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Differential Privacy Consensus in Dynamic Topologies: Performance Analysis and Optimization
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DOI：10.1109/TCSI.2025.3599614.png)
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Abstract
En 中文
This paper investigates the differential privacy consensus problem for a class of multiagent systems under dynamic topologies. To meet the requirements of power consumption, a random communication strategy is proposed in which each agent sends data to its neighbors with different probabilities. For analyzing the effect of time-varying topology and coupling strength among agents on system performance, a necessary and sufficient condition for almost sure convergence of differential privacy consensus systems is established. Furthermore, the convergence rate and convergence accuracy of the system are also studied. By formulating the communication costs and topological characteristics as a constrained problem, a convex optimization algorithm for fast convergence of the differential privacy consensus system is proposed. In addition, the differential privacy of the agents is analyzed, and the optimal noise parameters that achieve a trade-off between convergence accuracy and privacy levels are derived. A numerical simulation is presented to demonstrate the effectiveness of the developed approach.
Keywords:
Dynamic topology
average consensus
differential privacy
convergence
trade-off
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