Asynchronous Operation Distribution for Synchronous Execution
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Solution Overview
Problem
Software applications face corruption due to out-of-sequence operations when asynchronous requests are distributed across multiple instances without communication, particularly during upgrades and entity provisioning in network-based systems.
Innovation Solution
A system and method that determine consumer identification for client operations and approximately evenly distribute them between two asynchronous queues based on an algorithm (e.g., even/odd identifiers) for synchronous execution, ensuring operations with earlier timestamps are executed first.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If operations are distributed across multiple application instances asynchronously, then system throughput and scalability are improved, but data corruption occurs due to out-of-sequence execution
Solution Approach 1:
The system segments operations into distinct asynchronous queues based on consumer identifier patterns (even/odd), allowing parallel processing while maintaining isolation between operation groups. This segmentation enables throughput improvement while preventing cross-contamination that causes data corruption.
Solution Approach 2:
The system performs preliminary classification of operations by consumer identifier before distribution, determining the target queue in advance based on identifier patterns. This preliminary action ensures that operations are routed to appropriate queues before execution, preventing out-of-sequence processing and maintaining data integrity.
2Reliability
If operations are executed synchronously to maintain order, then data integrity is preserved, but system responsiveness and throughput decrease
Solution Approach 1:
The system divides the monolithic synchronous processing into multiple parallel asynchronous queues, each handling specific operation groups. This segmentation allows concurrent execution while maintaining internal order within each queue, achieving both throughput improvement and data integrity.
Solution Approach 2:
The asynchronous queue acts as an intermediary between operation submission and execution, buffering operations and managing their execution order. This intermediary mechanism decouples the submission rate from execution rate, improving throughput while preserving execution semantics through timestamp-based ordering.
3Adaptability or versatility
If multiple application instances process the same subscriber operations independently, then system scalability is improved, but out-of-sequence operations occur causing corruption
Solution Approach 1:
The system segments the subscriber operation space by consumer identifier patterns, directing even identifiers to one instance and odd identifiers to another. This segmentation enables multiple instances to process operations independently and concurrently while ensuring each instance handles a consistent subset, preventing out-of-sequence execution.
Solution Approach 2:
Each application instance is assigned a specific quality characteristic (handling operations with particular consumer identifier patterns), making them specialized for certain operation types. This local quality ensures that each instance processes its assigned operations in correct sequence without interfering with other instances, maintaining both scalability and reliability.
Data Source
AI summary
A system and method may manage traffic to software applications that ingest operations into an asynchronous queue when those operations are required to execute in a synchronous manner. An identifier may be retrieved from data corresponding to each client operation. A process distribution module may be placed in front of the two incompatible systems/applications to inspect each data payload and intelligently distribute the transactions to each instance based on a well-defined algorithm (e.g., even/odd, last digit, etc.). Synchronous execution may then occur according to a timestamp for each operation.


