Distributed Server Cluster Data Storage Group-Based Consistency
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Solution Overview
Problem
In distributed data storage systems, existing data consistency protocols require data to be written to more than half of the servers, leading to high server resource utilization and lower service availability due to limited resources.
Innovation Solution
A data storage method and server architecture where a master node broadcasts a data write request to groups of nodes, sending a confirmation message upon successful writing to more than half of the groups, and allows a candidate node to become a new master if fewer groups respond, reducing the number of nodes needed for data consistency and improving service availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is written to more than half of the servers to ensure data consistency, then data consistency is improved, but server resource utilization increases and service availability decreases
Solution Approach 1:
The patent divides the server cluster into multiple groups, where each group contains one or more servers. Data consistency is achieved by writing data to more than half of the groups rather than more than half of all individual servers. This segmentation reduces the total number of servers that need to participate in write operations, thereby improving service availability while maintaining data consistency.
2Reliability
If data is written to more than half of the servers to ensure data consistency, then data consistency is improved, but the number of nodes required increases
Solution Approach 1:
By segmenting servers into groups and requiring write acknowledgment from more than half of the groups rather than more than half of all servers, the patent reduces the quantity of individual nodes that must successfully write data. This allows the system to maintain strong data consistency guarantees while involving fewer total nodes in each write operation.
3Reliability
If server resources are allocated to data consistency operations, then data consistency is improved, but service processing efficiency decreases
Solution Approach 1:
The group-based architecture allows write operations to be distributed across fewer logical units (groups) rather than requiring coordination with every individual server. This reduces the overhead of data consistency operations and frees up server resources to handle service requests more efficiently.
Solution Approach 2:
The system implements a feedback mechanism where the master node receives write acknowledgments from group leaders, who in turn receive confirmations from their respective group members. This structured feedback approach streamlines the data consistency verification process and reduces unnecessary resource consumption.
Data Source
AI summary
Data may be stored in a distributed server cluster which includes a plurality of nodes. A specific implementation of a method for storing data in the distributed server cluster comprises: receiving a data write request, the data write request comprising to-be-written data; broadcasting the data write request to each of groups in the server cluster, the each of the groups comprising at least one node, and at least one of the groups comprising at least two nodes; and sending a notification message of successful writing to a client sending the data write request, in response to receiving a confirmation message fed back from more than a half of the groups.