An SDN energy saving method based on topology switch and rerouting

Ba, Junhua; Wang, Ying; Zhong, Xuxia; Feng, Sixiang; Qiu, Xuesong; Guo, Shaoyong

doi:10.1109/noms.2018.8406202

Cited by 10 publications

(4 citation statements)

References 19 publications

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“…The authors reported that the traffic patterns of GEANT networks are generally regular and predictable in [19]. To save power, they divided the traffic into intervals, and implemented link sleeping, which temporarily suspends certain links when the minimum or maximum link utility thresholds were met.…”

Section: ) Elastic-trees: Need For Correlation-aware Power Optimizationmentioning

confidence: 99%

Survey of Routing Techniques-Based Optimization of Energy Consumption in SD-DCN

Nsaif,

Kovásznai,

Malik

et al. 2023

Infocommunications journal

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The increasing power consumption of Data Center Networks (DCN) is becoming a major concern for network operators. The object of this paper is to provide a survey of state-of-the-art methods for reducing energy consumption via (1) enhanced scheduling and (2) enhanced aggregation of traffic flows using Software-Defined Networks (SDN), focusing on the advantages and disadvantages of these approaches. We tackle a gap in the literature for a review of SDN-based energy saving techniques and discuss the limitations of multi-controller solutions in terms of constraints on their performance. The main finding of this survey paper is that the two classes of SDNbased methods, scheduling and flow aggregation, significantly reduce energy consumption in DCNs. We also suggest that Machine Learning has the potential to further improve these classes of solutions and argue that hybrid ML-based solutions are the next frontier for the field. The perspective gained as a consequence of this analysis is that advanced ML-based solutions and multi-controller-based solutions may address the limitations of the state-of-the-art, and should be further explored for energy optimization in DCNs.

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Section: ) Elastic-trees: Need For Correlation-aware Power Optimizationmentioning

confidence: 99%

Survey of Routing Techniques-Based Optimization of Energy Consumption in SD-DCN

Nsaif,

Kovásznai,

Malik

et al. 2023

Infocommunications journal

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“…Data Center Network Energy-Saving Technology. In terms of data center network energy-saving technologies, there is a lot of research, which can be divided into energysaving topology design [12], and energy-saving routing and flow scheduling schemes [13][14][15][16][17][18][19][20][21], which are mainly based on the DS energy cost model or the ALR energy cost model.…”

Section: Related Workmentioning

confidence: 99%

“…Ref. [17] proposed an online switching mechanism of multiple topologies in the data plane, which can sleep some devices and ports to achieve energy saving while meeting the dynamic demand of traffic. Li et al [18] explored a new energy-aware flow preempting scheduling method in the time dimension and used the policy of EXR (exclusive routing), i.e., each flow preempted the route according to the priority and occupied its own route.…”

Section: Related Workmentioning

confidence: 99%

“…The network energy-saving technology can be divided into three types: topology design and transformation [12], device sleeping (DS) [13][14][15][16][17][18], and adaptive link rate (ALR) [19][20][21]. The energy-saving topology design and transformation mainly studies how to maximize the ratio of the forward-ing capacity provided by the topology to the total energy consumption of the network under constraint conditions, to improve the utilization rate of topology energy consumption.…”

Section: Introductionmentioning

confidence: 99%

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

Yao

Wang

Meng

et al. 2021

Wireless Communications and Mobile Computing

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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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