Fair-share CPU scheduling

Fair-share CPU scheduling is a scheduling algorithm used in operating systems that aims to allocate CPU resources fairly among different user or process groups. Unlike traditional priority-based schedulers, fair-share scheduling assigns a weight to each process group based on its historical usage and allocates CPU time to ensure no group is starved of resources for extended periods.

This scheduling approach is particularly valuable in multi-user systems and virtualized environments where multiple users or virtual machines share a single physical CPU. It provides better resource utilization and ensures equal opportunities for all groups to access CPU time.

How Fair-Share Scheduling Works

Fair-share scheduling operates on the principle of entitlement and usage tracking. Each process group is assigned a fair-share weight based on its historical CPU consumption. Groups that have used less than their fair share receive higher priority, while groups that have exceeded their allocation receive lower priority.

Fair-Share Scheduling Algorithms

Several algorithms implement fair-share scheduling principles

• Weighted Fair Queueing (WFQ) Assigns weights to each process based on traffic characteristics and ensures each receives its proportional CPU time.

• Generalized Processor Sharing (GPS) Uses fluid modeling to assign virtual processors to each process, providing precise control over resource allocation.

• Stochastic Fairness Queueing (SFQ) Divides bandwidth into equal time slots and assigns processes based on hash values to ensure fairness.

• Fair Queueing (FQ) Assigns a queue to each flow and serves them in round-robin fashion.

• Virtual Round Robin (VRR) Assigns virtual time slices to processes and serves them in round-robin manner.

Example Fair-Share Calculation

Consider three process groups with the following historical CPU usage over 60 seconds

Fair-Share Weight = Historical Usage ÷ Entitlement

Group A receives higher scheduling priority since it has used only 50% of its entitled resources, while Group C receives lower priority for exceeding its fair share by 50%.

Implementation Approaches

Kernel-Level Implementation

• Process Group Identification Kernel identifies groups based on process ownership and assigns weights based on historical CPU usage.

• Fair-Share Calculation Calculates each group's entitlement to CPU resources based on system capacity and group count.

• Resource Allocation Allocates CPU time based on fair-share weights, allowing unused resources to accumulate for later use.

• Dynamic Weight Adjustment Periodically adjusts weights based on recent usage patterns.

User-Level Implementation

• Group Formation Groups processes based on resource requirements or ownership.

• Weight Assignment Assigns weights representing each group's CPU entitlement.

• Monitoring and Adjustment Continuously monitors usage and adjusts weights to maintain fairness.

Advantages

• Fairness Ensures equitable CPU allocation regardless of process priorities or resource demands.

• Starvation Prevention Prevents any group from being completely denied CPU access.

• Predictability Provides consistent resource allocation that improves system stability.

• Scalability Works effectively with large numbers of process groups.

• Resource Optimization Maximizes CPU utilization based on historical patterns rather than fixed priorities.

Disadvantages

• Computational Overhead Requires continuous tracking and calculation of usage statistics and fair-share weights.

• Implementation Complexity More complex than simple priority-based schedulers, requiring careful configuration.

• Real-Time Limitations May not be suitable for hard real-time systems requiring guaranteed response times.

• Tuning Difficulty Requires understanding of application usage patterns to set appropriate weights.

• Limited Effectiveness Less effective with many short-lived processes or highly variable workloads.

Integration with Other Schedulers

Fair-share scheduling can be combined with other algorithms

• Multi-Level Feedback Queue (MLFQ) Uses MLFQ for priority-based allocation while fair-share ensures group equity.

• Priority Scheduling Combines process priorities with fair-share weights for balanced allocation.

• Real-Time Scheduling Integrates deadline-based scheduling with fair-share principles for mixed workloads.

Conclusion

Fair-share CPU scheduling provides an effective solution for equitable resource allocation in multi-user and virtualized environments. While it introduces computational overhead and complexity, it ensures long-term fairness and prevents resource starvation, making it valuable for systems requiring balanced CPU distribution among competing process groups.