DESC: Type I: Data-driven system-design for sustainable long-lasting distributed infrastructures

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To mitigate the effects of climate change, it is crucial to transition to a carbon-free economy where existing infrastructures no longer rely on carbon-based electricity. However, the rapid growth in computing demand has resulted in a significant increase in overall energy consumption, which has a detrimental impact on carbon emissions. While current research has primarily focused on reducing energy consumption, it is important to recognize that improving energy efficiency alone does not necessarily lead to reducing carbon emissions. Highly energy-efficient systems may still produce substantial carbon emissions. To effectively reduce emissions from computing systems, it is essential to consider the entire lifecycle of these systems. This project aims to develop novel lifespan-aware operation and emission-reduction strategies for distributed computing infrastructures that enable these systems to consider lifecycle emissions, promoting the longevity of computing systems and facilitating emission reduction. The project's broader impacts include developing prototypes and educational resources for K-12 and undergraduate levels. Designing distributed computing systems requires rethinking how systems can operate on clean energy sources and maintain longevity despite demand and supply uncertainties. This project addresses this challenge by designing a lifetime management system that incorporates principles of safe computing to ensure system operation and prevent degradation or failures. It focuses on developing emission-reduction strategies using novel models and policies integrated into container-based orchestration platforms. This enables applications to make sound decisions with regard to emissions and regulate their services based on the implications of these decisions. Additionally, this project also focuses on minimizing embodied emissions by extending the system's lifespan and proposing novel mechanisms and policies that adjust application resources to ensure systems operate at safe levels. Finally, techniques are developed to jointly reduce both energy use and embodied emissions, leveraging spatial and temporal variations in emissions and workload. Together, these mechanisms and policies will provide a new technical foundation for emission-aware applications.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.