Exploring e-Infrastructure and Climate Change Interactions
Can we model e-Infrastructure and climate change interactions?
Almost everything that we do today is computing driven, with most of the data processing done in the cloud. Yet computing takes heavy toll on the environment, with data centres consuming over 200TWh/year. While green computing has been researched for close to two decades, it focused on solutions given today’s e-infrastructure, rather than rethinking new e-infrastructure models. Furthermore, recent years have shown that climate change has significant inverse effects on e-infrastructure, e.g. a flood in a small city can invalidate computing resources worldwide.
Aims of the Project
This project aims to quantify the interactions between climate change and e-infrastructure, enabling the development of green e-infrastructure, that is further resilient to climate change (see more details below).
By next year, 94% of the world’s computing is expected to run in the cloud, and demand keeps increasing. Covid-19 has further increased our dependence on e-infrastructure, and cloud computing in particular. However, current e-infrastructure is not sustainable nor resilient. It is anticipated that by 2025, 20% of the world’s electricity production will be used for data communications and processing. On the other hand, climate change effects increase the risk of e-infrastructure failures. Despite best efforts, repeatedly local weather events, such as floods and lightning storms, have worldwide ramifications.
Research to date has either focused on traditional infrastructure (e.g., electricity grid) or on data centres as the centre of computing.
This research project will explore the interactions between e-infrastructure and climate change. The project will explore current e-infrastructure deployment and its environmental footprint, and continue to study the effects of severe weather events on e-infrastructure. The knowledge gained will be used to build a model of e-infrastructure that enables exploring questions of sustainability and resilience.
The project allows to focus on one direction of effects (e-infrastructure on climate change or climate change on e-infrastructure), but it is likely that the synergy between the two topics will lead to a more interesting project.
Some of the questions likely to addressed by the developed model are:
How does current e-infrastructure affect the environment?
Will building e-infrastructure differently reduce its environmental footprint?
How can we minimise e-infrastructure effect on the environment through new e-infrastructure paradigms?
How do severe weather events propagate across e-infrastrcuture?
Can we increase e-infrastructure’s resilience to climate change by adopting new e-infrastructure paradigms?
The project will design a model of e-infrastructure that accounts for environmental events and effects, enabling to explore different e-infrastructure paradigm. The model will be evaluated through simulation, likely using modified existing simulation tools.
To take part in this project, a previous experience in programming (e.g., Python, C/C++, java) OR in modelling and simulations is required. Basic knowledge of computing concepts is an advantage, but it is expected to learn and gain during the project expert knowledge in e-infrastructure, computing and communications.
 Zilberman, N., Moore, A. W., & Crowcroft, J. A. (2016). From Photons to Big Data Applications: Terminating Terabits. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2014.0445.
 Cisco. (2018). Cisco Global Cloud Index: Forecast and Methodology, 2016–2021.
 Andrae, A. S. (2017). Total Consumer Power Consumption Forecast. Nordic Digital Business Summit.
 Nichols, S. (2018, September 4). Thunderstruck: Azure Back in Black(out) after High Voltage causes Flick of the Switch. The Register. https://www.theregister.co.uk/2018/09/04/thunderstruck_azure_backout/
Methods to be used
This research will modelling and simulation based.
Specialised skills required
Previous programming experience, or experience in modelling and simulations, is required. Knowledge of computing concepts is an advantage.
Please contact Noa Zilberman on firstname.lastname@example.org if you are interested in this project