Cache Memory Hash Lookup for Redundant Data Elimination
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Solution Overview
Problem
Current storage systems face inefficiencies in managing redundant data storage, particularly in single-instance storage systems where identical data portions are stored multiple times, leading to reduced storage efficiency and increased operational costs.
Innovation Solution
Implementing a method within a cache memory system that uses a lookup table to identify and store only unique data portions by generating mathematical hashes, allowing for the comparison and association of newly-received data with previously written data, thereby discarding redundant copies and maintaining a single instance of each data portion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional storage systems store all received data portions without checking for duplicates, then the storage process is simple and fast, but storage efficiency deteriorates due to redundant data occupying cache memory space
Solution Approach 1:
The system performs preliminary hashing of data portions before storage and maintains a lookup table of existing data hashes. When new data arrives, its hash is compared against the lookup table to detect duplicates before actual storage occurs, preventing redundant data from occupying cache memory space
Solution Approach 2:
A mathematical hash function serves as an intermediary mechanism to represent data portions in a compact form. Instead of storing and comparing entire data portions directly, the system stores and compares their hash values, which are much smaller and faster to process, thereby improving storage efficiency while managing complexity
2Productivity
If the system compares newly-received data with all previously stored data to eliminate duplicates, then storage efficiency improves, but the time and computational resources required increase significantly
Solution Approach 1:
The system extracts the essential identifying characteristic of each data portion (its mathematical hash) and stores only this extracted feature in the lookup table. This allows rapid comparison of new data against existing data without comparing the entire data contents, significantly reducing processing time while maintaining storage efficiency
Solution Approach 2:
The system transforms the data representation from full data portions to compact hash values. This parameter change from storing complete data to storing hash digests reduces the computational burden of duplicate detection from O(n) to O(1) average time complexity, eliminating the time loss associated with exhaustive data comparison
3Speed
If redundant data portions are stored multiple times in the cache memory system, then the system can provide faster access to frequently accessed data, but storage capacity is wasted and operational costs increase
Solution Approach 1:
Instead of creating physical copies of redundant data portions in the cache memory, the system creates logical references through the lookup table. When duplicate data is detected via hash comparison, the system discards the redundant copy and stores only a single instance in the cache, maximizing storage capacity utilization while maintaining fast access to unique data
Data Source
AI summary
A method and computer program product for receiving a newly-received data portion for storing within a cache memory system. A determination is made concerning whether the newly-received data portion corresponds with at least one data portion previously written to and currently resident on the cache memory system. If the newly-received data portion does not correspond with at least one previously-written and currently resident data portion, the newly-received data portion is written to the cache memory system.