Operating Systems 10EC65 Unit 7
Scheduling
Reference Book: “Operating Systems - A Concept based Approach” D. M. Dhamdhare, TMH, 3rd Edition, 2010
Shrishail Bhat, AITM Bhatkal
Operating Systems, by Dhananjay Dhamdhere 7.2
Introduction
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• Scheduling is the activity of selecting the next request to be serviced by a server – In an OS, a request is the execution of a job or a process, and the server is the CPU – A user submits a request and waits for its completion
• Four events related to scheduling are – – – –
Arrival Scheduling Preemption Completion
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Scheduling
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Scheduling Terminology and Concepts
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Scheduling Terminology and Concepts (continued)
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Scheduling Terminology and Concepts (continued)
Shrishail Bhat, AITM Bhatkal
Operating Systems, by Dhananjay Dhamdhere 7.7
Copyright © 2008
Fundamental Techniques of Scheduling
• Schedulers use three fundamental techniques: – Priority-based scheduling • Provides high throughput of the system
– Reordering of requests • Implicit in preemption – Enhances user service and/or throughput
– Variation of time slice • Smaller values of time slice provide better response times, but lower CPU efficiency • Use larger time slice for CPU-bound processes
Shrishail Bhat, AITM Bhatkal
Operating Systems, by Dhananjay Dhamdhere 7.8
The Role of Priority
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• Priority: tie-breaking rule employed by scheduler when many requests await attention of server – May be static or dynamic
• Some process reorderings could be obtained through priorities – E.g., Short processes serviced before long ones – Some reorderings would need complex priority functions
• What if processes have the same priority? – Use round-robin scheduling
• May lead to starvation of low-priority requests – Solution: aging of requests Shrishail Bhat, AITM Bhatkal
Scheduling Policies
• A scheduling policy determines the quality of service provided to the user. • Two categories based on preemption: – Nonpreemptive Scheduling Policies – Preemptive Scheduling Policies
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Operating Systems, by Dhananjay Dhamdhere 7.10
Nonpreemptive Scheduling Policies
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• A server always services a scheduled request to completion • Preemption never occurs • Scheduling is performed only when processing of the previously scheduled request gets completed • Attractive because of its simplicity • Some nonpreemptive scheduling policies: – First-come, first-served (FCFS) scheduling – Shortest request next (SRN) scheduling – Highest response ratio next (HRN) scheduling Shrishail Bhat, AITM Bhatkal
First-Come, First-Served (FCFS) Scheduling
• Requests are scheduled in the order in which they arrive in the system • The list of pending requests is organized as a queue • The scheduler always schedules the first request in the list
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FCFS Scheduling – An Example
Short requests may suffer high weighted turnarounds
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Shortest Request Next (SRN) Scheduling
• It always schedules the request with the smallest service time • A request remains pending until all shorter requests have been serviced • The SRN policy offers poor service to long processes, because a steady stream of short processes arriving in the system can starve a long process
Shrishail Bhat, AITM Bhatkal
SRN Scheduling – An Example
May cause starvation of long processes
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Highest Response Ratio Next (HRN) Scheduling • It computes the response ratios of all processes in the system and selects the process with the highest response ratio
• The response ratio of a newly arrived process is 1 • The response ratio of a short process increases more rapidly than that of a long process, so shorter processes are favoured for scheduling • However, the response ratio of a long process eventually becomes large enough for the process to get scheduled • This does not cause starvation of long processes Shrishail Bhat, AITM Bhatkal
HRN Scheduling – An Example
Use of response ratio counters starvation Shrishail Bhat, AITM Bhatkal
Nonpreemptive Scheduling Policies (continued) Do it yourself
• Calculate the mean turnaround time and mean weighted turnaround for the following set of processes using – FCFS Scheduling – SRN Scheduling – HRN Scheduling Process
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Arrival time
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Service time
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Preemptive Scheduling Policies
• The server can be switched to the processing of a new request before completing current request – Preempted request is put back into pending list – Its servicing is resumed when it is scheduled again
• A request may be scheduled many times before it is completed – Larger scheduling overhead than with non-preemptive scheduling
• Used in multiprogramming and time-sharing OSs
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Preemptive Scheduling Policies (continued)
• Some preemptive scheduling policies: – Round-robin (RR) scheduling with time slicing – Least completed next (LCN) scheduling – Shortest time to go (STG) scheduling
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Round-Robin (RR) Scheduling
• The time slice, which is designated as δ, is the largest amount of CPU time a request may use when scheduled • A request is preempted at the end of a time slice – A timer interrupt is raised when the time slice elapses
• It provides good response times to all requests • It provides comparable service to all CPU-bound processes • It does not fare well on measures of system performance like throughput because it does not give a favored treatment to short processes Shrishail Bhat, AITM Bhatkal
