Shaolei Ren and Yuxiong He
Due to the enormous energy consumption and associated environmental concerns, data centers have been increasingly pressured to reduce long-term net carbon footprint to zero, i.e., carbon neutrality. In this paper, we propose an online algorithm, called CACO (optimizing for COst minimization and CArbon neutrality), for minimizing data center operational cost while satisfying carbon neutrality without long-term future information.
Unlike the existing research, CACO enables distributed server-level resource management: each server autonomously adjusts its processing speed and optimally decides the amount of workloads to process. We prove that CACO achieves a close-to-minimum operational cost (incorporating both electricity and delay costs) compared to the optimal algorithm with future information, while bounding the potential violation of carbon neutrality. We also perform trace-based simulation studies to complement the analysis, and the results show that CACO reduces the cost by more than 25% (compared to the state of the art) while resulting in a smaller carbon footprint.
In Super Computing