Real-Time Transaction Routing by Processor Capacity and Configuration
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Solution Overview
Problem
Existing transaction processing systems face challenges in completing transactions in real time due to processing components experiencing overloads or outages, leading to difficulties in routing transactions effectively.
Innovation Solution
A computer system dynamically distributes transactions to processors based on their capacity and configuration, automatically selecting alternate processors in real-time to maintain transaction processing and minimize latency, using parametric data and machine learning models to manage workload distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If transactions are routed to a single processor, then processing simplicity is maintained, but system reliability deteriorates when the processor experiences outages or overloads
Solution Approach 1:
The system segments transaction processing across multiple processors instead of relying on a single processor. Each processor handles specific transactions based on routing decisions, creating independent processing units that can operate autonomously. This segmentation improves reliability by isolating failures to individual processors while maintaining overall system functionality.
Solution Approach 2:
The system introduces an intermediary routing mechanism that sits between transaction sources and processors. This intermediary evaluates processor status, capacity, and suitability in real-time, then directs transactions to appropriate processors. The intermediary abstracts the complexity of multi-processor management from individual transaction handlers while enabling intelligent load distribution and failover.
2Adaptability or versatility
If transactions are distributed across multiple processors, then system robustness is improved, but routing complexity increases
Solution Approach 1:
The routing system dynamically adjusts transaction distribution based on real-time processor status, capacity, and performance metrics. Routing decisions are not static but continuously adapt to changing conditions such as processor outages, load variations, and capacity fluctuations. This dynamic approach enables the system to optimize transaction flow while managing complexity through automated real-time adjustments.
Solution Approach 2:
The system implements feedback loops where processor performance metrics, capacity status, and transaction outcomes are continuously monitored and fed back to the routing mechanism. This feedback enables intelligent decision-making about transaction routing, allowing the system to learn from past performance and adjust routing strategies accordingly. The feedback mechanism automates complex routing decisions based on observed system state.
3Productivity
If processor capacity is increased to handle more transactions, then transaction volume capacity improves, but latency may increase due to overload
Solution Approach 1:
The system applies local quality by matching specific transaction types or characteristics with processors that have appropriate capacity and performance characteristics. Instead of uniformly distributing all transactions, the routing mechanism identifies which processors are best suited for particular transactions based on their current state and capabilities. This ensures transactions are handled by processors operating at optimal capacity levels, preventing overload-induced latency while maximizing overall throughput.
Data Source
AI summary
Techniques for distributing transaction processing based on processor capacity and configuration are described herein. For example, a computer system can determine a trigger event indicating that transactions are no longer to be processed by a first processor. The computer system can select a second processor to which the transactions are to be sent. The second processor can be selected based on a transaction processing capacity of the second processor and a configuration of the second processor that indicates that the second processor is configured to process the transactions. The computer system can receive transaction data indicating that a transaction is to be processed. The transaction can be associated with transaction attributes. The computing system can send the transaction data to the second processor in real-time relative to the transaction data being received based at least in part on the second processor being selected and the transaction attributes.