2025/09/02 by Benedikt Pittl, Pittl, Benedikt, Werner Mach +3
Computer Science · Engineering · #91-08 #Big Data and Digital Economy #Cloud Computing and Resource Management #Computers and Society (cs.CY) #Distributed #FOS: Computer and information sciences #Green IT and Sustainability #H.1.m #J.1 #Parallel #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2509.02767
openalex publication_date 2025/09/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The cloud computing technology uses datacenters, which require energy. Recent trends show that the required energy for these datacenters will rise over time, or at least remain constant. Hence, the scientific community developed different algorithms, architectures, and approaches for improving the energy efficiency of cloud datacenters, which are summarized under the umbrella term Green Cloud computing. In this paper, we use an economic approach - taxes - for reducing the energy consumption of datacenters. We developed a tax model called GreenCloud tax, which penalizes energy-inefficient datacenters while fostering datacenters that are energy-efficient. Hence, providers running energy-efficient datacenters are able to offer cheaper prices to consumers, which consequently leads to a shift of workloads from energy-inefficient datacenters to energy-efficient datacenters. The GreenCloud tax approach was implemented using the simulation environment CloudSim. We applied real data sets published in the SPEC benchmark for the executed simulation scenarios, which we used for evaluating the GreenCloud tax.