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

Jiajia Huang; Ying Sun; Xiao Jiang; Youpeng Huang; DongXu Zhou

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 Modelingbased 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.

POWER measurement (Electricity); CLOUD computing; SMART power grids; ENERGY management; ELECTRONIC data processing

EAI Endorsed Transactions on the Energy Web, 2024, Vol 11, Issue 1, p1

2032-944X

Academic Journal

10.4108/ew.5522