Garbage Collection Verification Using Perfect Hash Vector
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Solution Overview
Problem
Data storage systems face inefficiencies in verifying stored data and removing unnecessary data in deduplicated, containerized environments, where real-time deletion is computationally expensive and data corruption can lead to incorrect loss detection.
Innovation Solution
Implementing a method that uses a perfect hash vector to track and verify segments, allowing for intermittent garbage collection and file verification, while managing special segments that may appear lost due to their status, thereby ensuring accurate data removal and resource efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time deletion is performed in deduplicated storage systems, then data integrity is maintained, but computational cost increases significantly
Solution Approach 1:
The patent implements periodic garbage collection operations instead of real-time deletion. The system performs verification and deletion operations at scheduled intervals using background threads, allowing the storage system to accumulate verification tasks and process them periodically rather than immediately upon detecting potential data loss. This reduces peak computational load while maintaining data integrity over time.
Solution Approach 2:
The system performs preliminary verification by tracking special segments and maintaining verification queues before actual deletion occurs. By pre-identifying segments that need verification and preparing deletion candidates in advance, the system can efficiently process garbage collection operations during periodic execution without requiring intensive real-time computation when data loss is detected.
2Reliability
If frequent verification is performed to ensure data integrity, then data loss is detected accurately, but system performance decreases
Solution Approach 1:
The verification process is segmented into independent background threads that operate separately from the main data processing operations. The system divides verification tasks into manageable units (verification queues with individual segments) that can be processed concurrently without blocking primary storage operations. This segmentation allows verification to proceed with high accuracy while minimizing impact on overall system performance.
Solution Approach 2:
The verification system operates autonomously through background threads that self-manage the verification process. These threads independently retrieve segments from storage, verify their integrity using checksums, and update verification status without requiring intervention from the main processing system. This self-service approach enables continuous verification with minimal performance overhead.
3Measurement precision
If special segments are tracked during garbage collection, then false data loss detection is prevented, but system complexity increases
Solution Approach 1:
The patent introduces a special segment tracking mechanism that acts as an intermediary between the garbage collection process and the verification system. Special segments are identified and tracked separately, and their status is used to adjust verification outcomes. This intermediary layer prevents false positive data loss detections caused by segments currently being processed during garbage collection, improving measurement precision without requiring fundamental changes to the core verification logic.
Data Source
AI summary
Methods and systems for managing data in a distributed system are disclosed. The distributed system may include devices used by users (e.g., clients) and devices in which data is stored for future accessibility (e.g., storage providers). A data storage system may manage the data for the clients. To manage the data efficiently, the data storage system may perform an integrated process of both verifying that segments of files believed to be stored are actually stored and segments of files that no longer need to be stored are removed. The process may not be performed in real-time as files that no longer need to be stored are identified (e.g., as deletion requests are received). Rather, the integrated process may employ a garbage collection process where deletion conditions for segments are checked intermittently over time, and files are verified.