T-DCORAL: A Threshold-Based Dynamic Controller Resource Allocation for Elastic Control Plane in Software-Defined Data Center Networks

2019 ◽  
Vol 23 (2) ◽  
pp. 198-201 ◽  
Author(s):  
Woojoong Kim ◽  
James Won-Ki Hong ◽  
Young-Joo Suh
Keyword(s):  
Resource Allocation ◽  
Data Center ◽  
Control Plane ◽  
Data Center Networks ◽  
Dynamic Controller

Resource Allocation in Electrical/Optical Hybrid Switching Data Center Networks

2017 ◽  
Vol 9 (8) ◽  
pp. 648 ◽  
Author(s):  
Zhangxiao Feng ◽  
Weiqiang Sun ◽  
Jie Zhu ◽  
Junyi Shao ◽  
Weisheng Hu
Keyword(s):  
Resource Allocation ◽  
Data Center ◽  
Data Center Networks ◽  
Hybrid Switching

scholarly journals An Efficient Wireless Control Plane for Software Defined Networking in Data Center Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 58158-58167
Author(s):  
Zuneera Umair ◽  
Umair Mujtaba Qureshi ◽  
Yingying Cheng ◽  
Xiaohua Jia
Keyword(s):  
Data Center ◽  
Software Defined Networking ◽  
Control Plane ◽  
Data Center Networks ◽  
Wireless Control

Cost and Security-Aware Resource Allocation in Optical Data Center Networks

2019 ◽  
Vol 23 (11) ◽  
pp. 2031-2035 ◽  
Author(s):  
Bo Yi ◽  
Xingwei Wang ◽  
Min Huang ◽  
Liuqing Yang
Keyword(s):  
Resource Allocation ◽  
Data Center ◽  
Optical Data ◽  
Data Center Networks

scholarly journals Class-based Flow Scheduling Framework in SDN-based Data Center Networks

2020 ◽  
Author(s):  
Maiass Zaher ◽  
Aymen Alawadi ◽  
Sandor Molnar
Keyword(s):  
Quality Of Service ◽  
Data Center ◽  
Completion Time ◽  
Emerging Technologies ◽  
Control Plane ◽  
Traffic Patterns ◽  
Data Center Networks ◽  
Available Bandwidth

The emerging technologies leveraging Data Center Networks (DCN) and their consequent traffic patterns impose more necessity for improving Quality of Service (QoS). In this paper, we propose Sieve, a new distributed SDN framework that efficiently schedules flows based on the available bandwidth to improve Flow Completion Time (FCT) of mice flows. In addition, we propose a lightweight sampling mechanism to sample a portion of flows. In particular, Sieve schedules the sampled flows, and it reschedules only elephant flows upon threshold hits. Furthermore, our framework allocates a portion of the flows to ECMP, so that the associated overhead can be mitigated in the control plane and ECMP-related packet collisions are fewer as well. Mininet has been used to evaluate the proposed solution, and Sieve provides better FCT up to 50% in comparison to the existing solutions like ECMP and Hedera.

scholarly journals Distributed Resource Allocation for Data Center Networks: A Hierarchical Game Approach

2018 ◽  
pp. 1-1 ◽  
Author(s):  
Huaqing Zhang ◽  
Yong Xiao ◽  
Shengrong Bu ◽  
Richard Yu ◽  
Dusit Niyato ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Data Center ◽  
Data Center Networks ◽  
Distributed Resource Allocation
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