Workload Serialization via Message Queue and Culler
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for distributed applications lack effective mechanisms to serialize and prioritize workload requests, leading to potential concurrency issues and inefficient processing, particularly when certain operations must be performed sequentially.
Innovation Solution
A system comprising a message queue and a request manager that serializes workload requests based on receipt order and priority, with a culler for monitoring request validity and network connections, ensuring that requests are processed in a first-in-first-out order while preventing concurrent operations on shared resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workload requests are processed concurrently in a distributed system, then processing speed and productivity are improved, but data corruption and system reliability deteriorate when operations must be sequential
Solution Approach 1:
The system segments workload requests into individual units that can be independently tracked and serialized. Each request is broken down into discrete operations that can be managed separately through the message queue, allowing concurrent submission while ensuring sequential execution when needed.
Solution Approach 2:
A message queue acts as an intermediary between request sources and processing components. This mediator receives, queues, and manages workload requests, coordinating access to shared resources and preventing concurrent conflicts while maintaining high throughput through efficient request routing.
2Reliability
If a message queue serializes all workload requests in strict FIFO order, then data integrity and reliability are improved, but processing efficiency and productivity worsen when prioritization is needed
Solution Approach 1:
The message queue implements different serialization behaviors for different request types or priorities. High-priority requests can be processed ahead of lower-priority ones within the same queue, allowing local optimization of processing order based on specific requirements while maintaining overall serialization guarantees.
Solution Approach 2:
The queue system dynamically adjusts processing priorities based on request characteristics, resource availability, and system state. Priority levels and processing orders can change adaptively rather than being fixed, enabling the system to respond to varying workload conditions while maintaining data integrity.
3Reliability
If the system monitors all network connections and request validity continuously, then system reliability and error detection are improved, but computational overhead and device complexity increase
Solution Approach 1:
Requestors and processing components are responsible for reporting their own status and validity. The system uses lightweight mechanisms where components self-report connection status and request completion, reducing the need for complex centralized monitoring while maintaining reliable error detection.
Solution Approach 2:
The system implements feedback loops where processing components report completion status and the message queue monitors for stuck requests. This continuous feedback mechanism enables automatic detection of failures and invalid requests without requiring complex proactive monitoring of all system states.
4Adaptability or versatility
If the system allows multiple requestors to submit workload requests simultaneously, then system versatility and adaptability are improved, but coordination complexity and device complexity increase
Solution Approach 1:
The message queue serves multiple functions: receiving requests from any requestor, serializing them, managing priorities, tracking coordination points, and coordinating processing across the distributed system. This universal component handles all coordination needs through a single standardized interface, reducing overall system complexity.
Solution Approach 2:
The message queue acts as a universal intermediary between multiple requestors and processing components. It abstracts away the complexity of direct peer-to-peer coordination, providing a standardized mechanism for all requestors to submit work and for all processors to receive and track requests, thereby simplifying multi-requestor coordination.
Data Source
AI summary
Apparatuses, systems, methods, and computer program products are provided for processing workload requests in a distributed computing system. In general, a cooperative workload serialization system is provided that includes a Message Queue that is configured to receive and hold workload requests from a number of requestors and a Request Manager that is in communication with the Message Queue and is configured to direct the processing of the workload requests. The system may include a Culler in communication with the Request Manager, where the Culler is configured to monitor the validity of the workload requests. The Request Manager, in turn, may be configured to remove an indicated workload request from the Message Queue based on information from the Culler that the indicated workload request is not valid.