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  • Open Access

    ARTICLE

    A Fault-Tolerant Mobility-Aware Caching Method in Edge Computing

    Yong Ma1, Han Zhao2, Kunyin Guo3,*, Yunni Xia3,*, Xu Wang4, Xianhua Niu5, Dongge Zhu6, Yumin Dong7

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 907-927, 2024, DOI:10.32604/cmes.2024.048759 - 16 April 2024

    Abstract Mobile Edge Computing (MEC) is a technology designed for the on-demand provisioning of computing and storage services, strategically positioned close to users. In the MEC environment, frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery, ultimately enhancing the quality of the user experience. However, due to the typical placement of edge devices and nodes at the network’s periphery, these components may face various potential fault tolerance challenges, including network instability, device failures, and resource constraints. Considering the dynamic nature of MEC, making high-quality content caching decisions… More >

  • Open Access

    ARTICLE

    A Novel Interacting Multiple-Model Method and Its Application to Moisture Content Prediction of ASP Flooding

    Shurong Li1,*, Yulei Ge2, Renlin Zang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.1, pp. 95-116, 2018, DOI:10.3970/cmes.2018.114.095

    Abstract In this paper, an interacting multiple-model (IMM) method based on data-driven identification model is proposed for the prediction of nonlinear dynamic systems. Firstly, two basic models are selected as combination components due to their proved effectiveness. One is Gaussian process (GP) model, which can provide the predictive variance of the predicted output and only has several optimizing parameters. The other is regularized extreme learning machine (RELM) model, which can improve the over-fitting problem resulted by empirical risk minimization principle and enhances the overall generalization performance. Then both of the models are updated continually using meaningful… More >

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