State Object Data Store Using Modified Ternary Tree

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Solution Overview

Problem

Current technologies face challenges in efficiently storing and updating large quantities of state data at high rates while minimizing memory usage, especially in networked environments with hardware limitations, where existing disk-based trees and data store implementations struggle to maintain millions of objects at sustained rates of 50,000 or greater per second.

Innovation Solution

The implementation of a State Object Data Store (SODS) using a modified ternary tree structure with an index file and data object structure, allowing for efficient storage and updates of state objects across different hardware capabilities, utilizing an index file for fast look-ups and in-place updates, and dynamic allocation of storage space to optimize disk usage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If disk-based trees and data store implementations are used, then storage capacity is improved, but processing speed and update rate deteriorate

Engineering Contradiction:

Improvestorage capacityVSAvoidprocessing speed

Core Design Contradiction:

Quantity of substanceVSProductivity

Solution Approach 1:

The data store is segmented into a hierarchical structure with a trie-based index layer and a data layer. The index is divided into prefix tables that store common prefixes, allowing the system to quickly locate data without scanning entire datasets. This segmentation enables millions of updates per second while maintaining billions of objects in storage.

Inventive Principle:

Principle #1Segmentation

2Productivity

If memory usage is increased, then real-time processing capability is improved, but hardware cost and resource consumption worsen

Engineering Contradiction:

Improvereal-time processing capabilityVSAvoidmemory usage

Core Design Contradiction:

ProductivityVSQuantity of substance

Solution Approach 1:

The system applies local quality by keeping only essential index structures in memory (prefix tables with common prefixes) while storing the bulk of data objects on disk. This selective memory allocation optimizes real-time processing for frequently accessed data while minimizing overall memory consumption to fit hardware constraints.

Inventive Principle:

Principle #3Local quality

3Duration of action of stationary object

If data retention period is extended, then data completeness is improved, but storage space consumption worsens

Engineering Contradiction:

Improvedata retention periodVSAvoidstorage space consumption

Core Design Contradiction:

Duration of action of stationary objectVSVolume of stationary object

Solution Approach 1:

The data store implements nesting by organizing data objects within data files that can be selectively loaded and unloaded. Historical data is nested within the same storage structure but can be moved to cold storage or archived segments, allowing extended retention periods while managing active storage space through hierarchical data organization.

Inventive Principle:

Principle #7Nested doll (Nesting)

Data Source

PatentUS20220414085A1System and method for state object data store

Publication Date: 2022.12.29 CISCO TECHNOLOGY INC

AI summary

Disclosed in a fast, compact, efficient, hardware agnostic, stateful data store that can universally store and track millions of stateful data objects, such as networking routing data (or any stateful data) in files for use in, for example, embedded applications. Stateful data objects can be tracked by a modified tree for updating and insert data objects into the stateful data store. The stateful data object can also be allocated additional space in memory for potential future data updates.