FRCR:Raft consensus scheme based on semi asynchronous federal reconstruction

Today, Raft's distributed cluster scale is growing rapidly and cluster throughput is declining. The Raft consensus algorithm needs to be continuously optimized to adapt to a complex and changeable application environment. To solve the above problems, we propose a federal reconstruction Committe...

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Bibliographic Details
Published in:IEEE eTransactions on network and service management Vol. 19; no. 4; p. 1
Main Authors: Rong, Baojun, Zheng, Zhaohui
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Clustering algorithms
Clusters
Committee
Data models
Distributed consensus
Elections
Federal reconstruction
Federated learning
Reconstruction
Security
Semi asynchronous aggregation
Servers
Training
Voting
ISSN:1932-4537, 1932-4537
Online Access:Get full text
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Summary:Today, Raft's distributed cluster scale is growing rapidly and cluster throughput is declining. The Raft consensus algorithm needs to be continuously optimized to adapt to a complex and changeable application environment. To solve the above problems, we propose a federal reconstruction Committee Raft consensus algorithm FRCR. Based on the Federation reconstruction technology, the algorithm trains, updates and evaluates the model of the characteristic data set of the Raft node, runs the model to get the nodes with better performance, constructs the committee mechanism, and improves the quality and speed of the election. We also design a semi asynchronous buffer mechanism and a strategy to resist malicious node attacks to solve the inconsistency and security problems of federation aggregation. Finally, seven aspects of FRCR are tested and analyzed to verify the effectiveness of FRCR in the consensus cluster.
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ISSN:1932-4537
1932-4537
DOI:10.1109/TNSM.2022.3217332