Quality of Service-aware Elastic Flow Aggregation Based on Enhanced Rough K-Means

Zheng WU; Yuning DONG; Wei TIAN; Pingping TANG

doi:10.11999/JEIT181169

Volume 41 Issue 12

Dec. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(12): 3036-3042

Zheng WU, Yuning DONG, Wei TIAN, Pingping TANG. Quality of Service-aware Elastic Flow Aggregation Based on Enhanced Rough K-Means[J]. Journal of Electronics & Information Technology, 2019, 41(12): 3036-3042. doi: 10.11999/JEIT181169

Citation:

Zheng WU, Yuning DONG, Wei TIAN, Pingping TANG. Quality of Service-aware Elastic Flow Aggregation Based on Enhanced Rough K-Means[J]. Journal of Electronics & Information Technology, 2019, 41(12): 3036-3042. doi: 10.11999/JEIT181169

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Quality of Service-aware Elastic Flow Aggregation Based on Enhanced Rough K-Means

doi: 10.11999/JEIT181169

1.
College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2.
College of Physics and Electronic Information, Anhui Normal University, Wuhu 241000, China

Funds: The National Natural Science Foundation of China (61271233), The Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18 0894)

Received Date: 2018-12-19
Rev Recd Date: 2019-04-08

Available Online: 2019-04-22

Publish Date: 2019-12-01

Abstract

Abstract

Facing changeable network environment, current Quality of Service (QoS)-aware flow aggregation scheme is lack of flexibility. A dynamic flow aggregation method to overcome present problems is proposed. An Enhanced Rough K-Means (ERKM) algorithm is used to aggregate network flows properly. Importantly, it is able to adjust degree of membership to face ever-changing internet environment to make algorithm more flexible. Internet scheduler experiment is carried out and a comparison is made with existing methods. Experimental results suggest that proposed method has advantages not only on flexibility of aggregation, but also on assurance of QoS of Internet flows. In addition, the consistency of QoS allocation under different network environment is investigated.
- Flow aggregation,
- Enhanced Rough K-Means(ERKM),
- Quality of Service(QoS) mapping,
- Degree of membership

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References(19)

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