Raft Node State Transition for Sub-Cluster Reintegration
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Solution Overview
Problem
In network clusters using Byzantine Fault Tolerance-Raft (BFT-Raft), when a cluster splits into isolated sub-clusters due to network interruptions, the operational reliability is low as node devices in one sub-cluster ignore voting requests and heartbeat information from another, preventing reintegration into a single system.
Innovation Solution
Node devices in a leader state obtain cycle length information and latest log indexes from voting requests, degrading their state to follower or candidate if the information is greater than their own, allowing participation in elections across sub-clusters and reintegration into a single system until a new leader node is established.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a node device in leader state ignores voting requests and heartbeat information from other sub-clusters, then the leader state is maintained, but the system cannot be reintegrated into a single system and operational reliability is low
Solution Approach 1:
The node device dynamically adjusts its state based on received voting requests. When voting requests are received during leader state, the device transitions to follower or candidate state, allowing the system to adapt to network recovery scenarios and enable reintegration of sub-clusters.
Solution Approach 2:
The invention changes the operational parameters of the node device by introducing conditions under which a leader node should transition to follower or candidate state. This parameter change enables the system to handle split-brain scenarios and improves operational reliability through state flexibility.
2Stability of the object's composition
If a node device in leader state always ignores voting requests, then the leader state stability is maintained, but the device cannot combine with other sub-clusters into one system
Solution Approach 1:
The node device employs dynamic state transition based on received voting requests. Instead of statically ignoring all voting requests, the leader node dynamically evaluates incoming requests and transitions to follower or candidate state when appropriate, balancing stability with adaptability.
Solution Approach 2:
The invention introduces feedback mechanisms where the leader node responds to voting requests from other sub-clusters. This feedback loop enables the system to detect split-brain scenarios and trigger appropriate state transitions, allowing reintegration while maintaining stability through controlled responses.
Data Source
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AI summary
This application discloses a node device operation method, a work status switching apparatus, a node device, and a medium, and relates to the field of network technologies. The method includes: receiving voting requests of a plurality of node devices, a quantity of the plurality of node devices being greater than half a quantity of node devices in a system; obtaining cycle length information and latest log indexes from the voting requests of the plurality of node devices if a current node device operates in a leader state; and switching a current work status from the leader state to a follower state or a candidate state if all the cycle length information in the voting requests of the plurality of node devices is greater than cycle length information of the current node device and all the latest log indexes in the voting requests of the plurality of node devices are not less than a latest log index of the current node device. This application enables that a first sub-cluster and a second sub-cluster can be combined into one system to work together, thereby improving the operational reliability of the system.