Priority Scheduling Manager Single Queue Reordering
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Solution Overview
Problem
Existing priority queue systems in distributed computing systems require significant computing resources to update all events in the queue when new events are added, especially when multiple queues or buckets are used, and they often need to monitor multiple buckets to find the highest priority event, which is inefficient.
Innovation Solution
A scheduling manager in a distributed computing system that uses a single queue with priority information to reorder events based on their priority, updating at most two events when a new event with higher priority is added, eliminating the need for multiple queues and reducing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple queues or buckets are used to manage priority events, then priority scheduling capability is improved, but device complexity and computing resource usage increase
Solution Approach 1:
The patent merges multiple priority queues or buckets into a single queue structure. Instead of maintaining separate queues for different priority levels, the invention uses one queue where events are ordered by priority, eliminating the need for multiple data structures and reducing system complexity while preserving priority scheduling capability.
Solution Approach 2:
The single queue is designed to handle multiple priority levels universally. The queue incorporates priority information within each event and uses reorder information to manage different priority levels within the same data structure, making the single queue multi-functional in handling various priority scenarios.
2Manufacturing precision
If all events in the queue are updated when a new event is added, then priority ordering accuracy is maintained, but computing resource consumption increases
Solution Approach 1:
The patent extracts only the necessary events for updating when a new event is added to the queue. Instead of updating all events, the system identifies and updates only those events that are affected by the new event's insertion, specifically focusing on events with similar or lower priority that might need reordering, thereby reducing computing resource consumption while maintaining accuracy.
Solution Approach 2:
The system performs partial updates rather than complete updates of the queue. When a new event is inserted, only the minimal necessary portion of the queue (at most two events with reorder information) is updated to maintain priority ordering, avoiding the excessive action of updating all events and thus reducing computational overhead.
3Measurement precision
If multiple buckets are monitored to find the highest priority event, then event selection accuracy is improved, but time consumption increases
Solution Approach 1:
The patent combines multiple buckets into a single queue where the highest priority event can be identified without monitoring multiple separate structures. The single queue maintains events in priority order with reorder information, allowing the system to identify the highest priority event by examining only the front of the queue rather than scanning multiple buckets, thus reducing time consumption while maintaining selection accuracy.
4Device complexity
If a single queue with priority information is used, then device complexity is reduced, but ensuring priority ordering becomes more challenging
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing reorder information within each event in the queue. When events are inserted or prioritized, the system预先 determines the reorder information that indicates how events should be reordered, so that when priority changes occur, the maintenance of correct ordering is simplified because the reordering logic is already prepared in advance.
Solution Approach 2:
The system uses feedback through reorder information that is updated and maintained within the queue structure. When a new event is added or priorities change, the reorder information provides feedback on how the queue should be reorganized, enabling the system to automatically maintain correct priority ordering in the single queue without complex external control mechanisms.
Data Source
AI summary
Embodiments disclosed herein are related to systems and methods for a scheduling manager or other element of a distributed computing system to schedule events performed by a various computing systems based on a priority of the events. The distributed computing system includes one or more processors and system memory having stored thereon executable instructions. When the executable instructions are executed by the processors, the computing system receives a new event that is to be added to a queue of events that are to be executed by the distributed computing system, determines that there is a current active event in the queue, compares a priority of the new event with a priority of the current active event, and based on the comparison, modifies an order of the events in the queue by updating the event in the queue that is to be the current active event.