Per-Client Resource Counters to Prevent Compute Monopolization
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Solution Overview
Problem
A single client can monopolize or dominate a computing resource, leading to inadequate access for other clients, especially when the client has a large quantity of tasks or tasks that take a long time to execute, thereby disrupting the equitable distribution of resource usage.
Innovation Solution
Implementing a counter for each client that increments when the computing resource is occupied and decrements over time, with a threshold value to prevent the execution of new tasks when the counter exceeds a certain range, ensuring fair access by refraining from executing tasks from dominant clients until their counter value falls below the threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the computing resource executes tasks from a client with a large quantity or long execution time, then the client's task completion is improved, but other clients lose adequate access to the computing resource
Solution Approach 1:
The system performs preliminary assessment of task characteristics (size, execution time, resource requirements) before accepting tasks into the queue. By evaluating tasks in advance and classifying them accordingly, the system can prevent monopolization before it occurs, ensuring that large or time-consuming tasks do not block smaller tasks from other clients.
Solution Approach 2:
The task queue system dynamically adjusts execution priorities and resource allocation based on real-time conditions. When a client accumulates excessive tasks or exhibits monopolizing behavior, the system dynamically reprioritizes queues, suspends certain client tasks, or implements rate-limiting mechanisms to restore fair access for other clients while maintaining progress on accepted tasks.
2Productivity
If the computing resource prioritizes tasks from clients with large quantities of tasks, then task throughput is improved, but wait times for other clients increase
Solution Approach 1:
The system segments the task queue into multiple categories or priority levels based on task characteristics, client behavior patterns, and resource availability. By dividing tasks into segments (e.g., high-priority vs. low-priority queues, or separate queues for different client types), the system can optimize throughput for critical tasks while ensuring timely execution for other clients, preventing any single client from monopolizing all resources.
Solution Approach 2:
The system changes execution parameters such as task priority levels, resource allocation ratios, and queue processing speeds based on real-time monitoring of client behavior and task characteristics. By dynamically adjusting these parameters, the system can maintain high throughput for important tasks while controlling wait times for other clients, preventing monopolization without sacrificing overall productivity.
3Adaptability or versatility
If the computing resource accepts all tasks from clients without limitation, then client service coverage is improved, but resource monopolization occurs
Solution Approach 1:
The system implements continuous feedback mechanisms that monitor client task submission patterns, resource consumption, and execution progress. When a client's counter value (indicating accumulated task burden) exceeds predefined thresholds, the system provides feedback by limiting further task acceptance, suspending execution, or applying penalties. This feedback loop enables the system to maintain broad service coverage while preventing resource monopolization through automated enforcement of fair access policies.
Data Source
AI summary
A computing resource may be monopolized or dominated by a client, if the client has a large quantity of tasks for execution and/or the tasks from that client take a long time to execute. In some embodiments, each client is associated with a respective counter, and the counter is indicative of how much the computing resource has been recently occupied by the client associated with that counter. In some embodiments, the computing resource refrains from executing new tasks for a client if its counter is within a particular range. In some embodiments, a counter increments when the computing resource is occupied by a client and decrements otherwise based on the passage of time. In some embodiments, different counters may have different rates of incrementing or decrementing, or different particular ranges.