Privacy-preserving energy sharing over converged communication-energy-compute networks
Author Identifier (ORCID)
Abstract
The rapid growth of edge cloud infrastructure introduces new challenges in managing energy consumption data while ensuring privacy during energy trading. Existing studies focused on smart metering privacy, local electricity markets, and privacy-aware control, whereas privacy-preserving cloudlet energy trading with battery support remains largely unexplored. This paper addresses these challenges by proposing an approach that effectively motivates cloudlets to trade their superfluous energy to minimize energy cost while protecting the privacy of energy usage information and the corresponding underlying data processing patterns. By applying Lyapunov optimization in coupling with differential privacy (DP), we develop a privacy-preserving energy trading algorithm where the cloudlet battery level and data backlog are modeled as virtual queues. This transforms the problem of interest from a long-term average objective to a convex per-instant optimization problem solved effectively. We analytically establish the trade-off between minimizing energy costs and maintaining the stability of both data queues and batteries. It is revealed that the effect of DP on average system costs can be minimized by allowing higher data queue and battery levels, ensuring robust privacy protection without sacrificing cost efficiency. The minimum capacity requirement for the batteries is identified for privacy guarantee. Simulations confirm the effectiveness of our approach, demonstrating up to a 34% reduction in average energy costs for cloudlets.
Keywords
cloudlet, differential privacy, energy trading, Laplace mechanism, power grid
Document Type
Journal Article
Date of Publication
1-1-2026
E-ISSN
23274697
Volume
13
Publication Title
IEEE Transactions on Network Science and Engineering
Publisher
IEEE
School
School of Engineering
Funding Information
Scientific Research Program of Higher Education Institutions in Gansu Province (Grant Number: 2026QB-092), Doctoral Research Foundation of Hexi University (Grant Number: KYQD2025003), Gansu Province University Industry Support Plan Project (Grant Number: 2025CYZC-060), National Natural Science Foundation of China (Grant Number: 62461022)
Copyright
subscription content
First Page
11283
Last Page
11300
Recommended Citation
Qi, L., Xiong, L., Wu, B., Ni, W., Li, K., Li, Y., Jamalipour, A., & Zeng, X. (2026). Privacy-preserving energy sharing over converged communication-energy-compute networks. IEEE Transactions on Network Science and Engineering, 13, 11283–11300. https://doi.org/10.1109/TNSE.2026.3726477