Distributed Storage Server Managing File and Object Data
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Solution Overview
Problem
Existing storage systems, particularly file storage, face challenges in scalability and convenience for storing large files or large-capacity data, leading to potential time delays and errors during synchronization, as well as high costs, while object storage systems may experience single point failures and inefficiencies.
Innovation Solution
A distributed storage management system that employs a server with a deploying module to set up reverse proxies and partition magnetic regions, an obtaining module to manage file storage requirements, and a processing module to perform distributed processing, utilizing object storage units and distributed storage units to handle file and object storage needs, ensuring reliability and load balancing through a proxy device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If file storage systems are used, then data can be stored and accessed in organized directory structures, but the system is not easy to expand and is not convenient to store large numbers of files or large-capacity files
Solution Approach 1:
The system segments storage resources into multiple distributed storage nodes, each capable of independent operation. Files are divided into blocks and distributed across different nodes, enabling horizontal scaling without requiring system-wide reconfiguration. This allows the storage system to expand by simply adding more nodes while maintaining organized directory structures.
Solution Approach 2:
The system transitions from traditional single-dimension file storage to multi-dimensional distributed storage architecture. Data is organized not only by directory structures but also distributed across multiple dimensions including storage nodes, data blocks, and replication groups, enabling scalable expansion while preserving file organization capabilities.
2Reliability
If object storage systems are used, then large-capacity files can be stored, but there may be time delay or error during data synchronization and the cost is relatively high
Solution Approach 1:
The system implements local quality by caching frequently accessed data blocks in memory at each storage node, reducing the need for repeated disk I/O operations and network synchronization. This local caching mechanism minimizes synchronization time delays while maintaining data consistency across the distributed system.
Solution Approach 2:
The system performs preliminary actions by pre-replicating data blocks across multiple storage nodes before actual write operations complete. This proactive replication ensures that data is already available at multiple locations, reducing synchronization time and improving reliability without waiting for confirmation from all nodes.
3Adaptability or versatility
If object storage systems are used, then universal identification codes can package data and metadata together, but the cost is relatively high
Solution Approach 1:
The system implements multi-functionality by using the same distributed storage infrastructure to handle both file storage with directory structures and object storage with universal identification codes. This unified architecture eliminates the need for separate hardware systems for different storage paradigms, reducing overall hardware costs while maintaining storage flexibility.
Solution Approach 2:
The system merges file storage and object storage capabilities into a single distributed storage platform. By combining these storage models, the system achieves versatility in handling different data types and access patterns while utilizing shared hardware resources, thereby reducing redundant hardware costs.
4Reliability
If distributed storage is implemented across multiple servers, then scalability and reliability are improved, but system complexity increases
Solution Approach 1:
The system introduces a gateway as an intermediary layer between clients and distributed storage nodes. The gateway handles complex operations such as data block division, replication management, and node coordination, shielding clients from distributed system complexity while maintaining high reliability through coordinated operations across multiple servers.
Solution Approach 2:
Storage nodes implement self-service mechanisms by automatically managing their own data blocks, replication, and failover operations. Each node independently monitors its health and can take over failed nodes' responsibilities without manual intervention, reducing the operational complexity of managing distributed systems while improving reliability.
Data Source
AI summary
A method for managing distributed storage implemented in a server includes obtaining files to be stored from a user; performing processing for distribution on the files to be stored; determine a storage requirement of the files to be stored, wherein the storage requirement can comprise file storage and object storage; storing the distributed files into a plurality of storage areas through a distributed storage unit when the storage requirement of the files to be stored is determined to be the file storage; and storing the distributed files into the plurality of storage areas through a distributed storage unit and an object storage unit when the storage requirement of the files to be stored is determined to be the file storage.