Data Archival System Using Classification Model for Network Load Reduction
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Solution Overview
Problem
Current data archiving methods lack an efficient strategy for managing data elements based on their characteristics, such as type, format, and usage patterns, leading to suboptimal archival processes and potential disruptions in network environments.
Innovation Solution
A system utilizing a data detection and classification model that identifies data types, determines appropriate archival actions, and continuously monitors network usage to optimize data archival, ensuring that archival actions meet security and retention requirements while minimizing network load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data archiving is performed without classification and optimization, then archiving process is simple, but archival efficiency and data management quality deteriorate
Solution Approach 1:
The system performs preliminary classification of data elements into different data types before archiving. The classification model analyzes data characteristics and assigns appropriate data types, enabling subsequent archival actions to be optimized based on this pre-established classification. This preliminary categorization improves archival efficiency without requiring complex real-time decision-making during the archiving process itself.
Solution Approach 2:
The patent introduces a classification model as an intermediary component between data ingestion and archiving. This model acts as a mediator that processes raw data elements, determines their types based on various characteristics, and guides the archival process. By inserting this intermediary layer, the system achieves optimized archival efficiency while maintaining manageable complexity through modular architecture.
2Reliability
If archival actions are customized based on data characteristics, then archival quality and data security improve, but processing time and computational resources increase
Solution Approach 1:
The system performs data classification and determines archival requirements in advance, before the actual archiving operation. By pre-analyzing data characteristics and assigning data types, the system establishes the archival strategy beforehand, reducing the computational burden during the time-critical archiving execution phase while maintaining high data security through customized archival actions.
Solution Approach 2:
The classification model analyzes multiple parameters of data elements (format, structure, sensitivity, volume) and transforms these raw characteristics into standardized data type classifications. This parameter transformation enables the system to make complex security and archival decisions based on simplified classification results, improving data security without proportionally increasing processing time.
3Speed
If data elements are archived without considering usage patterns, then archiving process is faster, but network disruptions and data accessibility issues increase
Solution Approach 1:
The system performs preliminary analysis of data usage patterns and accessibility requirements before initiating archiving. By pre-assessing how frequently data elements are accessed and by whom, the system can plan archival timing and destination selection in advance, avoiding rushed archival operations that might disrupt network stability while maintaining efficient archival speed through pre-coordinated actions.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors data usage patterns and accessibility requirements. This feedback information is fed back into the classification model and archival decision-making process, enabling the system to adjust archival timing and strategies dynamically. This ensures archival operations proceed at optimal speeds while maintaining network stability through usage-aware scheduling.
Data Source
AI summary
Systems, computer program products, and methods are described herein for optimized data archival using data detection and classification model. The present invention is configured to receive information associated with a first data element within a distributed network environment; determine a first data type associated with the first data element; determine one or more archival actions associated with the first data element; determine one or more archival requirements associated with the first data element; determine one or more utilization parameters associated with the first data element; initiate an execution of the one or more archiving actions on the first data element; determine that the one or more archival actions meet the one or more archival requirements associated with the first data element; and execute the one or more archiving actions based on at least determining that the one or more archival actions meet the one or more archival requirements.