Managing renewable energy and carbon footprint in multi-cloud computing environments

Abstract

Cloud computing offers attractive features for both service providers and customers. Users benefit from the pay-as-you-go model by saving expenditures and service providers are deploying their services to cloud data centers to reduce their maintenance efforts. However, due to the fast growth of cloud data centers, the energy consumed by the data centers can lead to a huge amount of carbon emission with environmental impacts, and the carbon intensity of different locations are varied among different power plants according to the sources of energy. Thus, in this paper, to address the carbon emission problem of data centers, we consider shifting the workloads among multi-cloud located in different time zones. We also formulate the energy usage and carbon emission of data centers and model the solar power corresponding to the locations. This helps to reduce the usage of brown energy and maximize the utilization of renewable energy at different locations. We propose an approach for managing carbon footprint and renewable energy for multiple data centers at California, Virginia, and Dublin, which are in different time zones. The results show that our proposed approaches that apply workload shifting can reduce around 40% carbon emission in comparison to the baseline while ensuring the average response time of user requests.