Edge Emergency Demand Response Control via Scheduling in Cloudlet Cluster

A cloudlet is a small-scale cloud datacenter deployed at the network edge to support mobile applications in proximity with low latency. While an individual cloudlet operates on moderate power, cloudlet clusters are well-suited candidates for emergency demand response (EDR) scenarios due to substantial electricity consumption and job elasticity: mobile workloads in the edge often exhibit elasticity in their execution. To efficiently carry out edge EDR via cloudlet cluster control, one fundamental problem needs to be addressed: how to schedule and allocate workloads in a cloudlet cluster to satisfy EDR requirements. We propose an online task scheduling algorithm for the chosen cluster to dispatch workloads to guarantee target EDR power reduction. By exploiting the primal-dual optimization theory, we prove that our control scheme runs in polynomial time and achieves near-optimal performance. Large-scale simulation studies based on real-world data also confirm the efficiency and superiority of our scheme over state-of-the-art algorithms.