  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.
