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Improving Cloud Service Resilience using Brownout-Aware Load-Balancing
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. (DS)ORCID-id: 0000-0003-0106-3049
Lund University, Sweden.ORCID-id: 0000-0002-1364-8127
Lund University, Sweden.
Lund University, Sweden.
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2014 (Engelska)Ingår i: 2014 IEEE 33RD INTERNATIONAL SYMPOSIUM ON RELIABLE DISTRIBUTED SYSTEMS (SRDS), IEEE Computer Society, 2014, s. 31-40Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

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.

Ort, förlag, år, upplaga, sidor
IEEE Computer Society, 2014. s. 31-40
Serie
Symposium on Reliable Distributed Systems Proceedings, ISSN 1060-9857
Nyckelord [en]
cloud, load-balancing, self-adaptation, control theory, statistical evaluation
Nationell ämneskategori
Datorsystem Reglerteknik
Forskningsämne
datalogi
Identifikatorer
URN: urn:nbn:se:umu:diva-91327ISI: 000380439400004ISBN: 978-1-4799-5584-8 (tryckt)OAI: oai:DiVA.org:umu-91327DiVA, id: diva2:735567
Konferens
2014 IEEE 33RD INTERNATIONAL SYMPOSIUM ON RELIABLE DISTRIBUTED SYSTEMS (SRDS), OCT 06-09, 2014, Nara, JAPAN
Projekt
Cloud Control
Forskningsfinansiär
VetenskapsrådetELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsLinnaeus research environment CADICSTillgänglig från: 2014-07-29 Skapad: 2014-07-29 Senast uppdaterad: 2018-06-07Bibliografiskt granskad

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Klein, CristianPapadopoulos, Alessandro VittorioMaggio, MartinaHernández-Rodriguez, FranciscoElmroth, Erik

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Klein, CristianPapadopoulos, Alessandro VittorioMaggio, MartinaHernández-Rodriguez, FranciscoElmroth, Erik
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