PopFlow: a novel flow management scheme for SDN switch of multiple flow tables based on flow popularity

Water and flow reductions in the channels downstream of water storage and hydropower projects have significant impacts on aquatic ecosystems. Understanding and analyzing the ecosystem status is of great significance to facilitate the protection of riverine ecosystems. A database was established based on the 2000–2017 environmental impact assessment (EIA) reports on water storage and hydropower projects in China, and corresponding analysis software was built based on an ArcGIS spatial analysis platform. The projects in China are mainly found in the Yangtze and Pearl River basins and in south-western China. The hydropower projects have a larger influence than the water storage projects on the flow of downstream rivers sections, and most of the hydropower projects, especially the water diversion projects, cause flow reductions in the downstream rivers. An ecological flow management mechanism in China implemented in 2006 provided a promising method to alleviate river flow reductions. However, there is still only one kind of ecological flow calculation method and few ecological flow regulation measures in use. Based on the advantages and problems of the existing ecological flow management system, this paper proposes a management scheme based on a regional-engineering calculation method. The results can facilitate decision making in ecological flow management.

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An Enhanced Service Flow Management Scheme for IEEE 802.16 Broadband Wireless Access Systems

International Journal of Computer Theory and Engineering ◽

10.7763/ijcte.2012.v4.515 ◽

2012 ◽

pp. 484-488

Author(s):

Juma Modie Mwamafundo ◽

Sang Kipkorir ◽

Felix Musau

Keyword(s):

Ieee 802.16 ◽

Wireless Access ◽

Broadband Wireless Access ◽

Flow Management ◽

Broadband Wireless ◽

Service Flow ◽

Management Scheme ◽

Broadband Wireless Access Systems

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DFMS: Differential flow management scheme for denial of service impact mitigation in 5G communications

Journal of King Saud University - Computer and Information Sciences ◽

10.1016/j.jksuci.2020.12.005 ◽

2020 ◽

Author(s):

P. Sakthibalan ◽

K. Devarajan

Keyword(s):

Denial Of Service ◽

Flow Management ◽

Impact Mitigation ◽

Management Scheme ◽

Differential Flow

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Effective TCP Flow Management Based on Hierarchical Feedback Learning in Complex Data Center Network

Sensors ◽

10.3390/s22020611 ◽

2022 ◽

Vol 22 (2) ◽

pp. 611

Author(s):

Kimihiro Mizutani

Keyword(s):

Reinforcement Learning ◽

Data Center ◽

Transmission Control Protocol ◽

Complex Structure ◽

Effective Bandwidth ◽

Complex Data ◽

Data Center Network ◽

Data Center Networks ◽

Flow Management ◽

Management Scheme

Many studies focusing on improving Transmission Control Protocol (TCP) flow control realize a more effective use of bandwidth in data center networks. They are excellent ways to more effectively use the bandwidth between clients and back-end servers. However, these schemes cannot achieve the total optimization of bandwidth use for data center networks as they do not take into account the path design of TCP flows against a hierarchical complex structure of data center networks. To address this issue, this paper proposes a TCP flow management scheme specified a hierarchical complex data center network for effective bandwidth use. The proposed scheme dynamically controls the paths of TCP flows by reinforcement learning based on a hierarchical feedback model, which obtains an optimal TCP flow establishment policy even if both the network topology and link states are more complicated. In evaluation, the proposed scheme achieved more effective bandwidth use and reduced the probability of TCP incast up to 30% than the conventional TCP flow management schemes: Variant Load Balancing (VLB), Equal Cost Multi Path (ECMP), and Intelligent Forwarding Strategy Based on Reinforcement Learning (IFS-RL) in the complex data center network.

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