Yumei Wang

TL;DR: This paper investigates the power and energy characteristics of mainstream hypervisors and container engine, i.e., VMware ESXi, Microsoft Hyper-V, KVM, XenServer and Docker, on five different platforms with hundreds of hours' power measures to provide useful insights to system designers, as well as data center operators for power-aware workload placement and virtual machine scheduling.

TL;DR: This paper investigates all 477 valid published results of SPECpower_ssj benchmark from 2007 to 2016Q3 and reorganizes them by hardware availability year for more accurate analysis on production servers, finding that specious stagnation of energy proportionality in recent years is mainly caused by the adoption of processors of specific microarchitecture.

TL;DR: The authorsﻷ propose to use useﻹ implicitﻴ formattingﻵ templatesﻅ and ﻷ implicitｿ formattingｽ semantics﻽ informationﻢ forﻩ automaticﻰ metadataﻱ identificationﻡ� and﻾ segmentation.

TL;DR: This article will discuss EASE, the energy efficiency and proportionality aware VM scheduling approach that schedules VMs to servers to keep them working at their peak energy efficiency point (or optimal working range) and improves the overall energy efficiency of the cluster and the data center.