Overview
Weighted Round Robin extends round robin by assigning each queue a weight that controls how many jobs or bytes it can serve per cycle.
CoreSource checked
Weighted Round Robin
Cycles through queues while giving higher-weight queues more service opportunities.
Quick Facts
Compact metadata for implementation and discovery.
- Category
- Scheduling
- Difficulty
- Beginner
- Family
- Queue Scheduling
- Tier
- Core
- Status
- Verified
- Review
- Source Checked
- Sources
- 1
- Formulas
- 1
- Relationships
- 3
- Code example
- Ready
- Visualization
- Ready
Core Concepts
queue cycleservice weightproportional sharefairness
Quick facts
Complexity
Runtime and memory behavior at a glance.
Best
O(1)
Average
O(n)
Worst
O(n)
Space
O(queues)
When to Use
- Use when simple proportional service is needed across queues or tenants.
- Use when network scheduling is a central requirement.
When Not to Use
- Avoid when job sizes vary widely and precise fairness is required.
- Avoid when task priorities, durations, or fairness goals are unknown or unstable.
What It Does
- Maintains multiple queues
- Cycles through queues
- Serves each queue according to weight
Use Cases
- Network scheduling
- Load balancers
- Shared worker pools
Inputs
- Queues
- Weights
- Jobs or packets
Outputs
- Weighted service order
Key Formulas (1)
Service share
sharei = weighti / ∑(weights)
share_i = weight_i / sum(weights)Describes the intended long-run share for each queue.
Pseudocode
- 1.Assign a weight to each queue
- 2.Visit queues in cyclic order
- 3.Serve up to the queue's weight from each non-empty queue
- 4.Repeat while work remains
Canonical Example
- Input
- weights A:2, B:1
- Output
- order = A, A, B, A, A, B
- Explanation
- Queue A receives roughly twice as many service slots as B.
Implementation Notes
- Decide whether weight means jobs, bytes, time, or another service unit.
- Track waiting time, service time, and queue state separately.
- Keep a tiny example with expected output beside the implementation.
- State whether the policy is preemptive and what fairness, latency, or deadline objective it optimizes.
Common Pitfalls
- Weights based on job count can be unfair when job costs differ.
- A locally fair rule can still create starvation or poor latency under skewed workloads.
- Not defining boundary, empty, or degenerate inputs before implementation.
- Ignoring preemption cost, release times, or starvation can make a schedule look correct only in toy cases.
Interactive Mechanism Walkthrough
Graph Frontier & Edge RelaxationShow a scheduler cycling through queues where high-weight queues get extra turns.
Step 1 of 4: Assign a weight to each queue
timelineNotes
Large jobs can still create short-term unfairness if weights count jobs instead of work size.
Sources (1)
What each reference supports for this entry.
Operating System Concepts
BookOperating-systems reference for Weighted Round Robin CPU scheduling policy, ready-queue ordering, and preemption behavior.
Explore Next
Good next jumps from the relationship graph, ranked for useful discovery.
Variant ofRound Robin Scheduling
Scheduling · Foundation
Weighted round robin extends round robin by assigning different service weights to queues.
Compare with thisRelationships
View full relationship pageVariant ofRound Robin Scheduling
Weighted round robin extends round robin by assigning different service weights to queues.
Related Algorithms
Tags
SchedulingQueueLoad Balancing