In the context of global warming, reducing the carbon emissions of computer systems is a top priority. Data centers are responsible for a large fraction of the carbon emissions of IT. The carbon footprint of cloud applications is amplified by all the replication techniques used to ensure availability despite hardware failures [1].
Our research team works on assessing the impact of these availability techniques. To this end, we need to measure precisely the energy consumption of applications. This is not as simple as it might look at first sight, especially when multiple applications are co-hosted on the same physical server [2].
In this study, we would like to consider different hardware architectures for the servers and more specifically, multiple processors families (Intel, AMD, ARM), as hardware architectures can have a significant impact on the way applications consume energy [3].
The goal of this internship is to study how different processor families impact the energy consumption of applications running in shared cloud infrastructures. The results will be used to analyze the carbon footprint of highly available cloud applications
The intern will be in charge of the following tasks:
Through a literature review and experiments, study how energy consumption can be measured on different processor families, and how processors can be configured to reduce their energy consumption
Run an extensive experimental campaign to collect data about the energy consumption of cloud applications on different processors
Use these data to analyze the carbon footprint of Cloud applications
[1] Diptyaroop Maji, Walid A Hanafy, Li Wu, David Irwin, Prashant Shenoy, and Ramesh K Sitaraman. 2025. Data Centers Carbon Emissions at Crossroads: An Empirical Study. ACM SIGENERGY Energy Informatics Review 5, 2 (2025), 48–55.
[2] Ian Schneider and Taylor Mattia. 2024. Carbon accounting in the Cloud: a methodology for allocating emissions across data center users. arXiv preprint arXiv:2406.09645 (2024).
[3] Li, Ruihao, et al. “Hardware Lifecycle-Aware Power Planning in Commercial Hyperscale Datacenters (Operational Systems).” 20th USENIX Symposium on Operating Systems Design and Implementation (OSDI 26). 2026.
The intern will join the Informatics Laboratory of Univ. Grenoble Alpes (LIG), one of the largest laboratory in Computer Science in France. Univ. Grenoble Alpes is one of the 50 best universities in the world for computer science according to international rankings.
More specifically, the intern will work in the KrakOS research team, that focus on the efficiency and robustness of systems. KrakOS is one of the top system research teams in France and in Europe, with publications in the most selective conferences of the domain.