Database Transfer Scheduling with Dynamic Rescheduling
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Solution Overview
Problem
Existing database management systems face challenges in managing data transfer timing effectively, leading to undesirable impacts on account values and potential violations of transfer rules, particularly in financial databases where transfers need to be scheduled to avoid unduly affecting account balances.
Innovation Solution
An electronic system and method that includes a communication interface, memory, and processor to manage data transfers by receiving signals from third-party systems, determining the impact of scheduled transfers on account values, and updating transfer schedules to reschedule data transfers to avoid negative impacts or rule violations, ensuring transfers occur at optimal times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data transfers are scheduled automatically without review, then transfer efficiency is improved, but account value stability deteriorates
Solution Approach 1:
The system implements feedback by continuously monitoring account values and transfer schedules, then automatically adjusting transfer timing based on the monitored state. The processor detects when transfers would cause undesirable account value impacts and reschedules them accordingly, creating a closed-loop control system that maintains stability while preserving overall transfer efficiency.
Solution Approach 2:
The transfer schedule is made dynamic rather than static. The system automatically adjusts transfer timing based on real-time account conditions, allowing the schedule to adapt flexibly to changing account values and transfer patterns. This dynamic adjustment resolves the contradiction by enabling efficient transfers when conditions are favorable while preventing instability when conditions are unfavorable.
2Reliability
If data transfers occur at scheduled times without adjustment, then transfer predictability is improved, but compliance with transfer rules deteriorates
Solution Approach 1:
The system performs preliminary evaluation of scheduled transfers before they execute. The processor proactively identifies potential rule violations by assessing account values and transfer conditions in advance, then reschedules transfers beforehand to ensure compliance. This preliminary action maintains predictability by keeping most transfers on schedule while preventing rule violations.
Solution Approach 2:
The system uses feedback from transfer rule requirements to adjust scheduling decisions. By continuously monitoring transfer rules and account conditions, the system learns which scheduling patterns comply with rules and which do not, then applies this knowledge to maintain both predictability and compliance automatically.
3Stability of the object's composition
If manual review of each data transfer is implemented, then account value stability is improved, but transfer efficiency deteriorates
Solution Approach 1:
The system provides self-service by automatically monitoring its own transfer schedules and account values, then making autonomous decisions about when to reschedule transfers. The processor acts as both the scheduler and the reviewer, eliminating the need for external manual intervention while maintaining account stability. This self-service capability preserves transfer efficiency by avoiding manual processing delays.
Solution Approach 2:
The system implements automated feedback loops where transfer outcomes and account value changes are continuously monitored and fed back into the scheduling algorithm. This automated feedback mechanism provides the stability benefits of manual review without the efficiency costs, as the system learns from past transfers and automatically optimizes future scheduling decisions.
Data Source
AI summary
A method for managing transfer of data over a network to a recipient system is disclosed. The method is implemented at a database management system that stores a schedule of data transfers associated with records in a database. The method includes: receiving a signal representing an electronic message from a third party system, the electronic message including details of a first scheduled data transfer to a first record in the database at a first transfer time; obtaining details of a second scheduled data transfer from the first record to the recipient system; determining that an effect on the first record by the first and second scheduled data transfers meets stored predefined criteria; updating the schedule of data transfers to change a second transfer time associated with the second scheduled data transfer; and initiating the second scheduled data transfer according to the updated schedule of data transfers.