Energy-aware Time- and Event-triggered KVM Nodes

TL;DR

This paper introduces an energy-aware scheduling algorithm for real-time virtual machines in cloud and edge environments, aiming to reduce energy consumption while maintaining real-time guarantees.

Contribution

It proposes a novel algorithm supporting energy-efficient time-triggered execution of VMs, integrating dynamic power management and voltage scaling, implemented as a Linux kernel extension.

Findings

Effective energy reduction in real-time VM scheduling

Maintains real-time guarantees with energy-aware techniques

Validated on Intel Xeon hardware

Abstract

Industries are considering the adoption of cloud and edge computing for real-time applications due to current improvements in network latencies and the advent of Fog and Edge computing. Current cloud paradigms are not designed for real-time applications, as they neither provide low latencies/jitter nor the guarantees and determinism required by real-time applications. Experts estimate that data centers use 1% of global electricity for powering the equipment, and in turn, for dealing with the produced heat. Hence, energy consumption is a crucial metric in cloud technologies. Applying energy conservation techniques is not straightforward due to the increased scheduling overheads and application execution times. Inspired by slot shifting, we propose an algorithm to support energy-aware time-triggered execution of periodic real-time VMs while still providing the ability to execute aperiodic real-time and best-effort VMs in the slack of the time-triggered ones. The algorithm considers energy reduction techniques based on dynamic power management and dynamic voltage and frequency scaling. We implement our algorithm as an extension to the Linux kernel scheduler (for use with the KVM hypervisor) and evaluate it on a server-grade Intel Xeon node.