WattsApp: power-aware container scheduling

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

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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:	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

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