Storage Server Data Backhaul for Cloud Transmission Exceptions
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Solution Overview
Problem
Cloud storage systems face issues with incomplete data storage and unreliable data integrity due to exceptional data transmission status between data acquisition devices and storage servers, leading to potential data loss and incomplete data sets.
Innovation Solution
A method where the storage server monitors data transmission status, generates data exception information, and initiates data backhaul requests to acquire missing data within exception time periods, ensuring complete data storage and integrity through comparison with storage records and tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data transmission is performed from data acquisition device to storage server, then data storage capacity is improved, but data reliability deteriorates due to exceptional transmission status
Solution Approach 1:
The storage server proactively monitors data transmission status and detects exceptions before they result in permanent data loss. By identifying transmission failures in advance and initiating backhaul requests to retrieve missing data, the system prevents reliability deterioration while maintaining storage capacity expansion.
Solution Approach 2:
The system implements a feedback mechanism where the storage server continuously monitors transmission status, compares stored data with expected data ranges, and triggers corrective backhaul operations when exceptions are detected. This closed-loop feedback ensures data reliability is maintained despite transmission issues during capacity expansion.
2Reliability
If data backhaul request is initiated to acquire missing data, then data integrity is improved, but system complexity increases
Solution Approach 1:
The storage server autonomously monitors its own data integrity, detects transmission exceptions, and initiates backhaul requests without external intervention. This self-service approach maintains data integrity while avoiding the complexity of additional monitoring systems or manual intervention protocols.
Solution Approach 2:
The system discards incomplete or corrupted data received during transmission exceptions and recovers the missing data through backhaul requests. This selective discarding and recovering mechanism ensures data integrity while keeping the complexity management focused only on exceptional cases rather than processing all data uniformly.
3Reliability
If transmission exception is detected and data backhaul is performed, then data completeness is improved, but time consumption increases
Solution Approach 1:
The system skips the time-consuming process of checking every transmitted data packet by instead monitoring transmission status exceptions and only initiating backhaul operations when failures are detected. This selective approach maintains data completeness while minimizing time consumption by avoiding unnecessary verification of successfully transmitted data.
Solution Approach 2:
The storage server performs preliminary monitoring of transmission status to detect exceptions before they result in permanent data loss. By identifying issues early and immediately initiating backhaul requests, the system minimizes the time data remains incomplete while ensuring eventual data completeness.
4Reliability
If storage server monitors data transmission status continuously, then data reliability is improved, but energy consumption increases
Solution Approach 1:
The storage server performs periodic monitoring of data transmission status at strategically chosen intervals rather than continuous monitoring. This periodic approach maintains data reliability by detecting transmission exceptions while significantly reducing energy consumption compared to uninterrupted monitoring.
Solution Approach 2:
The storage server autonomously monitors transmission status and only activates energy-intensive backhaul operations when exceptions are detected. This self-service mechanism maintains data reliability while minimizing energy consumption by keeping the monitoring system in a low-power state during normal operation and activating full processing only when necessary.
Data Source
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AI summary
The present disclosure provides a data storage method, a storage server, and a storage medium and system, belonging to the field of data processing. The method is applied to a storage server in a cloud storage system. The method includes: monitoring data transmission status of a data acquisition device; obtaining data exception information according to the monitored data transmission exceptional status; transmitting a first data backhaul request to the data acquisition device, the data acquisition device being configured to return first data acquired within the exception time period upon receiving the first data backhaul request; and storing the first data upon receiving the first data. The present disclosure can punctually monitor an exception occurring in a process of transmitting data to the storage server by the data acquisition device, and store, in the storage server, the data acquired by the data acquisition device within an exception time period. In this way, the lost data is complemented by data backhaul, the integrity and reliability of the data are ensured, and excellent instantaneity is achieved.