Mingxing Zhou^1,2, Peng Xiao³, Qixu Wang^1,2,*, Shuhua Ruan^1,2, Xingshu Chen^1,2, Menglong Yang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 957-979, 2024, DOI:10.32604/cmes.2023.028612

Abstract Due to the need for massive device connectivity, low communication latency, and various customizations in 6G architecture, a distributed cloud deployment approach will be more relevant to the space-air-ground-sea integrated network scenario. However, the openness and heterogeneity of the 6G network cause the problems of network security. To improve the trustworthiness of 6G networks, we propose a trusted computing-based approach for establishing trust relationships in multi-cloud scenarios. The proposed method shows the relationship of trust based on dual-level verification. It separates the trustworthy states of multiple complex cloud units in 6G architecture into the state within and between cloud units.… More >

Neema George^1,*, B. K. Anoop¹, Vinodh P. Vijayan²

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2281-2297, 2023, DOI:10.32604/csse.2023.028117

Abstract Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application. When workload execution, accuracy, and cost are accurately stabilized in opposition to the best possible framework in real-time, efficiency is attained. In addition, every workload or application required for the framework is characteristic and these essentials change over time. But, the existing method was failed to ensure the high Quality of Service (QoS). In order to address this issue, a Tricube Weighted Linear Regression-based Inter Quartile (TWLR-IQ) for Cloud Infrastructural Resource Optimization is introduced. A Tricube Weighted Linear Regression… More >

Amit Chhabra^{1, *}, Gurvinder Singh², Karanjeet Singh Kahlon²

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 813-834, 2020, DOI:10.32604/cmc.2020.010934

Abstract Cloud computing infrastructure has been evolving as a cost-effective platform for providing computational resources in the form of high-performance computing as a service (HPCaaS) to users for executing HPC applications. However, the broader use of the Cloud services, the rapid increase in the size, and the capacity of Cloud data centers bring a remarkable rise in energy consumption leading to a significant rise in the system provider expenses and carbon emissions in the environment. Besides this, users have become more demanding in terms of Quality-of-service (QoS) expectations in terms of execution time, budget cost, utilization, and makespan. This situation calls… More >