Processorsharing

Processor sharing is a scheduling discipline used in operating systems and queueing theory in which all active jobs share the processor capacity equally. If there are n jobs currently being served, each one receives a service rate of μ/n, where μ is the total service rate of the system. The policy is generally considered preemptive-resume: as the set of active jobs changes due to arrivals or completions, the shares are instantly reallocated and progress continues from the current state.

As an idealized model, PS abstracts away the specifics of scheduling order and prioritization, focusing instead on fairness. It contrasts with first-come-first-served or fixed-priority schemes by ensuring that no job can starve another; every active job progresses at the same instantaneous rate regardless of its identity. In practice, exact PS is difficult to implement, but it informs design and analysis of systems where simultaneous service is feasible, such as multi-processor CPUs, time-shliced environments, or shared network links.

Generalized Processor Sharing (GPS) extends PS by allowing different customers to receive different fixed shares of capacity. Discrete, packet-based networks emulate GPS with scheduling frameworks such as Weighted Fair Queuing (WFQ) or other fair queuing algorithms, which approximate the continuous PS ideal.

Applications and implications: PS is used to model the performance of time-sharing operating systems, multi-processor servers, and network routers where fair allocation of processing or bandwidth is desirable. Advantages include fairness and intuitive behavior under load; limitations include the challenge of exact implementation, potential overhead from frequent context switches, and deviations from PS in real hardware or highly dynamic workloads.