Dynamic Frequency Adjustment and Dispatching for Cloud Computing System with Energy Cost Considerations
Series/Report No.
Lecture Notes in Mechanical Engineering
Part Of
International Conference on Flexible Automation and Intelligent Manufacturing
Start Page
197
End Page
205
ISSN
2195-4356
2195-4364
ISBN
9783031744846
9783031744853
Date Issued
2024
Author(s)
DOI
10.1007/978-3-031-74485-3_22
Abstract
This research studies the dynamic frequency adjustment and task dispatching problems for cloud computing systems under user demand uncertainties. The objective of the research is to minimize energy consumption and waiting costs. A dynamic programming model is presented to minimize total costs by adjusting CPU frequency dynamically. In this model, we implement real-time job dispatching based on the current state. With the objective of minimizing the total waiting time for tasks. Additionally, the model employs a stochastic process to accurately estimate the transition probability between various events. Backward induction is used to solve the model and make the optimal decision for the different states. Compared with other control methods from the literature, our numerical results show that the proposed method reduces total energy and waiting costs. The improvement is particularly significant when cloud servers and tasks have higher heterogeneity. This approach provides a comprehensive solution to the challenges of cloud computing, balancing performance and cost efficiency.
Event(s)
33rd International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2024, Taichung, 23 June 2024 through 26 June 2024. Code 323949
Subjects
Cloud computing
Dynamic dispatching
Stochastic process
Publisher
Springer Nature Switzerland
Type
conference paper