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ew 24(1):

Research Article

Construction and Research on Cloud-edge Collaborative Power Measurement and Security Model

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  • @ARTICLE{10.4108/ew.5522,
        author={Jiajia Huang and Ying Sun and Xiao Jiang and Youpeng Huang and DongXu Zhou},
        title={Construction and Research on Cloud-edge Collaborative Power Measurement and Security Model},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={11},
        number={1},
        publisher={EAI},
        journal_a={EW},
        year={2024},
        month={3},
        keywords={Cloud-Edge Computing, Power Measurement, Security Model, Collaborative Systems, Smart Grids},
        doi={10.4108/ew.5522}
    }
    
  • Jiajia Huang
    Ying Sun
    Xiao Jiang
    Youpeng Huang
    DongXu Zhou
    Year: 2024
    Construction and Research on Cloud-edge Collaborative Power Measurement and Security Model
    EW
    EAI
    DOI: 10.4108/ew.5522
Jiajia Huang1,*, Ying Sun2,*, Xiao Jiang3,*, Youpeng Huang3,*, DongXu Zhou3,*
  • 1: Guangdong Power Grid Co., Ltd. ShaoGuan Power Supply Bureau. No. 66 Gongye West Road, Wujiang District, Shaoguan City, Guangdong Province, 512000, China
  • 2: Guangdong Power Grid Corporation No. 757 Dongfeng East Road, Yuexiu District, Guangzhou City, Guangdong Province, 510600,China
  • 3: Metrology Center of Guangdong Power Grid Corporation, Yuedian Building No. 8 Shuijungang, Dongfeng East Road, Yuexiu District, Guangzhou City, 510000, China
*Contact email: zhoudongxu_jlzx@163.com, zhoudongxu_jlzx@163.com, zhoudongxu_jlzx@163.com, zhoudongxu_jlzx@163.com, zhoudongxu_jlzx@163.com

Abstract

Accurate power consumption assessment is of critical importance in the fast-evolving world of cloud and edge computing. These technologies enable rapid data processing and storage but they also require huge amounts of energy. This energy requirement directly impacts operational costs, as well as environmental responsibility. We are conducting research to develop a specialized cloud-edge power measurement and security model. This model delivers reliable power usage data from these systems while maintaining security for the data they process and store. A combination of simulation-based analysis and real-world experimentation helped us to deliver these results. Monte Carlo based simulations produced power usage predictions under various conditions and Load Testing validated their real-world performance. A Threat Modeling-based security study identified potential vulnerabilities and suggested protection protocols. A collaborative approach enhances power measurements accuracy and encourages secure operation of the combined cloud-edge systems. By fusing these metrics, a more efficient and secure operation of computing resources becomes possible. This research underscores the critical importance of developing advanced techniques for power metering and security in cloud-edge computing systems. Future research may focus on both expanding the model’s use to an array of larger, more complex networks, as well as the inclusion of AI driven predictive analytics to amplify accuracy of power management.

Keywords
Cloud-Edge Computing, Power Measurement, Security Model, Collaborative Systems, Smart Grids
Received
2023-09-29
Accepted
2024-03-20
Published
2024-03-22
Publisher
EAI
http://dx.doi.org/10.4108/ew.5522

Copyright © 2024 Huang et al., licensed to EAI. This is an open access article distributed under the terms of the CC BYNC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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