Round-Robin (RR) Scheduling – An Example
In this example, δ = 1
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Least Completed Next (LCN) Scheduling
• It schedules the process that has so far consumed the least amount of CPU time • All processes will make approximately equal progress in terms of the CPU time consumed by them – Guarantees that short processes will finish ahead of long processes
• It starves long processes of CPU attention • It neglects existing processes if new processes keep arriving in the system Shrishail Bhat, AITM Bhatkal
LCN Scheduling – An Example
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Issues: • Short processes will finish ahead of long processes • Starves long processes of CPU attention • Neglects existing processes if new processes keep arriving in the system Shrishail Bhat, AITM Bhatkal
Shortest Time to Go (STG) Scheduling
• It schedules a process whose remaining CPU time requirements are the smallest in the system • It favors short processes over long ones and provides good throughput • It also favors a process that is nearing completion over short processes entering the system – Helps to improve the turnaround times and weighted turnarounds of processes
• Since it is analogous to the SRN policy, long processes might face starvation Shrishail Bhat, AITM Bhatkal
STG Scheduling – An Example
Since it is analogous to the SRN policy, long processes might face starvation
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Preemptive Scheduling Policies (continued) Do it yourself
• Calculate the mean turnaround time and mean weighted turnaround for the following set of processes using – RR Scheduling with time slicing (δ = 1) – LCN Scheduling – STG Scheduling Process
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Arrival time
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9
Service time
3
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3
Shrishail Bhat, AITM Bhatkal
Scheduling in Practice
• An OS has to provide a suitable combination of user-centric and system-centric features • It also has to adapt its operation to the nature and number of user requests and availability of resources • A single scheduler and a single scheduling policy cannot address all these its concerns • So an OS has an arrangement consisting of three schedulers called long-term scheduler, medium-term scheduler and shortterm scheduler to address different user-centric and systemcentric issues Shrishail Bhat, AITM Bhatkal
Scheduling in Practice (continued)
• Long-term scheduler: Decides when to admit an arrived process for scheduling, depending on its nature (whether CPUbound or I/O-bound) and on availability of resources like kernel data structures and disk space for swapping • Medium-term scheduler: Decides when to swap-out a process from memory and when to load it back, so that a sufficient number of ready processes would exist in memory • Short-term scheduler: Decides which ready process to service next on the CPU and for how long Shrishail Bhat, AITM Bhatkal
Scheduling in Practice (continued)
• The short-term scheduler is the one that actually selects a process for operation • Hence it is also called the process scheduler
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Event Handling and Scheduling
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Event Handling and Scheduling (continued)
• The kernel operates in an interrupt-driven manner • Every event that requires the kernel’s attention causes an interrupt • The interrupt handler performs context save and invokes an event handler • The event handler processes the event and changes the state of the process affected by the event • It then invokes the long-term, medium-term or short-term scheduler as appropriate Shrishail Bhat, AITM Bhatkal
Event Handling and Scheduling (continued)
• For example, the event handler that creates a new process invokes the long-term scheduler • The medium-term scheduler is invoked when a process is to be suspended or resumed • The short-term scheduler gains control and selects a process for execution
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Scheduling in Time-Sharing Systems
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Scheduling in Time-Sharing Systems (continued) • The long-term scheduler admits a process when resources can be allocated to it • It allocates swap space for the process on a disk, copies the code of the process into the swap space, and adds the process to the list of swapped-out processes • The medium-term scheduler controls swapping of processes and moves processes between the swapped-out, blocked and ready lists • The short-term scheduler selects one process from the ready list for execution • A process may shuttle between the medium-term and short-term schedulers many times due to swapping Shrishail Bhat, AITM Bhatkal
Process Scheduling
• The short-term scheduler is often called the process scheduler • It uses a list of ready processes and decides which process to execute and for how long
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Process Scheduling (continued) • The list of ready processes is maintained as a list of their PCBs • When the process scheduler receives control, it selects one process for execution • The process dispatching mechanism loads two PCB fields – PSW and CPU registers fields – into the CPU to resume execution of the selected process • The context save mechanism is invoked when an interrupt occurs to save the PSW and CPU registers of the interrupted process • The priority computation and reordering mechanism recomputes the priority of requests and reorders the PCB lists to reflect the new priorities Shrishail Bhat, AITM Bhatkal
Priority-based Scheduling
• It offers good response times to high priority processes and good throughput. • Main features: – A mix of CPU-bound and I/O-bound processes exist in the system – An I/O-bound process has a higher priority than a CPU-bound process. – Process priorities are static. – Process scheduling is preemptive.
