Cloud Storage Analysis System for Modality-Based Resource Management
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Solution Overview
Problem
Current electronic storage systems face challenges in efficiently managing and analyzing the impact of diverse data files on storage resources, particularly in terms of resource consumption and cost, especially in cloud environments, where accurate tracking and management are complex and resource-intensive.
Innovation Solution
The system performs an analysis of data files based on their modality type, examining resource consumption and cost, and presents the results in a user-friendly interface, allowing for efficient storage management, cost analysis, and secure, pay-per-use capacity options, with data files being stored in a cloud environment and forwarded between local and remote locations according to predetermined metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data files are stored in a cloud environment for centralized management, then storage capacity and accessibility are improved, but tracking and managing the impact on storage resources becomes more complex and resource-intensive
Solution Approach 1:
The patent introduces an intermediary analysis system that sits between the cloud storage environment and the data files. This intermediary performs automated analysis of data files to determine their impact on storage resources, acting as a mediator that simplifies the tracking and management process without requiring direct manual intervention in the complex cloud storage infrastructure.
Solution Approach 2:
The system enables self-service by automatically analyzing data files and generating reports about storage impact without requiring manual intervention. The analysis process autonomously examines data characteristics, calculates storage requirements, and presents findings through user interfaces, allowing the system to manage itself partially without constant human involvement.
2Measurement precision
If comprehensive analysis of data files is performed to examine storage impact, then storage management accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by analyzing data file characteristics and estimating storage impact before files are actually stored in the cloud environment. This allows the system to determine storage requirements and resource implications in advance, reducing the need for time-consuming post-storage analysis and enabling better resource allocation decisions beforehand.
Solution Approach 2:
The system performs partial analysis by focusing on the most critical data characteristics and storage impact factors rather than analyzing every possible attribute of every data file. This selective analysis approach maintains sufficient measurement precision for storage management decisions while significantly reducing processing time and computational resource requirements.
3Loss of energy
If storage resources are allocated based on actual usage patterns, then cost efficiency is improved, but monitoring and analysis requirements increase
Solution Approach 1:
The patent implements feedback mechanisms where the analysis system continuously monitors data file characteristics and storage usage patterns, then provides feedback reports that inform storage resource allocation decisions. This feedback loop enables cost-efficient resource allocation by adjusting storage capacity based on actual usage while maintaining manageable monitoring complexity through automated analysis and reporting.
Data Source
AI summary
Systems and methods for extent reference count updates are presented. In one embodiment; a reference count update method includes: receiving a plurality of data files associated with various modalities; performing an analysis on the data files including examining an impact of the plurality of data files on storage based upon a type of the modality; and forwarding resulting analysis information for presentation in a convenient user interface, including an indication of the impact of the plurality of data files on the storage based upon the type of the modality. In one embodiment the analysis includes resource consumption analysis of the storage associated with the type of modality. The analysis can include a cost analysis of the storage associated with the type of modality. The storage can be included in a cloud environment.