CAREER: A Robust and Data-driven Design for Carbon-intelligent Distributed Systems

点击翻译按钮获取中文摘要

The internet is a 24/7 service, it could be 24/7 carbon-free too. This is an ambitious goal that has been recently advocated by internet pioneer industries as a response of the computing domain to climate change. Achieving this goal requires the decarbonization of operations of geographically distributed digital infrastructure, e.g., data centers, providing services such as video streaming, or hosting compute-intensive applications. Despite a decade of effort on the sustainability of digital infrastructure, the current design is still inadequate to achieve the 24/7 carbon-free goal. The current design focuses to minimize the energy cost and/or consumption or maximize renewable participation. The latter is the closest effort towards the decarbonization goal; however, when the wind is not blowing or the sun is not shining, this design has no carbon intelligence, i.e., it obliviously draws energy from the grid without taking into account that the carbon intensity of grid changes over time due to existence of other carbon-free sources such as hydropower. This proposal explicitly considers carbon intelligence as a first-class design principle of digital infrastructure. It will develop and evaluate novel carbon-intelligent methodologies that are robust against uncertainty and provide a design space for data-driven adaptation for improved practical performance. The proposed theories will create a foundation for designing robust and data-driven systems and will be applicable more broadly to the computer and network systems. The carbon-intelligence approaches open new research directions for advancing the research at the intersection of computer science and sustainability. More broadly, this proposal is a response of the computing domain to climate change, one of the largest problems’ society has ever faced. Last, it creates opportunities for educational, sociotechnical, and outreach activities. The planned sociotechnical activities broaden the research outcome of this proposal for measuring and improving the inequity of the energy system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.