Hierarchical Scale Unit Values for Distributed Data Storage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional data storage techniques in distributed systems are inflexible and provide inadequate protection against data loss, as they often cluster multiple instances within a single entity, making them vulnerable to failures and access issues when all instances are contained within a single IT infrastructure entity.
Innovation Solution
Implementing a hierarchical scale unit system where data instances are stored across nodes with assigned hierarchical scale unit values, allowing for the distribution of primary and secondary instances across multiple hierarchical scale units, thereby reducing the likelihood of data loss by separating them geographically and across different infrastructure levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple instances of data are stored in the same scale unit (machine, pod, or rack), then device complexity is reduced and ease of operation is improved, but reliability deteriorates because a single failure can affect all instances
Solution Approach 1:
The patent segments the scale unit assignment by introducing hierarchical levels (rack-level, pod-level, machine-level scale units) and assigning different scale unit values at each level. This allows data instances to be distributed across different hierarchical segments, ensuring that failures at one level do not affect all instances. Primary and secondary instances are assigned to different scale units based on hierarchical differences, providing fault isolation while maintaining manageable complexity through structured segmentation.
2Adaptability or versatility
If conventional scale unit assignment is used, then ease of operation is maintained with simple configuration, but adaptability deteriorates because it provides insufficient protection against data loss in distributed systems
Solution Approach 1:
The patent adds a hierarchical dimension to scale unit assignment by introducing multiple levels (rack-level, pod-level, machine-level) with different scale unit values. This dimensional expansion allows the system to adapt to distributed storage requirements while maintaining operational simplicity through automated hierarchical assignment. The multi-dimensional approach provides robust data loss protection by ensuring instances are distributed across hierarchical boundaries without requiring complex manual configuration.
3Reliability
If all instances of data are contained within a single IT infrastructure entity, then device complexity is minimized, but reliability deteriorates as data becomes inaccessible upon entity failure
Solution Approach 1:
The patent applies local quality by assigning different hierarchical scale unit characteristics to different storage locations. Each node's scale unit assignment is optimized for its specific hierarchical position (rack-level, pod-level, or machine-level), creating locally adapted storage configurations. This ensures that data instances are distributed with appropriate hierarchical separation to prevent single-point failures, while the localized assignment logic at each level keeps infrastructure complexity manageable through context-specific optimization.
Data Source
AI summary
Techniques are described herein for storing instances of data among nodes of a distributed store based on hierarchical scale unit values. Hierarchical scale unit values are assigned to the respective nodes of the distributed store. A first instance (e.g., a primary instance) of a data module is stored in a first node having a first hierarchical scale unit value. A primary instance of the data module with respect to a data operation is an instance of the data module at which the data operation with respect to the data module is initiated or initially directed. A second instance (e.g., a primary or secondary instance) of the data module is stored in a second node having a second hierarchical scale unit value based on a magnitude of a difference between the first hierarchical scale unit value and the second hierarchical scale unit value. A secondary instance is essentially a “back-up” instance.