Storage Metadata Name Encoding with Prefix-Midsection-Suffix Tables
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Solution Overview
Problem
As storage clusters grow in capacity, managing metadata efficiently becomes a challenge due to inefficient allocation of memory for storage, particularly when address spaces are not fully occupied, leading to wasteful use of memory space by long metadata names.
Innovation Solution
A method for efficient name coding in storage systems is implemented by identifying common prefixes, midsections, and suffixes of strings, encoding their positions in a string table, and writing these encodings to memory, allowing for compact representation of strings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If memory is allocated for all possible combinations in the address space, then the address space is fully covered, but memory space is wasted when the address space is not fully occupied
Solution Approach 1:
The patent segments the address space into occupied and unoccupied regions, allocating memory only for the occupied segments. This is achieved by tracking actual object placements and allocating memory dynamically based on real usage patterns rather than pre-allocating for the entire address space, thereby eliminating memory waste while maintaining complete coverage of occupied address space.
2Loss of information
If long names are stored in metadata, then complete information is preserved, but storage space consumption increases
Solution Approach 1:
The patent creates compact copies of object names using encoding schemes that represent full names with shorter bit patterns. Instead of storing complete long names in metadata, the system generates encoded representations that capture the essential identifying information while occupying significantly less storage space, thus preserving information completeness while reducing storage consumption.
Solution Approach 2:
The patent transforms the representation parameter of object names from full-string format to encoded bit-pattern format. By changing the parameter representation from human-readable long names to compact binary encodings, the system maintains the ability to uniquely identify objects while dramatically reducing the storage space required for metadata.
3Adaptability or versatility
If memory is allocated for maximum capacity, then future growth is accommodated, but available memory space is consumed by allocated but sparsely occupied data structures
Solution Approach 1:
The patent implements dynamic memory allocation that adapts to actual storage usage patterns. Instead of static pre-allocation for maximum capacity, the system dynamically adjusts memory allocation based on real-time occupancy, allowing future growth while avoiding waste from pre-allocated but unused space. This dynamic approach maintains scalability while improving memory utilization efficiency.
Data Source
AI summary
A method for efficient name coding in a storage system is provided. The method includes identifying common prefixes, common suffixes, and midsections of a plurality of strings in the storage system, and writing the common prefixes, midsections and common suffixes to a string table in the storage system. The method includes encoding each string of the plurality of strings as to position in the string table of prefix, midsection and suffix of the string, and writing the encoding of each string to memory in the storage system for the plurality of strings, in the storage system.