Storage Node Data Replication with Priority Queues
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Solution Overview
Problem
Existing distributed data storage systems face challenges in maintaining data robustly and reliably across multiple geographically disparate storage nodes, particularly in detecting and managing the need for data replication and prioritizing maintenance processes.
Innovation Solution
A method and device for monitoring conditions that require data replication between nodes, initiating replication processes with priority flags, and managing requests in different queues based on priority, ensuring high-priority requests are addressed first, with mechanisms to handle congestions and maintain data consistency across nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data replication is performed across multiple geographically dispersed storage nodes, then data reliability and robustness are improved, but system complexity and maintenance difficulty increase
Solution Approach 1:
Each storage node autonomously monitors system conditions and initiates replication processes without requiring centralized control. The nodes self-manage their replication needs by detecting conditions implying data maintenance requirements and executing replication decisions independently, thereby reducing overall system complexity while maintaining high data reliability across distributed nodes
2Reliability
If multiple replication processes are initiated simultaneously, then data consistency is improved, but processing time and resource consumption increase
Solution Approach 1:
The replication management process is segmented into priority levels with different queues handling replication requests of varying importance. High-priority replication processes are separated from low-priority ones, allowing the system to process critical consistency maintenance tasks immediately while deferring less urgent replication operations, thus reducing overall processing time while ensuring data consistency
3Productivity
If priority-based request handling is implemented, then maintenance efficiency is improved, but queue management complexity increases
Solution Approach 1:
The request handling mechanism is segmented into multiple priority-level queues, where each queue manages a specific subset of replication requests based on their importance. This segmentation allows the system to efficiently process high-priority maintenance tasks while managing lower-priority requests separately, improving overall maintenance efficiency without requiring complex centralized queue management
Solution Approach 2:
Storage nodes autonomously manage their own request queues and priority handling without requiring complex centralized coordination. Each node independently processes replication requests according to local priority flags and queue conditions, simplifying the overall queue management architecture while maintaining high maintenance efficiency through distributed self-service operation
Data Source
AI summary
A method and device for maintaining data in a data storage system, comprising a plurality of data storage nodes, the method being employed in a storage node in the data storage system and comprising: monitoring and detecting, conditions in the data storage system that imply the need for replication of data between the nodes in the data storage system; initiating replication processes in case such a condition is detected, wherein the replication processes include sending multicast and unicast requests to other storage nodes, said requests including priority flags, receiving multicast and unicast requests from other storage nodes, wherein the received requests include priority flags, ordering the received requests in different queues depending on their priority flags, and dealing with requests in higher priority queues with higher frequency than requests in lower priority queues.