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  • Open Access


    Virtual Machine Consolidation with Multi-Step Prediction and Affinity-Aware Technique for Energy-Efficient Cloud Data Centers

    Pingping Li*, Jiuxin Cao

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 81-105, 2023, DOI:10.32604/cmc.2023.039076

    Abstract Virtual machine (VM) consolidation is an effective way to improve resource utilization and reduce energy consumption in cloud data centers. Most existing studies have considered VM consolidation as a bin-packing problem, but the current schemes commonly ignore the long-term relationship between VMs and hosts. In addition, there is a lack of long-term consideration for resource optimization in the VM consolidation, which results in unnecessary VM migration and increased energy consumption. To address these limitations, a VM consolidation method based on multi-step prediction and affinity-aware technique for energy-efficient cloud data centers (MPaAFVMC) is proposed. The proposed method uses an improved linear… More >

  • Open Access


    Video Frame Prediction by Joint Optimization of Direct Frame Synthesis and Optical-Flow Estimation

    Navin Ranjan1, Sovit Bhandari1, Yeong-Chan Kim1,2, Hoon Kim1,2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2615-2639, 2023, DOI:10.32604/cmc.2023.026086

    Abstract Video prediction is the problem of generating future frames by exploiting the spatiotemporal correlation from the past frame sequence. It is one of the crucial issues in computer vision and has many real-world applications, mainly focused on predicting future scenarios to avoid undesirable outcomes. However, modeling future image content and object is challenging due to the dynamic evolution and complexity of the scene, such as occlusions, camera movements, delay and illumination. Direct frame synthesis or optical-flow estimation are common approaches used by researchers. However, researchers mainly focused on video prediction using one of the approaches. Both methods have limitations, such… More >

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