Data Placement Engine for Storage Reliability
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Solution Overview
Problem
Modern data storage systems are susceptible to overheating and vibration-induced damage, leading to data corruption or loss, which existing technologies have not adequately addressed, resulting in additional costs for organizations and service providers.
Innovation Solution
Implementing a redundancy encoding algorithm and a placement engine that strategically places data fragments across multiple storage devices to minimize the risk of data loss, using rules to avoid failure modes such as overheating and vibration damage, and restricting access to storage devices during archival or retrieval processes to prevent fatigue and maintain system stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored in modern data storage systems with spinning magnetic media, then data storage capacity and accessibility are improved, but the system becomes susceptible to overheating and vibration-induced damage leading to data corruption or loss
Solution Approach 1:
The patent segments data into multiple fragments and stores them across different storage devices within the system. This segmentation ensures that if one storage device suffers from overheating or vibration damage, the data can still be recovered from other fragments stored on different devices, thereby maintaining data integrity while preserving storage capacity.
Solution Approach 2:
The patent implements beforehand cushioning by creating redundant data fragments and storing them in advance across multiple storage devices. This preparatory measure cushions against potential hardware failures caused by overheating or vibration, ensuring data can be recovered even if some storage devices fail, thus resolving the contradiction between storage capacity and data reliability.
2Reliability
If redundant storage of data is implemented to address data loss risks, then data durability is improved, but additional costs are incurred for organizations and service providers
Solution Approach 1:
The patent changes the parameter of data representation by encoding data into redundant fragments with specific mathematical relationships. This allows the system to achieve enhanced data durability through redundancy while optimizing storage resource utilization, as the redundant fragments can be efficiently managed and recovered without requiring excessive additional storage capacity.
3Productivity
If storage devices are actively used for data archival and retrieval, then data accessibility is improved, but the devices are subjected to fatigue damage and overheating
Solution Approach 1:
The patent applies dynamics by implementing load balancing and rotational allocation strategies where storage devices are dynamically assigned different roles (active, standby, maintenance) based on system conditions. This dynamic approach ensures data accessibility is maintained through multiple fragments while distributing wear and thermal load across devices, thereby extending their operational lifespan.
Data Source
AI summary
A data storage service receives a request to store data into a data storage system that consists of many physical data storage locations, each location having various physical characteristics. The data storage service determines a proper location for the data based on data placement rules applied to the physical data storage locations such that a set of proper locations is identified. The data storage service can place the data according to data placement rules.