Distributed Database Key-Value Ring Balancing
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Solution Overview
Problem
Existing communication systems face challenges in efficiently managing and searching large databases within communication networks, particularly in ensuring fast search operations without degrading system performance, as prior art fails to provide adequate means for managing and locating information in large databases.
Innovation Solution
A distributed database system is implemented across multiple computing devices, where each device stores a subset of key-value pairs sorted in a logical order, allowing for efficient key-value pair queries and balancing operations to distribute storage evenly across devices, enabling fast search processes and maintaining system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a large database is stored in a centralized manner, then data storage capacity is improved, but search speed and system performance deteriorate
Solution Approach 1:
The patent divides the large database into multiple distributed nodes, where each node stores a portion of the key-value pairs. This segmentation allows the system to maintain large storage capacity while enabling parallel search operations across nodes, thus preserving search speed. The distributed architecture eliminates the bottleneck of centralized storage by distributing both data and search operations across multiple independent units.
2Quantity of substance
If database size increases to billions of entries, then data storage capacity is improved, but search efficiency and system performance deteriorate
Solution Approach 1:
The patent introduces a hierarchical dimension to the database architecture by organizing data into distributed nodes with hierarchical key ranges. Each node manages a specific range of keys, and the system provides hierarchical routing mechanisms. This dimensional organization allows efficient location of data even in databases with billions of entries by narrowing down the search space through hierarchical navigation rather than linear scanning.
Solution Approach 2:
The patent employs intermediary components such as distributed hash tables and routing mechanisms that mediate between the query and the actual data storage locations. These intermediaries enable efficient key-to-node mapping and facilitate rapid data location without requiring direct access to all database entries, thus maintaining search efficiency at scale.
3Speed
If data is distributed across multiple computing devices, then search efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements universal protocols and standardized interfaces that enable multiple computing devices to function as coherent database nodes. Each node performs multiple functions including data storage, search operation execution, and routing assistance. This multi-functionality reduces system complexity by eliminating the need for specialized components at each node, as standardized multi-purpose protocols handle diverse operations uniformly across the distributed system.
Data Source
AI summary
A self-balancing binary search capable distributed database (DB) includes a number of computing devices associated with a communication system and/or network. Each of the respective computing devices forming the distributed DB stores a subset of the overall information included within the distributed DB. Based on keys of key-value pairs (KVPs) stored in the computing devices, the computing devices are arranged logically to form a sorted key-ordered ring such that each computing device includes KVPs with keys higher than a predecessor computing device and lower than a successor computing device. A requested KVP query is made to any computing device in the distributed DB, which may include generating and transmitting another query to one or more other computing devices until the requested KVP is found. The distributed DB performs balancing operations moving the KVPs from computing devices with higher storage usage to computing devices with lower storage usage.