Balance Tree Node Management in Data Processing Systems
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Solution Overview
Problem
Current data processing systems face inefficiencies in managing index data using balance tree structures, particularly in optimizing storage and addressing within semiconductor memory devices, leading to suboptimal use of storage space and operational complexity.
Innovation Solution
A data processing system employing a balance tree structure where nodes are managed based on predetermined sizes, with a memory system that separates and stores data in new and rest nodes differently, using physical storage areas efficiently by mapping physical addresses to logical addresses based on node information, including ID and indication flags, to optimize storage and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data from two different new nodes are gathered and stored in one physical storage area, then storage space utilization is improved, but device complexity increases due to address mapping requirements
Solution Approach 1:
The patent segments physical storage areas into different types (first type for new nodes, second type for rest nodes) and applies different mapping strategies to each segment. This segmentation allows efficient packing of new node data while simplifying the mapping logic for rest nodes, resolving the contradiction between storage utilization and mapping complexity.
Solution Approach 2:
Different mapping approaches are applied to different types of nodes based on their characteristics. New nodes use a mapping strategy that gathers data from multiple nodes into one physical area, while rest nodes use a simpler one-to-one mapping. This local differentiation optimizes storage utilization where needed without unnecessarily complicating the entire system.
2Speed
If physical addresses are mapped to logical addresses based on node information, then data retrieval efficiency is improved, but device complexity increases due to additional mapping operations
Solution Approach 1:
The address mapping process is segmented into two distinct paths: one for new nodes that utilizes the gathering strategy, and one for rest nodes that uses direct mapping. This segmentation enables fast retrieval for both cases while keeping the mapping logic manageable by treating different node types differently.
Solution Approach 2:
The patent introduces an intermediary mapping layer that translates logical addresses to physical addresses based on node type. This intermediary layer abstracts the complexity of data gathering and physical storage organization, providing fast retrieval through efficient address translation without exposing the underlying complexity to the host system.
3Stability of the object's composition
If nodes are managed with predetermined sizes in balance tree structure, then storage organization is improved, but loss of time occurs due to fixed size constraints
Solution Approach 1:
While maintaining predetermined node sizes for structural stability, the patent dynamically adjusts the mapping strategy based on whether nodes are new or rest nodes. This dynamic approach allows the system to optimize data access patterns without changing the fundamental fixed-size node structure, thereby maintaining organizational stability while reducing access time penalties.
Data Source
AI summary
A data processing system may include: a host suitable for managing a plurality of data through a balance tree structure in which each node is set to a predetermined size, wherein each of the data includes information regarding the node in which the data is positioned, as node information; and a memory system having a plurality of physical storage areas each corresponding to the predetermined size, and suitable for gathering data included in two different new nodes based on the node information included in each of the data applied from the host, and storing the gathered data in one of the plurality of physical storage area.