TY - JOUR
T1 - Asynchronous Weighted Multi-Fan Control for Energy-Efficient Server Thermal Management
AU - Burak Demir
AU - Elif Arslan
AU - Mehmet Kaya
AU - Selin Kurt
JF - Journal of Smart Grids, Energy Analytics and Optimization
JO - J Smart Grids Energy Anal Optim
Y1 - 2023
VL - 2
IS - 1
SP - 55
N2 - Each server in data centers contains multiple fans and various heat-generating components. Factors such as fan speeds, component layout, and workload conditions affect airflow and temperature distribution within the server. Consequently, server thermal management is regarded as a Multi-Input Multi-Output (MIMO) nonlinear control system that cannot be effectively analyzed or controlled using conventional linear system techniques. This study implements a multi-fan thermal control approach for servers by applying a weighting mechanism that assigns distinct weights to each cooling fan, enabling asynchronous adjustment of multiple fans. This is combined with the Evolutionary Strategy (ES) algorithm and carefully designed fitness functions. The proposed system can identify near-optimal weighting combinations within a small number of search iterations, tailored to various workload scenarios. By asynchronously adjusting the fans according to these weightings, the system achieves near-optimal energy efficiency while still satisfying the server’s thermal requirements—specifically, the maximum allowable temperatures for the CPU and PCIe components. Compared with traditional synchronous fan modulation, this asynchronous multi-fan control method reduces the total fan power consumption by an average of 43.1%. It requires searching only 14.2% of all possible weighting combinations across the eight experimental workload scenarios. Moreover, the probability that each identified near-optimal weighting corresponds to the global optimal solution is 47.5%. Experimental results confirm that the proposed asynchronous multi-fan control system successfully meets thermal specifications while delivering near-optimal energy savings for the server. Therefore, the developed approach proves practical and highly effective for substantial energy reduction, without requiring the development of mathematical thermal models or the analysis of extensive datasets. In the future, by fine-tuning the system’s code parameters, it could potentially be adapted to different server architectures. 
UR - https://isespub.com/g508529074
ER -