Virtual Block Addressing Map for Distributed Storage Scaling

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Solution Overview

Problem

Conventional enterprise data storage solutions require substantial and expensive dedicated resources for tracking and mapping data locations, leading to increased complexity and disruption, and often fail to scale dynamically with demand.

Innovation Solution

A computing resource provider offers scalable computing resources through services like Web services, utilizing a data mapping engine with a logical block addressing map, a placement engine, and a map authority to manage data access and storage across multiple nodes, ensuring data integrity and availability by replicating data and optimizing storage configurations based on demand and system performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If dedicated resources are invested for tracking and mapping data locations in conventional storage solutions, then data management reliability is improved, but device complexity and cost increase

Engineering Contradiction:
Improvedata management reliabilityVSAvoiddevice complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent uses a virtual block addressing map that copies and abstracts the physical storage location information, allowing the system to track data locations without requiring complex dedicated hardware resources. The virtualization layer creates a simplified representation of storage locations that can be managed through software rather than expensive dedicated infrastructure.

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The patent introduces a virtualization layer as an intermediary between the storage system and the data management layer. This virtual block addressing map acts as a mediator that translates complex physical storage locations into simplified virtual addresses, reducing the need for direct complex tracking mechanisms while maintaining reliable data management.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Measurement precision

If additional computing resources are added for tracking data locations, then data mapping capability is improved, but loss of time and productivity increase

Engineering Contradiction:
Improvedata mapping capabilityVSAvoidloss of time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system performs self-service by automatically managing the virtual block addressing map and data location tracking without requiring manual intervention or additional dedicated computing resources. The virtualization layer automatically handles mapping operations, reducing time loss and improving productivity while maintaining precise data mapping capabilities.

Inventive Principle:
Principle #25Self-service

3Quantity of substance

If conventional storage solutions are implemented, then data storage capability is provided, but adaptability to demand changes is reduced

Engineering Contradiction:
Improvedata storage capabilityVSAvoidadaptability to demand changes
Core Design Contradiction:
Quantity of substanceVSAdaptability or versatility

Solution Approach 1:

The patent implements a dynamic virtual block addressing map that can automatically adapt to changing storage demands. The virtualization layer enables flexible allocation and reallocation of storage resources based on actual needs, allowing the system to scale and adjust without being constrained by fixed physical infrastructure, thereby improving adaptability while maintaining data storage capability.

Inventive Principle:
Principle #15Dynamics

Data Source

PatentUS11314444B1Environment-sensitive distributed data management
Publication Date: 2022.04.26 AMAZON TECH INC
  • US11314444B1 patent drawing
  • US11314444B1 patent drawing
  • US11314444B1 patent drawing

AI summary

A storage controller is implemented for controlling a storage system. The storage controller may be implemented using a distributed computer system and may include components for servicing client data requests based on the characteristics of the distributed computer system, the client, or the data requests. The storage controller is scalable independently of the storage system it controls. All components of the storage controller, as well as the client, may be virtual or hardware-based instances of a distributed computer system.