Intelligent Task Message Queue Management for Dynamic Priority Scoring
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Solution Overview
Problem
Existing workflow management systems lack flexibility and scalability in scheduling and processing tasks dynamically, relying on rigid policies that require constant user input and updates to adapt to complex computing systems.
Innovation Solution
Implementing an intelligent task message queue management system that assigns task messages to subclasses based on predetermined rules, generates subclass scores, and dispatches tasks to consumers based on these scores, allowing for dynamic priority adjustment and resource optimization across multiple tenants in a multi-tenant computing environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If rigid scheduling policies are used in task queue management, then system control is simplified, but system flexibility and adaptability deteriorate
Solution Approach 1:
The patent implements dynamic priority scoring for task messages based on multiple factors including tenant-defined weights, task characteristics, and queue conditions. Instead of rigid static policies, the system continuously calculates and updates priorities, allowing the scheduling behavior to adapt dynamically to changing system states and tenant requirements without increasing control complexity
Solution Approach 2:
The system allows tenants to define and modify weight parameters for different task characteristics and queue conditions. By changing these parameters dynamically, the scheduling behavior adapts to different scenarios and tenant preferences while maintaining a consistent underlying framework, thus improving flexibility without proportionally increasing system complexity
2Manufacturing precision
If manual policy updates are required to adapt to complex computing systems, then system precision in task scheduling is improved, but user intervention time and operational overhead increase
Solution Approach 1:
The system performs automatic priority calculation and task routing based on predefined tenant weights and current queue conditions. The intelligent task message queue management service autonomously evaluates task messages, computes priorities using the weighted formula, and dispatches tasks without requiring manual policy updates, thereby maintaining scheduling precision while eliminating continuous user intervention
Solution Approach 2:
The system continuously monitors queue conditions and task characteristics, using this feedback to dynamically adjust priority scores. This closed-loop approach allows the system to adapt to changing conditions automatically, maintaining high scheduling precision without requiring manual reconfiguration or user intervention
3Device complexity
If single-queue task management is used, then system simplicity is maintained, but resource allocation efficiency and scalability deteriorate
Solution Approach 1:
The patent segments the single task queue into multiple tenant-specific worklist queues, each managed independently with its own priority calculations. This segmentation allows efficient resource allocation per tenant while the overarching management framework remains unified and simple, thus improving productivity without proportionally increasing complexity
Solution Approach 2:
The intelligent task message queue management service provides universal priority calculation and routing functionality that serves multiple tenant queues simultaneously. This multi-functional approach allows the system to manage multiple queues with a single unified mechanism, improving resource allocation efficiency across tenants while maintaining operational simplicity through a common management layer
Data Source
AI summary
An approach for intelligent task message queue management may be provided herein. The approach may include receiving a task message from a producer at an intelligent task message queue management service. The approach may include assigning a subclass to the task message based on a predetermined set of rules. The approach may include assigning the task message to a one of a plurality of subclass worklist queues based on the assigned subclass. The approach may include generating a subclass score for the task message based on a weight associated with the assigned subclass work queue. The approach may include dispatching the task message to a consumer based on the generated subclass score for the task message.