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Edge-Preserving Consensus by Exploring the Feedback-Based Masking Method
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AI
DOI：10.1109/LSP.2025.3542636.png)
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Abstract
En 中文
This brief deals with the edge-preserving consensus in networked agent groups, which seeks to keep the information of the state trajectories of agents private by utilizing an edge-based decentralized protocol design. A novel type of decentralized feedback-based masking approach is adopted for designing local channel filters such that the agents reach consensus under the heterogenous channel filters, where the information of the filter associated with a specific communication link can only be known by the agents who share this communication link. Our design guarantees asymptotical convergence to the consensus value for both the cases of the non-recursive and recursive nominal filters. Moreover, the algorithms for designing the masking elements are provided, by using the parallel realization of several stable fundamental elements and the bisection method for searching the gain.
Keywords:
Privacy
Protocols
Transfer functions
Eigenvalues and eigenfunctions
Signal processing algorithms
Multi-agent systems
Design methodology
Artificial intelligence
Wireless sensor networks
Vehicle dynamics
Edge-preserving consensus
security
distributed networks
channel filter
Journal
IF:
9.6
Papers:
1.1W
Citations:
1.7W
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