Control-theoretical load-balancing for cloud applications with brownout

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding


Cloud applications are often subject to unexpected events like flash crowds and hardware failures. Without a predictable behaviour, users may abandon an unresponsive application. This problem has been partially solved on two separate fronts: first, by adding a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience, and, second, by introducing replicas -- copies of the applications having the same functionalities -- for redundancy and adding a load-balancer to direct incoming traffic. However, existing load-balancing strategies interfere with brownout self-adaptivity. Load-balancers are often based on response times, that are already controlled by the self-adaptive features of the application, hence they are not a good indicator of how well a replica is performing. In this paper, we present novel load-balancing strategies, specifically designed to support brownout applications. They base their decision not on response time, but on user experience degradation. We implemented our strategies in a self-adaptive application simulator, together with some state-of-the-art
solutions. Results obtained in multiple scenarios show that the proposed strategies bring significant improvements when compared to the state-of-the-art ones.


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Control Engineering
Original languageEnglish
Title of host publication2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014)
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)978-1-4799-7746-
ISBN (Print)9781467360890
Publication statusPublished - 2014
Publication categoryResearch
Event53rd IEEE Conference on Decision and Control - Los Angeles, CA, United States
Duration: 2014 Dec 15 → …


Conference53rd IEEE Conference on Decision and Control
CountryUnited States
CityLos Angeles, CA
Period2014/12/15 → …

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