Tree-Based Node Insertion Method for Memory Devices
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Solution Overview
Problem
Existing tree-based data structures face inefficiencies in node insertion, particularly when the tree shape is fixed, leading to exponential increases in the number of nodes to be transferred and significant time consumption.
Innovation Solution
The proposed method involves searching for the nearest node in a primary tree based on the key value of the node to be inserted, with the option to split nodes and reassign secondary trees to maintain tree balance, thereby reducing the height of the secondary tree and increasing insertion speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If new nodes are inserted into a tree with fixed shape, then the tree structure is maintained, but the number of nodes to be transferred increases exponentially with tree height
Solution Approach 1:
The patent divides the tree structure into multiple levels (primary tree and secondary trees) where the primary tree maintains the fixed shape for stability, while secondary trees handle the variable data storage. This segmentation allows insertion operations to occur in the secondary trees without requiring transfers throughout the entire tree structure, thus maintaining structural stability while improving insertion speed.
Solution Approach 2:
The patent introduces a hierarchical dimension by creating primary trees that point to multiple secondary trees. This dimensional change allows the system to maintain the fixed shape at the primary tree level while accommodating variable data in secondary trees, reducing the exponential node transfer problem by limiting transfers to local secondary tree operations rather than global tree operations.
2Quantity of substance
If the tree height increases to accommodate more nodes, then the storage capacity increases, but the time spent on node insertion increases sharply
Solution Approach 1:
By segmenting the tree into primary and secondary levels, the patent allows the primary tree to maintain a fixed, manageable height while secondary trees expand to accommodate additional nodes. This segmentation ensures that insertion time does not increase sharply with total node count, as insertions are localized to secondary trees rather than requiring traversal through increasing heights of a single tall tree.
Solution Approach 2:
The patent changes the structural parameters by introducing a hierarchical organization where the primary tree height remains constant while secondary trees provide variable capacity. This parameter change decouples the relationship between total node quantity and insertion time, allowing storage capacity to increase without proportionally increasing insertion time.
3Stability of the object's composition
If existing nodes are transferred to maintain tree balance during insertion, then the tree remains balanced, but the insertion process becomes time-consuming
Solution Approach 1:
The patent segments the tree into primary and secondary levels, allowing balance maintenance to occur locally within secondary trees rather than requiring global rebalancing across the entire tree structure. This segmentation enables the primary tree to maintain its fixed balanced shape while secondary trees handle insertions with minimal transfer operations, reducing insertion time while preserving overall tree balance.
Solution Approach 2:
The patent performs preliminary organization by establishing the primary tree structure with fixed shape and balanced properties before inserting data nodes into secondary trees. This preliminary action ensures that the main tree structure remains balanced without requiring time-consuming transfers during each insertion operation, as the balanced framework is already in place.
Data Source
AI summary
A tree-based node insertion method and a memory device are disclosed in embodiments of the present invention. The tree-based node insertion method includes: according to the key value of a node to be inserted, searching in a primary tree for the nearest node whose key value is smaller than and the most approximate to the key value of the node to be inserted; judging whether the current secondary tree is full, and if so, selecting a node from the current secondary tree as a split node, transferring all the nodes on the right of the split node in the current secondary tree to the new secondary tree, and if not, inserting the node to be inserted into the current secondary tree.