Service-Oriented Data Management Layer for Granular Storage Control
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Solution Overview
Problem
Current data management systems are limited in scalability and flexibility, as they rely on block storage and are agnostic to data content, failing to provide granular management and consistent performance across diverse storage resources and applications.
Innovation Solution
A service-oriented distributed data management layer that manages data as objects or groups based on content and metadata, using feature-based policies to provide scalable and granular data management, allowing for dynamic and distributed processing across multiple locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If block storage is used with no reference to data content, then storage capacity can be expanded, but data management becomes coarse-grained and cannot provide granular control
Solution Approach 1:
The patent segments data into objects with associated metadata, allowing individual data elements to be managed independently. This enables granular control over specific data objects while maintaining large-scale storage capacity, resolving the contradiction between storage quantity and management granularity.
Solution Approach 2:
The system changes the parameter of data organization from content-agnostic blocks to content-aware objects with metadata. This parameter change enables both large-scale storage and fine-grained management by allowing the system to track and control individual data objects based on their content and attributes.
2Adaptability or versatility
If multiple storage resources from different vendors are unified under single governance, then adaptability and versatility improve, but system complexity increases
Solution Approach 1:
The patent creates a universal data management layer that can handle multiple storage resources from different vendors through a common object-based interface. This universal layer provides multi-functionality by supporting various storage types and protocols while maintaining consistent governance, thus improving adaptability without proportionally increasing complexity.
Solution Approach 2:
The system introduces an intermediary data management layer between the heterogeneous storage resources and the applications. This intermediary layer handles the complexity of unifying multiple vendors' storage systems, providing a simplified unified interface to applications while managing the underlying diversity, thereby improving versatility without exposing the full complexity to users.
3Reliability
If data is managed as objects with content and metadata awareness, then data lifecycle management and security improve, but processing overhead increases
Solution Approach 1:
The patent applies preliminary action by pre-defining policies for data lifecycle management based on object features and metadata. These policies are established in advance and automatically executed, improving reliability of data management while reducing processing overhead by avoiding ad-hoc decision-making during data operations.
Solution Approach 2:
The system implements self-service by enabling data objects to carry their own metadata and feature information that automatically guides their management. This self-service approach improves lifecycle management reliability by making data self-descriptive while reducing processing overhead by minimizing the need for external analysis and decision-making.
Data Source
AI summary
A method of managing data with high granularity, comprises identifying data objects and an associated data management policy. The policy uses features and a common semantic to define a feature-based sequence of data management actions of a data management operation that varies for different objects depending on respective features. Features of the data objects are obtained and then used to associate a data management action with the object using the policy so that the object is managed individually according to its own features, thus achieving high granularity of data management precision and also high flexibility.