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Volumn , Issue , 2014, Pages 9-14

Online traffic prediction in the cloud: A dynamic window approach

Author keywords

Cloud computing; network traffic prediction; short range dependence; sliding window algorithm

Indexed keywords

CLOUD COMPUTING; DYNAMICS; MEAN SQUARE ERROR;

EID: 84922552091     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FiCloud.2014.12     Document Type: Conference Paper
Times cited : (15)

References (16)
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  • 7
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    • Vieira, K.1    Schulter, A.2    Westphall, C.3    Westphall, C.4
  • 8
    • 84889094568 scopus 로고    scopus 로고
    • Anomaly secure detection methods by analyzing dynamic characteristics of the network traffic in cloud communications
    • W. Xiong, H. Hu, N. Xiong, L. T. Yang, W.-C. Peng, X. Wang, and Y. Qu, "Anomaly secure detection methods by analyzing dynamic characteristics of the network traffic in cloud communications," Information Sciences, vol. 258, no. 0, pp. 403-415, 2013.
    • (2013) Information Sciences , vol.258 , Issue.0 , pp. 403-415
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  • 9
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  • 10
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  • 12
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    • Small-time scale network traffic prediction based on flexible neural tree
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    • Y. Chen, B. Yang, and Q. Meng, "Small-time scale network traffic prediction based on flexible neural tree," Applied Soft Computing, vol. 12, no. 1, pp. 274-279, 2012.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.