Distributed Storage Node Selection via Probability Factors
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Solution Overview
Problem
Existing distributed data storage systems face challenges in achieving robust and reliable data writing while maintaining system integrity, particularly during intensive operations and node malfunctions.
Innovation Solution
A method involving a server that sends a multicast storage query to multiple storage nodes, selects nodes based on an algorithmic probability factor, and randomly selects storage nodes for data writing, ensuring geographic diversity and reducing the risk of overloading high-ranked nodes, thereby facilitating quicker replication and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If storage nodes are selected based on high rank for data writing, then writing reliability is improved, but storage nodes become overloaded during intensive operations
Solution Approach 1:
The patent changes the selection parameter from static rank-based selection to dynamic probability-based selection. Storage nodes are selected based on a probability factor that considers both their rank and current load status, allowing the system to adapt to changing conditions and avoid overloading high-ranked nodes during intensive operations
Solution Approach 2:
The selection process transitions from a static ranking system to a dynamic probabilistic system. The probability factor is recalculated based on current system state, enabling flexible adaptation to varying load conditions while maintaining reliability through intelligent node selection
2Device complexity
If data is concentrated on fewer storage nodes, then maintenance complexity is reduced, but replication time increases when nodes malfunction
Solution Approach 1:
The system proactively distributes data to multiple storage nodes before failures occur. By using probability-based selection to spread data across multiple nodes in advance, the system ensures that replication can be quickly performed from multiple sources if any node malfunctions, rather than concentrating data on fewer nodes
3Reliability
If storage nodes are geographically distributed, then system redundancy is improved, but data spreading efficiency decreases
Solution Approach 1:
The patent introduces a probability factor that combines geographic distribution requirements with efficiency considerations. Instead of purely random or strictly geographic selection, the system calculates probability factors that balance both redundancy and efficiency, allowing flexible adaptation to different operational requirements
Data Source
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AI summary
The present invention relates to a distributed data storage system comprising a plurality of storage nodes. Using unicast and multicast transmission, a server application may write data in the storage system. When writing data, at least two storage nodes are selected based in part on a randomized function, which ensures that data is sufficiently spread to provide efficient and reliable replication of data in case a storage node malfunctions.