Consolidating Garbage Collector for Data Storage Efficiency
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Solution Overview
Problem
Current cloud-based data storage systems face inefficiencies in garbage collection due to uneven deletion times of object data, leading to additional data copying cycles and reduced storage capacity reclamation efficiency.
Innovation Solution
A consolidating garbage collector identifies live object segments in underutilized chunks, moves them to new chunks, and unites adjacent segments, reducing data distribution and metadata, thereby minimizing unnecessary data copying and improving storage capacity reclamation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If copying garbage collection is implemented to reclaim storage space by copying data from underloaded chunks to new chunks, then storage capacity reclamation is achieved, but additional data copying cycles are required when copied data is deleted at different times, reducing efficiency
Solution Approach 1:
The patent merges multiple scattered segments of the same object that reside in different underloaded chunks into a single consolidated chunk. By identifying all segments belonging to the same object across multiple chunks and copying them together to a destination chunk, the system eliminates the need for separate copying operations for each segment, thereby reducing total copying cycles and improving reclamation efficiency.
2Productivity
If generational garbage collection is implemented to segregate user data by age into multiple areas, then garbage collection frequency is reduced for older objects, but objects with different remaining lifetimes still require separate copying cycles, maintaining inefficiency
Solution Approach 1:
The patent segments the garbage collection process by object identity rather than by age groups. Instead of maintaining multiple chunk areas based on object age, the system segments work by identifying all segments of a specific object across any chunks and consolidating them together. This object-centric segmentation approach simplifies the structure while maintaining efficient collection frequency.
3Quantity of substance
If data is scattered across multiple underloaded chunks, then storage capacity is utilized, but data coherence is reduced and additional copying cycles are needed
Solution Approach 1:
The patent merges scattered object segments from multiple underloaded chunks into a single destination chunk, thereby improving data coherence. By consolidating all segments of the same object into one location, the system maintains storage capacity utilization while eliminating the fragmentation that causes additional copying cycles.
Data Source
AI summary
The technology described herein is directed towards consolidating garbage collection of data stored in data structures such as chunks, to facilitate efficient garbage collection. Low capacity utilization chunks are detected as source chunks, and live data of an object (e.g., in segments) is copied from the source chunks to new destination chunk(s). A source chunk is deleted when it no longer contains live data. By copying the data on an object-determined basis, new chunks contain more coherent object data, which increases the possibility of future chunk deletion without data copying or with a reduced amount of copying. When data segments of an object are adjacent, the consolidating garbage collector may unite them into a united segment, which reduces an amount of system metadata per object. New chunks can be associated with a generation number (e.g., indicating the oldest previous generation) to further facilitate more efficient future chunk deletion.