper we propose two novel brownout-aware load-balancing algorithms. To test their practical applicability, we extended the popular lighttpd web server and load-balancer, thus obtaining a production-ready implementation. Experimental evaluation shows that the approach enables cloud services to remain responsive despite cascading failures. Moreover, when compared to Shortest Queue First (SQF), believed to be near-optimal in the non-adaptive case, our algorithms improve user experience by 5%, with high statistical significance, while preserving response time predictability. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4698578
- author
- Klein, Cristian ; Papadopoulos, Alessandro Vittorio LU ; Dellkrantz, Manfred LU ; Dürango, Jonas LU ; Maggio, Martina LU ; Årzén, Karl-Erik LU ; Hernàndez-Rodriguez, Francisco and Elmroth, Erik
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- [Host publication title missing]
- pages
- 10 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 33rd IEEE International Symposium on Reliable Distributed Systems
- conference location
- Nara, Japan
- conference dates
- 2014-10-07
- external identifiers
-
- scopus:84938932324
- wos:000380439400004
- DOI
- 10.1109/SRDS.2014.14
- project
- EIT_VR CLOUD Cloud Control
- language
- English
- LU publication?
- yes
- id
- 315a6d32-02c1-4a3c-aa62-ebae1a7c2921 (old id 4698578)
- date added to LUP
- 2016-04-04 10:26:16
- date last changed
- 2024-01-27 18:01:25
@inproceedings{315a6d32-02c1-4a3c-aa62-ebae1a7c2921, abstract = {{We focus on improving resilience of cloud services (e.g., e-commerce website), when correlated or cascading failures lead to computing capacity shortage. We study how to extend the classical cloud service architecture composed of a load-balancer and replicas with a recently proposed self-adaptive paradigm called brownout. Such services are able to reduce their capacity requirements by degrading user experience (e.g., disabling recommendations). <br/><br> Combining resilience with the brownout paradigm is to date an open practical problem. The issue is to ensure that replica self-adaptivity would not confuse the load-balancing algorithm, overloading replicas that are already struggling with capacity shortage. For example, load-balancing strategies based on response times are not able to decide which replicas should be selected, since the response times are already controlled by the brownout paradigm. <br/><br> In this paper we propose two novel brownout-aware load-balancing algorithms. To test their practical applicability, we extended the popular lighttpd web server and load-balancer, thus obtaining a production-ready implementation. Experimental evaluation shows that the approach enables cloud services to remain responsive despite cascading failures. Moreover, when compared to Shortest Queue First (SQF), believed to be near-optimal in the non-adaptive case, our algorithms improve user experience by 5%, with high statistical significance, while preserving response time predictability.}}, author = {{Klein, Cristian and Papadopoulos, Alessandro Vittorio and Dellkrantz, Manfred and Dürango, Jonas and Maggio, Martina and Årzén, Karl-Erik and Hernàndez-Rodriguez, Francisco and Elmroth, Erik}}, booktitle = {{[Host publication title missing]}}, language = {{eng}}, pages = {{31--40}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Improving Cloud Service Resilience using Brownout-Aware Load-Balancing}}, url = {{https://lup.lub.lu.se/search/files/5538820/4698579.pdf}}, doi = {{10.1109/SRDS.2014.14}}, year = {{2014}}, }