Concurrent Database Operations Using Field-Specific Thread Allocation
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Solution Overview
Problem
Existing database synchronization mechanisms are inefficient due to their serial nature, leading to slow responsiveness and potential failures, especially when handling concurrent changes in real estate property ownership expenses, as they often require mutual exclusion techniques that can cause deadlocks and resource inefficiencies.
Innovation Solution
A system and method that employs data field-specific thread tasking, utilizing an underwriting server and scheduler to allocate threads for concurrent database operations, allowing for parallel execution of tasks such as create, read, update, and delete operations on multiple data fields, thereby managing real estate ownership expense insurance policies and reimbursing owners for increases in maintenance fees and assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If serial database update operations are used on the client device, then data consistency is maintained, but synchronization speed and responsiveness deteriorate
Solution Approach 1:
The patent segments the database record into multiple independent data fields, allowing concurrent access and modification of different fields by multiple threads. This segmentation enables parallel processing of database updates while maintaining consistency within each field, thereby improving synchronization speed without compromising data integrity.
Solution Approach 2:
The patent introduces version vectors as an intermediary mechanism to coordinate concurrent database operations. Version vectors track modifications across different threads and data fields, enabling the system to detect and resolve conflicts without requiring serial execution, thus maintaining data consistency while allowing parallel processing.
2Reliability
If mutual exclusion techniques are used for database operations, then data integrity is protected, but system responsiveness and throughput deteriorate
Solution Approach 1:
The patent divides the database record into separate data fields that can be accessed and modified independently by different threads. This segmentation eliminates the need for mutual exclusion locks across the entire record, allowing multiple threads to operate simultaneously on different fields, thereby improving system throughput while maintaining data integrity through field-level consistency.
Solution Approach 2:
The patent changes the concurrency control parameter from serial execution with mutual exclusion to parallel execution with version vector-based conflict detection. This parameter change allows the system to achieve both high throughput and data integrity by allowing concurrent operations that are later validated and merged using version vectors.
3Speed
If concurrent thread operations are implemented on data fields, then processing speed improves, but complexity of managing thread allocation and synchronization increases
Solution Approach 1:
The patent implements a universal version vector mechanism that serves multiple functions: tracking modifications, detecting conflicts, and coordinating synchronization across all data fields and threads. This single multi-functional mechanism simplifies thread management complexity while enabling concurrent processing, as the same version vector system handles all synchronization needs without requiring field-specific or thread-specific coordination logic.
Data Source
AI summary
A method and system for handling data field tasks, the system comprising a database containing records and data fields associated with real estate ownership expense insurance policies that reimburses for increases in property ownership expenses including increases in maintenance fees and assessments from non-covered losses, an underwriting server communicatively coupled to one or more client devices and data sources over a communications network, the underwriting server comprising a processor that configures processes to the data sources and generates data source connections to receive information from the data sources, and a scheduler that allocates threads within the processes to at least one of the data fields associated with premium for coverage, expenses, and reimbursement of the real estate ownership expense insurance policies, and assigns the threads to tasks for performing operations on the at least one of the data fields based on the information from the data sources.