Weighted Queue Scheduling Fairness Factors
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Solution Overview
Problem
The strict priority scheduling scheme in data switching networks can result in bias when multiple data packet requests have the same priority level, leading to consecutive ordering and unfair selection, as only priority weights are considered without additional factors.
Innovation Solution
A weighted round robin scheduling method is implemented, using additional fairness factors such as validity bits, priority weights, positions, and last scheduled queue IDs to prevent bias by generating temporary weights that prioritize equal-priority requests based on their position and order, ensuring non-biased queuing and selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If strict priority scheduling is used to maintain QoS, then high priority data packets are transmitted first ensuring quality of service, but bias occurs in scheduling when multiple data packet requests have the same priority level
Solution Approach 1:
The patent modifies the scheduling parameters by introducing a round-robin counter and position-based weighting factors that dynamically adjust the selection criteria beyond static priority levels. This allows equal-priority queues to be selected in a rotating fashion, preventing consecutive selection bias while maintaining priority-based QoS differentiation.
Solution Approach 2:
The scheduling mechanism transitions from a static priority-based selection to a dynamic system that incorporates round-robin counting and position-dependent weights. The scheduler state changes with each selection cycle, adapting the selection probability based on the current round-robin counter value and queue positions, thereby eliminating persistent bias toward initially positioned queues.
2Ease of operation
If weighted round robin scheduling is implemented to prevent bias, then fair selection among equal priority requests is achieved, but additional complexity is introduced through fairness factors and temporary weight calculations
Solution Approach 1:
The scheduling decision process is segmented into distinct computational stages: calculating base weights from priority levels, computing position-based weighting factors, determining temporary weights by combining these factors, and finally selecting queues based on temporary weights. This segmentation organizes the complexity into manageable, modular operations that can be implemented systematically.
Solution Approach 2:
The patent performs preliminary calculations of weighting factors and temporary weights before the actual queue selection occurs. By pre-computing these values based on current queue states and round-robin counter positions, the selection process itself becomes simpler, as it only needs to compare pre-prepared temporary weight values rather than performing complex evaluations during selection.
Data Source
AI summary
A computer-implemented medium using a scheduler for processing requests by receiving packet data from multiple source ports and then classifying, the received packet data based upon the source port received and a destination port the data being sent. Next, sorting, the classified packet data into multiple queues in a buffer, and updating, a static component of one or more of the multiple queues upon the queue receiving the sorted classified data packet. Further, scheduling, using the scheduler based upon the destination port availability and a set of fairness factors including priority weights and positions, for selecting a dequeuing of data packets from a set of corresponding queues of the multiple queues, and then updating the static of the dequeued queue upon the data packet being outputted from the dequeued queue.