Data Thread Storage Scheduling for Attribute Consistency

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Solution Overview

Problem

Existing data storage systems often lose data attributes when data is moved between storage management devices, as these attributes are typically separated from the data and not consistently managed across different storage mechanisms.

Innovation Solution

The concept of data threads is introduced, where each data unit is associated with a data thread that includes attributes and their durations, allowing for the scheduling of actions based on these attributes across multiple storage engines, ensuring that attributes remain linked to the data and can be managed effectively during data movement and storage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data attributes are stored as metadata separate from actual data in a file system, then data availability and reliability are improved, but attributes may be lost when data is moved between storage management devices

Engineering Contradiction:

Improvedata reliabilityVSAvoidattribute loss

Core Design Contradiction:

ReliabilityVSLoss of information

Solution Approach 1:

The patent merges data attributes with the data itself by storing attributes as part of the data structure rather than as separate metadata. This is achieved by incorporating attribute information directly into the data units, ensuring that attributes travel with the data when it is moved between storage management devices, thereby preventing attribute loss while maintaining reliability

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces a data thread as an intermediary structure that links data units with their attributes. The data thread acts as a mediator that carries both data and associated attributes together through the storage system, ensuring that attributes are preserved during data movement between different storage management devices

Inventive Principle:

Principle #24Intermediary (Mediator)

2Device complexity

If data is conceptualized and stored as files or blocks with separate metadata, then storage management and reliability schemes are simplified, but fine-grained attribute management and service level agreements become difficult

Engineering Contradiction:

Improvestorage management complexityVSAvoidattribute management flexibility

Core Design Contradiction:

Device complexityVSAdaptability or versatility

Solution Approach 1:

The patent segments the data management approach by introducing data threads as individual manageable units that can be independently scheduled and managed. Each data thread represents a discrete data unit with its own attributes, enabling fine-grained control and flexible service level agreements while maintaining a relatively simple overall storage management architecture

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces dynamic attribute management through the data thread structure, which allows attributes to be assigned, modified, and managed dynamically as data moves through the storage system. This dynamic approach enables flexible service level agreements and adaptive attribute management without significantly increasing storage management complexity

Inventive Principle:

Principle #15Dynamics

3Adaptability or versatility

If multiple storage engines are used to store data units, then storage capacity and flexibility are improved, but scheduling and coordinating actions across storage engines becomes complex

Engineering Contradiction:

Improvestorage flexibilityVSAvoidscheduling complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces a data thread as an intermediary structure that simplifies scheduling across multiple storage engines. The data thread carries all necessary attribute information and scheduling information, allowing the scheduling system to make decisions based on complete data about the data unit and its requirements, thereby reducing scheduling complexity while maintaining storage flexibility

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent creates a universal data thread structure that can be used across multiple storage engines and for multiple types of actions (storage, retrieval, migration, etc.). This universal structure simplifies the scheduling system by providing a consistent interface and data structure for managing diverse storage operations across different storage engines

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS7617497B1Method and system for creating and using storage threads

Publication Date: 2009.11.10 ORACLE AMERICAN INC

AI summary

A system including a plurality of data units, wherein each of the plurality of data units is associated with a data thread, a plurality of storage engines configured to store the plurality of data units, and a data scheduler configured to schedule an action to perform on the plurality of data units using the data thread associated with each of the plurality of data units, wherein the data thread includes a data thread duration and a plurality of tuples, and wherein each of the plurality of tuples includes an attribute and an attribute duration.