WattsApp: Power-Aware Container Scheduling

Mehta, H. K., Harvey, P. , Rana, O., Buyya, R. and Varghese, B. (2020) WattsApp: Power-Aware Container Scheduling. In: 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), 07-10 Dec 2020, pp. 79-90. (doi: 10.1109/UCC48980.2020.00027)

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 Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Harvey, Dr Paul
• Authors: Mehta, H. K., Harvey, P., Rana, O., Buyya, R., and Varghese, B.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Published Online: 30 December 2020