Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads

TL;DR

Cucumber is an admission control policy that maximizes renewable energy usage for delay-tolerant workloads in cloud and edge computing by accepting jobs based on probabilistic forecasts, reducing grid energy consumption.

Contribution

It introduces a novel renewable-aware admission control policy that leverages probabilistic forecasting to optimize renewable energy utilization in delay-tolerant workloads.

Findings

Achieves near-optimal acceptance rates with high renewable energy usage.

Reduces grid energy consumption by up to 97%.

Offers configurable admission policies for different energy and workload scenarios.

Abstract

The growing electricity demand of cloud and edge computing increases operational costs and will soon have a considerable impact on the environment. A possible countermeasure is equipping IT infrastructure directly with on-site renewable energy sources. Yet, particularly smaller data centers may not be able to use all generated power directly at all times, while feeding it into the public grid or energy storage is often not an option. To maximize the usage of renewable excess energy, we propose Cucumber, an admission control policy that accepts delay-tolerant workloads only if they can be computed within their deadlines without the use of grid energy. Using probabilistic forecasting of computational load, energy consumption, and energy production, Cucumber can be configured towards more optimistic or conservative admission. We evaluate our approach on two scenarios using real solar production forecasts for Berlin, Mexico City, and Cape Town in a simulation environment. For scenarios where excess energy was actually available, our results show that Cucumber's default configuration achieves acceptance rates close to the optimal case and causes 97.0% of accepted workloads to be powered using excess energy, while more conservative admission results in 18.5% reduced acceptance at almost zero grid power usage.