Edge DR Data Segmentation for Storage Efficiency

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

The high volume of data generated by IoT devices, such as video surveillance cameras, poses a challenge in data protection and disaster recovery, as duplicating the data for redundancy significantly increases storage costs and capacity requirements.

Innovation Solution

The data is split into multiple streams, each stored at a different site, allowing for reduced storage capacity needs while still enabling recovery of full-resolution data if required, by storing lower resolution data at disaster recovery sites.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If full copies of data are created for disaster recovery, then data protection and reliability are improved, but storage capacity requirements and costs increase significantly

Engineering Contradiction:

Improvedata protectionVSAvoidstorage capacity

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent divides the full data copy into multiple lower-resolution data streams that are distributed across multiple disaster recovery sites. Instead of storing complete data replicas at each site, the system segments the data into N streams where each site stores only a portion, reducing individual site storage requirements while maintaining the ability to reconstruct full-resolution data through aggregation of the segmented streams.

Inventive Principle:

Principle #1Segmentation

2Reliability

If full copies of data are created for disaster recovery, then data protection is improved, but storage costs increase significantly

Engineering Contradiction:

Improvedata protectionVSAvoidstorage cost

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system segments data into multiple lower-resolution streams distributed across N disaster recovery sites, reducing the storage capacity required at each individual site. This segmentation approach maintains data protection capabilities while significantly reducing the total storage infrastructure cost compared to storing full copies at each site.

Inventive Principle:

Principle #1Segmentation

3Quantity of substance

If data is stored at lower resolution at disaster recovery sites, then storage capacity needs are reduced, but data quality and analysis resolution may be compromised

Engineering Contradiction:

Improvestorage capacityVSAvoiddata resolution

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent combines multiple lower-resolution data streams from different disaster recovery sites to reconstruct full-resolution data. Each site stores a segmented portion of the data at reduced resolution, but when data needs to be accessed, the system merges the segments from multiple sites to restore the complete high-resolution data set, thus maintaining data quality while reducing individual site storage requirements.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS11275506B2Storage-efficient DR for edge devices

Publication Date: 2022.03.15 EMC IP HLDG CO LLC

AI summary

One example method includes receiving multiple raw data streams, each of the raw data streams including data generated and/or collected by a respective IoT device, storing the data of the raw data streams, splitting the data of the raw data streams into ‘N’ storage data streams, and transmitting each of the storage data streams to a different respective storage node. In this example, one of the storage nodes is a production edge node that retains one of the storage data streams, and each of N−1 other storage nodes receives a respective one of the storage data streams.