Control-theoretical load-balancing for cloud applications with brownout

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

Standard

Control-theoretical load-balancing for cloud applications with brownout. / Dürango, Jonas; Dellkrantz, Manfred; Maggio, Martina; Klein, Cristian; Papadopoulos, Alessandro Vittorio; Hernández-Rodriguez, Francisco; Elmroth, Erik; Årzén, Karl-Erik.

2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014) . IEEE - Institute of Electrical and Electronics Engineers Inc., 2014. p. 5320-5327.

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

Harvard

Dürango, J, Dellkrantz, M, Maggio, M, Klein, C, Papadopoulos, AV, Hernández-Rodriguez, F, Elmroth, E & Årzén, K-E 2014, Control-theoretical load-balancing for cloud applications with brownout. in 2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014) . IEEE - Institute of Electrical and Electronics Engineers Inc., pp. 5320-5327, 53rd IEEE Conference on Decision and Control, Los Angeles, CA, United States, 2014/12/15. https://doi.org/10.1109/CDC.2014.7040221

APA

Dürango, J., Dellkrantz, M., Maggio, M., Klein, C., Papadopoulos, A. V., Hernández-Rodriguez, F., ... Årzén, K-E. (2014). Control-theoretical load-balancing for cloud applications with brownout. In 2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014) (pp. 5320-5327). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2014.7040221

CBE

Dürango J, Dellkrantz M, Maggio M, Klein C, Papadopoulos AV, Hernández-Rodriguez F, Elmroth E, Årzén K-E. 2014. Control-theoretical load-balancing for cloud applications with brownout. In 2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014) . IEEE - Institute of Electrical and Electronics Engineers Inc. pp. 5320-5327. https://doi.org/10.1109/CDC.2014.7040221

MLA

Dürango, Jonas et al. "Control-theoretical load-balancing for cloud applications with brownout". 2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014) . IEEE - Institute of Electrical and Electronics Engineers Inc. 2014, 5320-5327. https://doi.org/10.1109/CDC.2014.7040221

Vancouver

Dürango J, Dellkrantz M, Maggio M, Klein C, Papadopoulos AV, Hernández-Rodriguez F et al. Control-theoretical load-balancing for cloud applications with brownout. In 2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014) . IEEE - Institute of Electrical and Electronics Engineers Inc. 2014. p. 5320-5327 https://doi.org/10.1109/CDC.2014.7040221

Author

Dürango, Jonas ; Dellkrantz, Manfred ; Maggio, Martina ; Klein, Cristian ; Papadopoulos, Alessandro Vittorio ; Hernández-Rodriguez, Francisco ; Elmroth, Erik ; Årzén, Karl-Erik. / Control-theoretical load-balancing for cloud applications with brownout. 2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014) . IEEE - Institute of Electrical and Electronics Engineers Inc., 2014. pp. 5320-5327

RIS

TY - GEN

T1 - Control-theoretical load-balancing for cloud applications with brownout

AU - Dürango, Jonas

AU - Dellkrantz, Manfred

AU - Maggio, Martina

AU - Klein, Cristian

AU - Papadopoulos, Alessandro Vittorio

AU - Hernández-Rodriguez, Francisco

AU - Elmroth, Erik

AU - Årzén, Karl-Erik

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

U2 - 10.1109/CDC.2014.7040221

DO - 10.1109/CDC.2014.7040221

M3 - Paper in conference proceeding

SN - 9781467360890

SP - 5320

EP - 5327

BT - 2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014)

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

ER -