53rd IEEE Conference on Decision and Control 2014
DOI: 10.1109/cdc.2014.7040221
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Control-theoretical load-balancing for cloud applications with brownout

Abstract: Abstract-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 … Show more

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Cited by 19 publications
(44 citation statements)
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“…EVALUATION This section presents our results. We validate our control strategy using the open source Python-based brownout simulator 2 , built to mimic the behavior of cloud applications [10] and described in the following Section IV-A.…”
Section: E Design Of Outer Loop Feedforward Controllermentioning
confidence: 99%
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“…EVALUATION This section presents our results. We validate our control strategy using the open source Python-based brownout simulator 2 , built to mimic the behavior of cloud applications [10] and described in the following Section IV-A.…”
Section: E Design Of Outer Loop Feedforward Controllermentioning
confidence: 99%
“…Computing resource allocation can easily be cast into a control problem, where a controller decides the amount of resource to allocate to different entities based on desired and measurable performance metrics [1,17,21,25]. Recently, the cloud computing domain has emerged as an interesting application domain for control-theoretical principles and techniques [4,7,10,15,22].…”
Section: Introductionmentioning
confidence: 99%
“…Preliminary simulation results [13] compared different loadbalancing algorithms for this architecture, such as round-robin, fastest replica first, random and two random choices. The main result of this comparison is that load-balancing algorithms that are based on measurements of the response times of the single replicas are not suited to be used with brownout-compliant services, since the replica controllers already keep the response times close to the setpoint.…”
Section: B Multiple Replica Brownout-compliant Servicesmentioning
confidence: 99%
“…The main result of this comparison is that load-balancing algorithms that are based on measurements of the response times of the single replicas are not suited to be used with brownout-compliant services, since the replica controllers already keep the response times close to the setpoint. The only existing algorithm that proved to work adequately with brownout-compliant services is Shortest Queue First (SQF) [10], [13]. It works by tracking the number of queued requests q i on each replica and directing the next request to the replica with the lowest q i .…”
Section: B Multiple Replica Brownout-compliant Servicesmentioning
confidence: 99%
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