Publication Type : Conference Paper
Publisher : IEEE
Source : Third International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS),IEEE,2024
Campus : Chennai
School : School of Computing
Year : 2024
Abstract : In this ever-growing technological world where the cloud plays a massive role in accommodating all the resources, there has been an increase in the amount of pressure on the environment. Though the cloud helps us reduce the physical server space, it still requires data centers to track its activity. With data centers accounting for a substantial portion of global energy usage, there is a pressing need to address the sustainability challenges posed by their operations. This paper aims to explore the critical topic of “Energy Efficiency in Heterogenous Cloud Data Centers” by inculcating a combination of Q-Learning and Deep-Q networks. With this, we can create an optimized algorithm that best fits the situation of high-energy-consuming data centers and enhances their efficiency.
Cite this Research Publication : Pandimurugan, V; Balakiruthiga, B; Rajaram, V; Umamageswaran, J; Angayarkanni, SA; Rajasoundaran, S; “Energy Efficiency in Heterogenous Cloud Data Centers by Inculcating a Combination of Q-Learning and Deep Q-Networks”, Third International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS),IEEE,2024