Mehta, Hemant Kumar, Harvey, Paul, Rana, Omer  ORCID: https://orcid.org/0000-0003-3597-2646, Buyya, Rajkumar and Varghese, Blesson
2020.
WattsApp: power-aware container scheduling.
Presented at: IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC 2020),
Leicester, England,
7-10 December 2020.
2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC).
IEEE,
pp. 79-90.
10.1109/UCC48980.2020.00027
|
Preview |
PDF
- Accepted Post-Print Version
Download (1MB) | Preview |
Abstract
Containers are popular for deploying workloads. However, there are limited software-based methods (hardware- based methods are expensive) for obtaining the power consumed by containers to facilitate power-aware container scheduling. This paper presents WattsApp, a tool underpinned by a six step software-based method for power-aware container scheduling to minimize power cap violations on a server. The proposed method relies on a neural network-based power estimation model and a power capped container scheduling technique. Experimental studies are pursued in a lab-based environment on 10 benchmarks on Intel and ARM processors. The results highlight that power estimation has negligible overheads - nearly 90% of all data samples can be estimated with less than a 10% error, and the Mean Absolute Percentage Error (MAPE) is less than 6%. The power-aware scheduling of WattsApp is more effective than Intel’s Running Power Average Limit (RAPL) based power capping as it does not degrade the performance of all running containers.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Publisher: | IEEE |
| ISBN: | 9780738123943 |
| Date of First Compliant Deposit: | 20 January 2021 |
| Date of Acceptance: | 12 October 2020 |
| Last Modified: | 09 Nov 2022 09:57 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/137738 |
Citation Data
Cited 11 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
 |
Edit Item |
Dimensions
Dimensions