Shui Liu^1,2, Ke Xiong^1,2,*, Yeshen Li^1,2, Zhifei Zhang^1,2,*, Yu Zhang³, Pingyi Fan⁴

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5077-5093, 2025, DOI:10.32604/cmc.2025.064880 - 30 July 2025

Abstract Accurate prediction of cloud resource utilization is critical. It helps improve service quality while avoiding resource waste and shortages. However, the time series of resource usage in cloud computing systems often exhibit multidimensionality, nonlinearity, and high volatility, making the high-precision prediction of resource utilization a complex and challenging task. At present, cloud computing resource prediction methods include traditional statistical models, hybrid approaches combining machine learning and classical models, and deep learning techniques. Traditional statistical methods struggle with nonlinear predictions, hybrid methods face challenges in feature extraction and long-term dependencies, and deep learning methods incur high… More >

Ahmed Y. Hamed¹, M. Kh. Elnahary^1,*, Faisal S. Alsubaei², Hamdy H. El-Sayed¹

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2133-2148, 2023, DOI:10.32604/cmc.2023.032215 - 22 September 2022

Abstract Cloud computing has taken over the high-performance distributed computing area, and it currently provides on-demand services and resource polling over the web. As a result of constantly changing user service demand, the task scheduling problem has emerged as a critical analytical topic in cloud computing. The primary goal of scheduling tasks is to distribute tasks to available processors to construct the shortest possible schedule without breaching precedence restrictions. Assignments and schedules of tasks substantially influence system operation in a heterogeneous multiprocessor system. The diverse processes inside the heuristic-based task scheduling method will result in varying… More >

Yangjae Lee¹, Sung Hoon Baek², Jung Taek Seo³, Ki-Woong Park^1,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4911-4929, 2022, DOI:10.32604/cmc.2022.026657 - 21 April 2022

Abstract One of the latest technologies enabling remote control, operational efficiency upgrades, and real-time big-data monitoring in an industrial control system (ICS) is the IIoT-Cloud ICS, which integrates the Industrial Internet of Things (IIoT) and the cloud into the ICS. Although an ICS benefits from the application of IIoT and the cloud in terms of cost reduction, efficiency improvement, and real-time monitoring, the application of this technology to an ICS poses an unprecedented security risk by exposing its terminal devices to the outside world. An adversary can collect information regarding senders, recipients, and prime-time slots through… More >