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Improving Cloud Service Resilience using Brownout-Aware Load-Balancing

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 (2014) 33rd IEEE International Symposium on Reliable Distributed Systems In [Host publication title missing] 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:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
[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
external identifiers
  • Scopus:84938932324
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
2014-11-09 17:48:45
date last changed
2017-01-01 07:57:56
@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          = {http://dx.doi.org/10.1109/SRDS.2014.14},
  year         = {2014},
}