Towards energy-efficient service scheduling in federated edge clouds

This paper proposes an energy-efficient service scheduling mechanism in federated edge cloud (FEC) called ESFEC, which consists of a placement algorithm and three types of reconfiguration algorithms. Unlike traditional approaches, ESFEC places delay-sensitive services on the edge servers in nearby edge domains instead of clouds. In addition, ESFEC schedules services with actual traffic requirements rather than maximum traffic requirements to ensure QoS. This increases the number of services co-located in a single server and thereby reduces the total energy consumed by the services. ESFEC reduces the service migration overhead using a reinforcement learning (RL)-based reconfiguration algorithm, ESFEC-RL, that can dynamically adapt to a changing environment. Additionally, ESFEC includes two different heuristic algorithms, ESFEC-EF (energy first) and ESFEC-MF (migration first), which are more suitable for real-scale scenarios. The simulation results show that ESFEC improves energy efficiency by up to 28% and lowers the service violation rate by up to 66% compared to a traditional approach used in the edge cloud environment.