Geographically Distributed Erasure Coding for Risk-Aware Object Storage
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Solution Overview
Problem
Current digital object storage systems face challenges in efficiently managing and distributing data across geographically dispersed locations to ensure data integrity and availability while balancing cost and risk, particularly in the context of natural disasters and political instability.
Innovation Solution
A geographically distributed erasure coding system that uses multiple computer-readable storage memories and processors to implement an erasure coding policy, distributing object blocks based on current status parameters such as latency, availability, and risk metrics to ensure data redundancy and integrity across diverse locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in geographically distributed locations to protect against natural disasters and political instability, then data availability and resilience are improved, but system complexity and cost increase
Solution Approach 1:
The patent divides data into multiple object blocks and distributes them across geographically separated storage memories. This segmentation allows data to be stored in multiple locations simultaneously, improving availability and resilience against regional disasters while maintaining manageable system complexity through automated distribution algorithms.
Solution Approach 2:
The patent introduces an intermediary system that manages the distribution and reconstruction of data blocks across geographically distributed storage memories. This intermediary layer handles the complexity of geographic distribution, monitoring status parameters and coordinating data recovery, thereby improving reliability without directly increasing operational complexity for users.
2Productivity
If erasure coding is used to reduce data reconstruction time and overhead, then productivity is improved, but manufacturing precision requirements increase
Solution Approach 1:
The patent applies erasure coding to pre-process data into encoded object blocks before distribution. This preliminary encoding action enables faster reconstruction by having redundant data pieces prepared in advance across multiple storage memories, improving productivity while the automated coding system handles the precision requirements.
Solution Approach 2:
The patent changes the parameter of data representation by transforming original data into encoded erasure code blocks with specific redundancy properties. This parameter change enables faster reconstruction speeds while the system automatically manages the precision of distribution across geographically dispersed storage memories based on status parameters.
3Reliability
If traditional RAID storage is replaced with erasure coding, then data protection efficiency is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic erasure coding that adapts to the status of storage memories and network conditions. Unlike static RAID configurations, the system dynamically adjusts data distribution and reconstruction strategies based on real-time parameters, improving data protection efficiency while managing complexity through adaptive algorithms.
Solution Approach 2:
The patent changes from fixed RAID parameters to dynamic erasure coding parameters that adjust based on storage memory status, geographic distribution, and reconstruction needs. This parameter flexibility improves data protection efficiency by optimizing redundancy placement while the automated system manages the increased complexity.
Data Source
AI summary
A geographically distributed erasure coding system includes multiple computer readable, non-transitory storage memories capable of storing a digital dataset including multiple object blocks, where each storage memory is configured to store one or more of the object blocks of the dataset according to an erasure coding policy. The system includes one or more processors configured to implement the erasure coding policy by distributing the multiple object blocks of the dataset to the multiple storage memories according to distribution criteria of the erasure coding policy, and the distribution criteria include at least one status parameter associated with each storage memory. The multiple storage memories are geographically distributed at different locations from one another.