A Back Propagation Neural Network for Evaluating Collaborative Performance in Cloud Computing
被引:0
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作者:
Song, Biao
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机构:
Kyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South KoreaKyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South Korea
Song, Biao
[1
]
Hassan, Mohammad Mehedi
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机构:
Kyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South KoreaKyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South Korea
Hassan, Mohammad Mehedi
[1
]
Tian, Yuan
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机构:
Kyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South KoreaKyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South Korea
Tian, Yuan
[1
]
Huh, Eui-Nam
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h-index: 0
机构:
Kyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South KoreaKyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South Korea
Huh, Eui-Nam
[1
]
机构:
[1] Kyung Hee Univ, Dept Comp Engn, Yongin 446701, Gyeonggi Do, South Korea
来源:
GRID AND DISTRIBUTED COMPUTING
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2009年
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63卷
关键词:
Back Propagation Neuron Network;
Partner Selection;
Dynamic Collaboration;
D O I:
暂无
中图分类号:
TP3 [计算技术、计算机技术];
学科分类号:
0812 ;
摘要:
The partner selection is an important decision problem in the formation of dynamic collaboration among Cloud Provides (CPs) To acquire optimal collaboration, both Individual and collaborative performance of candidate partners should be considered In the existing methods for partner selection, the collaborative performance is evaluated by using linear functions which cannot address the comprehensive relationships among candidate partners This paper proposes an evaluation approach using Back Propagation Neuron Network (BPNN) instead of any fixed objective function Through training, the BPNN can achieve function approximation and provide estimates of collaborative performance The experiment results show that our approach is effective and accurate in the evaluation.