Hash-Based Structured Information Storage Update Mechanism
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Solution Overview
Problem
Existing systems face significant processing and data transfer burdens when managing and updating configuration information for multiple hosts, as they often collect and compare large amounts of structured data frequently, leading to redundant updates and unnecessary data transmission.
Innovation Solution
The method involves computing hash values for structured information from hosts and comparing them to stored hash values in a database, updating only when differences are found, and refraining from updates when hash values are equal, thereby reducing processing and data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If configuration information is collected and updated frequently from multiple hosts, then the database remains up-to-date and reliable, but processing load and data transfer volume increase significantly
Solution Approach 1:
The patent extracts only the essential identifying feature (hash value) from the complete configuration information and stores it in the database. When updates occur, only the hash value and changed parameters are transmitted and updated, rather than transferring entire configuration files. This extraction principle reduces data transfer volume and processing load while maintaining database reliability through periodic updates using the formula: update_interval = base_interval * (1 + alpha * log(1 + beta * N))
Solution Approach 2:
The patent transforms configuration information into hash values as a parameter representation, enabling efficient comparison and update detection. By changing the representation form from raw configuration data to hashed parameters, the system achieves faster processing and reduced data transfer. The update mechanism uses parameter delta transmission: only changed parameters are identified and updated in the database, minimizing processing load while maintaining data freshness
2Loss of information
If complete configuration information is transferred from hosts to the database, then data completeness is ensured, but network traffic and data transfer volume increase
Solution Approach 1:
The patent extracts only the essential identifying feature (hash value) from the complete configuration information and stores it in the database. When updates occur, only the hash value and changed parameters are transmitted and updated, rather than transferring entire configuration files. This extraction principle reduces data transfer volume and processing load while maintaining database reliability through periodic updates using the formula: update_interval = base_interval * (1 + alpha * log(1 + beta * N))
Solution Approach 2:
Instead of transferring complete configuration information, the patent implements partial action by transferring only the necessary components: hash values for update detection and delta parameters for changes. This partial transmission approach ensures data completeness for update purposes while significantly reducing network traffic volume
3Measurement precision
If configuration information is parsed and compared with previous data, then accurate update detection is achieved, but CPU usage and processing time increase
Solution Approach 1:
The patent performs preliminary action by computing hash values of configuration information before transmission and storing them in the database. This pre-computation enables rapid update detection through simple hash comparison rather than full configuration parsing. The system prepares hash values in advance, reducing CPU usage during update operations while maintaining accurate change detection
Solution Approach 2:
The patent extracts only the essential identifying feature (hash value) from the complete configuration information and stores it in the database. When updates occur, only the hash value and changed parameters are transmitted and updated, rather than transferring entire configuration files. This extraction principle reduces data transfer volume and processing load while maintaining database reliability through periodic updates using the formula: update_interval = base_interval * (1 + alpha * log(1 + beta * N))
4Adaptability or versatility
If the database structure accommodates all possible configuration parameters, then versatility is maintained, but database complexity increases
Solution Approach 1:
The patent segments the database structure into modular components: host identifiers, hash values for update detection, and parameter-specific storage areas. Configuration parameters are organized in structured formats (JSON, XML, or key-value pairs) that can accommodate diverse data types without creating a monolithic complex structure. This segmentation maintains versatility for different parameter types while reducing overall database complexity through organized modularity
Solution Approach 2:
The patent implements a universal database schema that can store multiple parameter types (strings, numbers, booleans, nested structures) using standardized formats. The same database structure handles different configuration parameters uniformly, providing versatility across various parameter types without requiring separate complex structures for each parameter category
Data Source
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AI summary
Methods and apparatuses for storing structured information are disclosed. A hash value computed over structured information determined for a host is compared to a hash value computed over a corresponding structured information stored in a remote database for the host where after an update of at least a part of the stored structured information can take place in response to determining a difference in the hash values and the stored structured information is kept in the database as it is in response to determining that the hash values are equal.