Cloud Application Predictability through Integrated Load-Balancing and Service Time Control

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

Standard

Cloud Application Predictability through Integrated Load-Balancing and Service Time Control. / Nylander, Tommi; Thelander Andrén, Marcus; Årzén, Karl-Erik; Maggio, Martina.

Proceedings of the 15th IEEE International Conference on Autonomic Computing. IEEE Computer Society, 2018.

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

Harvard

Nylander, T, Thelander Andrén, M, Årzén, K-E & Maggio, M 2018, Cloud Application Predictability through Integrated Load-Balancing and Service Time Control. in Proceedings of the 15th IEEE International Conference on Autonomic Computing. IEEE Computer Society, 15th IEEE International Conference on Autonomic Computing , Trento, Italy, 2018/09/04. https://doi.org/10.1109/ICAC.2018.00015

APA

CBE

MLA

Nylander, Tommi et al. "Cloud Application Predictability through Integrated Load-Balancing and Service Time Control". Proceedings of the 15th IEEE International Conference on Autonomic Computing. IEEE Computer Society. 2018. https://doi.org/10.1109/ICAC.2018.00015

Vancouver

Author

RIS

TY - GEN

T1 - Cloud Application Predictability through Integrated Load-Balancing and Service Time Control

AU - Nylander, Tommi

AU - Thelander Andrén, Marcus

AU - Årzén, Karl-Erik

AU - Maggio, Martina

PY - 2018

Y1 - 2018

N2 - Cloud computing provides the illusion of infinite capacity to application developers. However, data center provisioning is complex and it is still necessary to handle the risk of capacity shortages. To handle capacity shortages, graceful degradation techniques sacrifice user experience for predictability. In all these cases, the decision making policy that determines the degradation interferes with other decisions happening at the infrastructure level, like load-balancing choices. Here, we reconcile the two approaches, developing a load-balancing strategy that also handles capacity shortages and graceful degradation when necessary. The proposal is based on a sound control-theoretical approach. The design of the approach avoids the pitfalls of interfering control decisions. We describe the technique and provide evidence that it allows us to achieve higher performance in terms of emergency management and user experience.

AB - Cloud computing provides the illusion of infinite capacity to application developers. However, data center provisioning is complex and it is still necessary to handle the risk of capacity shortages. To handle capacity shortages, graceful degradation techniques sacrifice user experience for predictability. In all these cases, the decision making policy that determines the degradation interferes with other decisions happening at the infrastructure level, like load-balancing choices. Here, we reconcile the two approaches, developing a load-balancing strategy that also handles capacity shortages and graceful degradation when necessary. The proposal is based on a sound control-theoretical approach. The design of the approach avoids the pitfalls of interfering control decisions. We describe the technique and provide evidence that it allows us to achieve higher performance in terms of emergency management and user experience.

KW - Cloud computing

KW - Graceful degradation

KW - Load balancing

U2 - 10.1109/ICAC.2018.00015

DO - 10.1109/ICAC.2018.00015

M3 - Paper in conference proceeding

SN - 978-153865139-1

BT - Proceedings of the 15th IEEE International Conference on Autonomic Computing

PB - IEEE Computer Society

ER -