A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 9 Issue 3
Mar.  2022

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 11.8, Top 4% (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
W. J. Huang, P. Y. Zhang, Y. T. Chen, M. C. Zhou, Y. Al-Turki, and A. Abusorrah, “QoS prediction model of cloud services based on deep learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 564–566, Mar. 2022. doi: 10.1109/JAS.2021.1004392
Citation: W. J. Huang, P. Y. Zhang, Y. T. Chen, M. C. Zhou, Y. Al-Turki, and A. Abusorrah, “QoS prediction model of cloud services based on deep learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 564–566, Mar. 2022. doi: 10.1109/JAS.2021.1004392

QoS Prediction Model of Cloud Services Based on Deep Learning

doi: 10.1109/JAS.2021.1004392
  • loading
  • [1]
    Y. Zhang, Z. Zheng, and M. R. Lyu, “Exploring latent features for memory-based QoS prediction in cloud computing,” in Proc. of 2011 IEEE 30th In. Symp. on Reliable Distributed Systems, pp. 1–10, Nov. 2011.
    [2]
    J. Zhu, P. He, Z. Zheng, and M. R. Lyu, “Online QoS prediction for runtime service adaptation via adaptive matrix factorization,” IEEE Trans. on Parallel and Distributed Systems, vol. 28, no. 10, pp. 2911–2924, Oct. 2017.
    [3]
    X. Zhu, X. Jing, D. Wu, Z. He, J. Cao, D. Yue, and L. Wang, “Similarity-maintaining privacy preservation and location-aware low-rank matrix factorization for QoS prediction based web service recommendation,” IEEE Trans. on Services Computing, vol. 14, no. 3, pp. 889–902, May–Jun. 2021.
    [4]
    Y. Zhang, P. Zhang, Y. Luo, and L. Ji, “Towards efficient, credible and privacy-preserving service QoS prediction in unreliable mobile edge environments,” in Proc. of 2020 In. Symp. on Reliable Distributed Systems (SRDS), pp. 309–318, Nov. 2020.
    [5]
    R. Xiong, J. Wang, Z. Li, B. Li, and P. Hung, “Personalized LSTM based matrix factorization for online QoS prediction,” in Proc. of 2018 IEEE In. Conf. on Web Services (ICWS), pp. 34–41, Sept. 2018.
    [6]
    X. Chen, B. Li, J. Wang, Y. Zhao, and Y. Xiong, ” Integrating EMD with multivariate LSTM for time series QoS prediction,” in Proc. of 2020 IEEE In. Conf. on Web Services (ICWS), pp. 58–65, Dec. 2020.
    [7]
    Z. Zheng, Y. Zhang, and M. Lyu, “Investigating QoS of real-world web services,” IEEE Trans. on Services Computing, vol. 7, no. 1, pp. 32–39, Jan.–Mar. 2014.
    [8]
    R. Salakhutdinov and A. Mnih, “Probabilistic matrix factorization,” Advances Neural Information Processing Systems, vol. 20, no. 1, pp. 1257–1264, Dec. 2007.
    [9]
    G. Zou, et al., “NDMF: Neighborhood-integrated deep matrix factorization for service QoS prediction,” IEEE Trans. on Network and Service Management, vol. 17, no. 4, pp. 2717–2730, Dec. 2020.
    [10]
    Y. Zhang, K. Wang, Q. He, F. Chen, S. Deng, Z. Zheng, and Y. Yang, “Covering-based web service quality prediction via neighborhood-aware matrix factorization, ” IEEE Trans. on Services Computing, pp. 1–12, Jan. 2019.
    [11]
    W. Yue, Z. Wang, J. Zhang, and X. Liu, “An overview of recommendation techniques and their applications in healthcare,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 701–717, Apr. 2021.
    [12]
    S. Imran, T. Mahmood, A. Morshed, and T. Sellis, “Big data analytics in healthcare − A systematic literature review and roadmap for practical implementation,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 1–22, Jan. 2021.

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(3)  / Tables(3)

    Article Metrics

    Article views (941) PDF downloads(147) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return