Quasi-Parallel Cross-Database Control for Synchronous Data Access
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Solution Overview
Problem
Current database systems cannot operate individual customer class database units synchronously, leading to inefficiencies in processing and accessing data across separate and independent database units, particularly in telecom companies with various contract types.
Innovation Solution
A method for controlling cross-database routines that allows quasi-parallel processing of information elements across multiple database units by a central unit, where information groups are divided into sub-elements and processed simultaneously, ensuring synchronous operation and preventing inconsistencies through a coordinator routine and dispatcher routine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If separate and independent database units are set up for individual information classes, then data organization and management become simpler and more specialized, but synchronous processing and access across multiple database units become impossible
Solution Approach 1:
The system segments data into different information classes (e.g., customer data, contract data, billing data) and stores them in separate database units. Each database unit is independently managed and optimized for its specific data type, enabling specialized data organization while maintaining the ability to access multiple units through the central control unit.
Solution Approach 2:
A central control unit acts as an intermediary between input systems and multiple database units. It coordinates access to different database units, manages transaction routing, and ensures synchronous processing by controlling the flow of transactions across database boundaries, thereby enabling cross-database operations without compromising individual database independence.
2Reliability
If sequential access to individual databases is used, then data consistency is maintained, but processing time increases significantly
Solution Approach 1:
The system enables continuous parallel processing of transactions across multiple database units by maintaining coordinated access control. Multiple transactions can be processed simultaneously in different database units while the central control unit ensures data consistency through transaction coordination, eliminating the need for sequential access and significantly reducing processing time.
Solution Approach 2:
The system dynamically adjusts the level of parallelism and coordination based on transaction requirements. For transactions requiring high consistency, it implements stricter coordination protocols; for less critical transactions, it allows greater parallelism. This dynamic approach optimizes both processing speed and data consistency maintenance.
3Productivity
If parallel processing across multiple database units is implemented, then processing speed increases, but system complexity and coordination overhead increase
Solution Approach 1:
The central control unit is designed as a universal coordinator that can manage multiple types of database units (relational, hierarchical, object-oriented) and handle various transaction types. It provides a unified interface and coordination mechanism that works across different database systems, reducing the need for separate coordination logic for each database type and thereby managing complexity while enabling parallel processing.
4Productivity
If multiple database units are accessed in parallel, then complex manipulations can be performed quickly, but ensuring uniform approval and preventing inconsistencies becomes more difficult
Solution Approach 1:
The central control unit implements feedback mechanisms by monitoring transaction status and data changes across all database units in real-time. It receives status information from each database unit, evaluates consistency conditions, and adjusts coordination actions accordingly. This feedback loop ensures that parallel operations maintain data consistency while achieving high processing speeds.
Data Source
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AI summary
The method involves supplying an information group in a central processing unit (10) by using input systems (20). The information group is divided in information elements in an allocation routine in the central processing unit. The information elements are divided in sub elements of the application routines (33) in database units (30,30',30'',30'''). The sub elements are processed in the data bases (31,31',31'',31''') in a quasi-parallel manner. An independent claim is also included for a database system.