Erasure Coded Linked Node Data Update Mechanism
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Solution Overview
Problem
Computing devices face data loss due to failure of persistent storage, and existing methods lack efficient solutions for managing and protecting data across nodes in distributed storage systems.
Innovation Solution
A method involving nodes that receive updated data chunks, identify associated parity chunks, transmit data and updated chunks to other nodes, and generate and store updated parity chunks, utilizing data protection domain information to manage and protect data through replication or erasure coding, allowing dynamic adjustment based on node state changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in persistent storage of computing devices, then data can be retained for later use, but data loss occurs when persistent storage fails
Solution Approach 1:
The patent divides data into multiple data chunks and distributes them across different nodes in a network. Each node stores only a portion of the total data, so that failure of one node does not result in complete data loss. This segmentation approach directly addresses the data loss problem by ensuring data redundancy across multiple storage locations.
Solution Approach 2:
The patent changes the storage parameter from single-location persistent storage to multi-location distributed storage across network nodes. By transforming the storage architecture from centralized to distributed, the system achieves improved reliability and protection against data loss while maintaining data accessibility.
2Reliability
If data chunks are transmitted to multiple nodes for redundancy, then data protection is improved, but network traffic and transmission overhead increase
Solution Approach 1:
The patent transmits only the necessary data chunks to the minimum number of nodes required to maintain data protection, rather than replicating data to all nodes. This partial action approach reduces network traffic and transmission overhead while still achieving the desired level of data protection through selective distribution of data chunks across the network.
Solution Approach 2:
The patent assigns different data chunks to different nodes based on local conditions and requirements. Each node receives and stores specific data chunks that are appropriate for its local context, which optimizes network utilization and reduces unnecessary transmission overhead while maintaining overall data protection.
3Reliability
If parity chunks are stored on separate nodes, then data integrity is improved, but system complexity increases
Solution Approach 1:
The patent combines the storage of data chunks and parity chunks into a unified distributed storage system. Instead of maintaining separate storage mechanisms for data and parity information, the system integrates both types of data chunks into the same networked node structure, simplifying the overall system architecture while maintaining data integrity through the distributed parity chunk approach.
4Reliability
If all nodes transmit data during updates, then data consistency is improved, but network traffic and processing time increase
Solution Approach 1:
The patent extracts and identifies only the specific nodes that hold parity chunks related to the data being updated. Instead of having all nodes participate in the update process, the system selectively involves only the necessary nodes, which reduces network traffic and processing time while maintaining data consistency through targeted updates of the identified parity chunk locations.
Data Source
AI summary
In general, embodiments of the invention relate to storing data and managing the stored data in linked nodes. Managing the data in the linked nodes includes updating erasure coded data in a manner that reduces the transmission of data chunks and parity chunks between the linked nodes.