Control-Based Load-Balancing Techniques: Analysis and Performance Evaluation via a Randomized Optimization Approach

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Control-Based Load-Balancing Techniques: Analysis and Performance Evaluation via a Randomized Optimization Approach. / Papadopoulos, Alessandro Vittorio; Klein, Cristian; Maggio, Martina; Dürango, Jonas; Dellkrantz, Manfred; Hernandez-Rodriguez, Francisco; Elmroth, Erik; Årzén, Karl-Erik.

In: Control Engineering Practice, Vol. 52, No. July, 07.2016, p. 24-34.

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Papadopoulos, Alessandro Vittorio ; Klein, Cristian ; Maggio, Martina ; Dürango, Jonas ; Dellkrantz, Manfred ; Hernandez-Rodriguez, Francisco ; Elmroth, Erik ; Årzén, Karl-Erik. / Control-Based Load-Balancing Techniques: Analysis and Performance Evaluation via a Randomized Optimization Approach. In: Control Engineering Practice. 2016 ; Vol. 52, No. July. pp. 24-34.

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TY - JOUR

T1 - Control-Based Load-Balancing Techniques: Analysis and Performance Evaluation via a Randomized Optimization Approach

AU - Papadopoulos, Alessandro Vittorio

AU - Klein, Cristian

AU - Maggio, Martina

AU - Dürango, Jonas

AU - Dellkrantz, Manfred

AU - Hernandez-Rodriguez, Francisco

AU - Elmroth, Erik

AU - Årzén, Karl-Erik

PY - 2016/7

Y1 - 2016/7

N2 - Cloud applications are often subject to unexpected events like flashcrowds and hardware failures. Users that expect a predictable behavior may abandon an unresponsive application when these events occur. Researchers and engineers addressed this problem on two separate fronts: first, they introduced replicas - copies of the application with the same functionality - for redundancy and scalability; second, they added a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience. The presence of multiple replicas requires a dedicated component to direct incoming traffic: a load-balancer.Existing load-balancing strategies based on response times interfere with the response time controller developed for brownout-compliant applications. In fact, the brownout approach bounds response times using a control action. Hence, the response time, that was used to aid load-balancing decision, is not a good indicator of how well a replica is performing.To fix this issue, this paper reviews some proposal for brownout-aware load-balancing and provides a comprehensive experimental evaluation that compares them. To provide formal guarantees on the load-balancing performance, we use a randomized optimization approach and apply the scenario theory. We perform an extensive set of experiments on a real machine, extending the popular lighttpd web server and load-balancer, and obtaining a production-ready implementation. Experimental results show an improvement of the user experience over Shortest Queue First (SQF) - believed to be near-optimal in the non-adaptive case. The improved user experience is obtained preserving the response time predictability.

AB - Cloud applications are often subject to unexpected events like flashcrowds and hardware failures. Users that expect a predictable behavior may abandon an unresponsive application when these events occur. Researchers and engineers addressed this problem on two separate fronts: first, they introduced replicas - copies of the application with the same functionality - for redundancy and scalability; second, they added a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience. The presence of multiple replicas requires a dedicated component to direct incoming traffic: a load-balancer.Existing load-balancing strategies based on response times interfere with the response time controller developed for brownout-compliant applications. In fact, the brownout approach bounds response times using a control action. Hence, the response time, that was used to aid load-balancing decision, is not a good indicator of how well a replica is performing.To fix this issue, this paper reviews some proposal for brownout-aware load-balancing and provides a comprehensive experimental evaluation that compares them. To provide formal guarantees on the load-balancing performance, we use a randomized optimization approach and apply the scenario theory. We perform an extensive set of experiments on a real machine, extending the popular lighttpd web server and load-balancer, and obtaining a production-ready implementation. Experimental results show an improvement of the user experience over Shortest Queue First (SQF) - believed to be near-optimal in the non-adaptive case. The improved user experience is obtained preserving the response time predictability.

KW - load-balancing

KW - randomized optimization

KW - cloud control

U2 - 10.1016/j.conengprac.2016.03.020

DO - 10.1016/j.conengprac.2016.03.020

M3 - Article

VL - 52

SP - 24

EP - 34

JO - Control Engineering Practice

T2 - Control Engineering Practice

JF - Control Engineering Practice

SN - 0967-0661

IS - July

ER -