SAVE

Server Adaptive Ventilation
This project is an attempt to optimize energy consumption of the data center ventilation systems by making it more adaptable to the computing load in servers.

Finding optimal control solutions for systems of high complexity Can not Be Achieved by Applying straightforward optimization algorithms. The results of our Recent research revealed That using distributed building automation system together with an accurate temporal thermal model of a server room, Substantial Amount of energy can be saved. Although we'll have created a predictive thermal model for server rooms, we Realized That current building automation systems utilized in data centers are inflexible And they do not exhibit enough intelligence and adaptability. To address These inadequacies, in this novel research methods based on cognitive algorithms, machine learning, and bio-inspired heuristics will be Explored. The results will be incorporated into an integrated solution and will ask Evaluated through simulations.