Data center heat distribution modeling using onboard sensors - Rubio, Jessi Christa R.
Uneven cooling in data centers can be detrimental to server performance. To maintain the desired cooling environment and avoid overworked cooling units, an appropriate thermal management strategy is necessary such as creating effective visual thermal maps to characterize cold air and hot air distribution. Given environmental sensor measurements, these maps embody heat distribution models which are numerically analyzed. Enabling reliable and real-time heat distribution monitoring suggests the need for computationally efficient and accurate models and optimized sensor placements. This study presents a customized or Custom heat distribution modeling based on continuity-momentum and convection-diffusion equations, and applying onboard server sensor measurements only instead of combining it with external server sensor measurements. To easily determine heat contributors, the Custom model considers generated internal server hot air. With the Navier-Stokes model using external and onboard sensor measurements as the baseline, the Laplacian-convection-diffusion (LCD) and the Custom models as well as the onboard versions of all models provide a comparable mean MAEs < 5°C. The Custom model produces competitive results of = 4.27°C mean MAE and a notable 1.095°C mean MAE using both external and onboard sensors in areas where cooling vents are located. The Custom model converges at 18 seconds, faster than Navier-Stokes but slower than LCD. In essence, the Custom model using onboard sensors reasonably provides the most computationally accurate, efficient and attainable solution suitable for real-time monitoring and effective in reducing electrical costs in the data cente