DDPG-Based Energy-Efficient Flow Scheduling Algorithm in Software-Defined Data Centers

With the rapid development of data centers, the energy consumption brought by more and more data centers cannot be underestimated. How to intelligently manage software-defined data center networks to reduce network energy consumption and improve network performance is becoming an important research...

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Bibliographic Details
Published inWireless communications and mobile computing Vol. 2021; no. 1
Main Authors Yao, Zan, Wang, Ying, Meng, Luoming, Qiu, Xuesong, Yu, Peng
Format Journal Article
LanguageEnglish
Published Oxford Hindawi 2021
John Wiley & Sons, Inc
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ISSN1530-8669
1530-8677
DOI10.1155/2021/6629852

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Summary:With the rapid development of data centers, the energy consumption brought by more and more data centers cannot be underestimated. How to intelligently manage software-defined data center networks to reduce network energy consumption and improve network performance is becoming an important research subject. In this paper, for the flows with deadline requirements, we study how to design the rate-variable flow scheduling scheme to realize energy-saving and minimize the mean completion time (MCT) of flows based on meeting the deadline requirement. The flow scheduling optimization problem can be modeled as a Markov decision process (MDP). To cope with a large solution space, we design a DDPG-EEFS algorithm to find the optimal scheduling scheme for flows. The simulation result reveals that the DDPG-EEFS algorithm only trains part of the states and gets a good energy-saving effect and network performance. When the traffic intensity is small, the transmission time performance can be improved by sacrificing a little energy efficiency.
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ISSN:1530-8669
1530-8677
DOI:10.1155/2021/6629852