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Priority-based Scheduling (continued)
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Priority-based Scheduling (continued)
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Round-Robin Scheduling
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Round-Robin Scheduling – An Example
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Multilevel Scheduling
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Multilevel Scheduling (continued)
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Multilevel Adaptive Scheduling
• Also called multilevel feedback scheduling • Scheduler varies priority of process so it receives a time slice consistent with its CPU requirement • Scheduler determines ‘correct’ priority level for a process by observing its recent CPU and I/O usage – Moves the process to this level
• Example: CTSS, a time-sharing OS for the IBM 7094 in the 1960s – Eight-level priority structure Shrishail Bhat, AITM Bhatkal
Fair Share Scheduling
• Fair share: fraction of CPU time to be devoted to a group of processes from same user or application • Ensures an equitable use of the CPU by processes belonging to different users or different applications • Lottery scheduling is a technique for sharing a resource in a probabilistically fair manner – Tickets are issued to applications (or users) on the basis of their fair share of CPU time – Actual share of the resources allocated to the process depends on contention for the resource Shrishail Bhat, AITM Bhatkal
Kernel Preemptibility
• Helps ensure effectiveness of a scheduler – With a noninterruptible kernel, event handlers have mutually exclusive access to kernel data structures without having to use data access synchronization • If handlers have large running times, noninterruptibility causes large kernel latency • May even cause a situation analogous to priority inversion
– Preemptible kernel solves these problems • A high-priority process that is activated by an interrupt would start executing sooner
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Scheduling Heuristics
• Scheduling heuristics reduce overhead and improve user service – Use of a time quantum • After exhausting quantum, process is not considered for scheduling unless granted another quantum – Done only after active processes have exhausted their quanta
– Variation of process priority • Priority could be varied to achieve various goals – Boosted while process is executing a system call – Vary to more accurately characterize the nature of a process
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Power Management
• Idle loop used when no ready processes exist – Wastes power – Bad for power-starved systems • E.g., embedded systems
• Solution: use special modes in CPU – Sleep mode: CPU does not execute instructions but accepts interrupts
• Some computers provide several sleep modes – “Light” or “heavy”
• OSs like Unix and Windows have generalized power management to include all devices Shrishail Bhat, AITM Bhatkal
Real-Time Scheduling
• Real-time scheduling must handle two special scheduling constraints while trying to meet the deadlines of applications – First, processes within real-time applications are interacting processes • Deadline of an application should be translated into appropriate deadlines for the processes
– Second, processes may be periodic • Different instances of a process may arrive at fixed intervals and all of them have to meet their deadlines
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Process Precedences and Feasible Schedules • Dependences between processes (e.g., Pi → Pj) are considered while determining deadlines and scheduling
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• Response requirements are guaranteed to be met (hard real-time systems) or are met probabilistically (soft real-time systems), depending on type of RT system
• RT scheduling focuses on implementing a feasible schedule for an application, if one exists Shrishail Bhat, AITM Bhatkal
Process Precedences and Feasible Schedules (continued)
• Another dynamic scheduling policy: optimistic scheduling – Admits all processes; may miss some deadlines Shrishail Bhat, AITM Bhatkal
Deadline Scheduling
• Two kinds of deadlines can be specified: – Starting deadline: latest instant of time by which operation of the process must begin – Completion deadline: time by which operation of the process must complete • We consider only completion deadlines in the following
• Deadline estimation is done by considering process precedences and working backward from the response requirement of the application Di = Dapplication −∑k Є descendant(i) xk Shrishail Bhat, AITM Bhatkal
Example: Determining Process Deadlines
• Total of service times of processes is 25 seconds • If the application has to produce a response in 25 seconds, the deadlines of the processes would be:
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Earliest Deadline First (EDF) Scheduling
• It always selects the process with the earliest deadline • If pos(Pi) is position of Pi in sequence of scheduling decisions, deadline overrun does not occur if – Condition holds when a feasible schedule exists
• Advantages: Simplicity and nonpreemptive nature • Good policy for static scheduling
Shrishail Bhat, AITM Bhatkal
Earliest Deadline First (EDF) Scheduling (continued) • EDF policy for the deadlines of Figure 7.13:
• P4 : 20 indicates that P4 has the deadline 20 • P2,P3 and P5,P6 have identical deadlines – Three other schedules are possible – None of them would incur deadline overruns
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Example: Problems of EDF Scheduling
• PPG of Figure 7.13 with the edge (P5,P6) removed – Two independent applications: P1–P4 and P6, and P5 – If all processes are to complete by 19 seconds • Feasible schedule does not exist
– Deadlines of the processes: – EDF scheduling may schedule the processes as follows: P1,P2,P3,P4,P5,P6, or P1,P2,P3,P4,P6,P5
• Hence number of processes that miss their deadlines is unpredictable
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Feasibility of schedule for Periodic Processes • Fraction of CPU time used by Pi = xi / Ti • In the following example, fractions of CPU time used add up to 0.93 – If CPU overhead of OS operation is negligible, it is feasible to service these three processes
• In general, set of periodic processes P1, . . . ,Pn that do not perform I/O can be serviced by a hard real-time system that has a negligible overhead if: Shrishail Bhat, AITM Bhatkal
Rate Monotonic (RM) Scheduling
• Determines the rate at which process has to repeat – Rate of Pi = 1 / Ti
• Assigns the rate itself as the priority of the process – A process with a smaller period has a higher priority
• Employs a priority-based scheduling • Can complete its operation early
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Rate Monotonic (RM) Scheduling (continued)
• Rate monotonic scheduling is not guaranteed to find a feasible schedule in all situations – For example, if P3 had a period of 27 seconds
• If application has a large number of processes, may not be able to achieve more than 69 percent CPU utilization if it is to meet deadlines of processes • The deadline-driven scheduling algorithm dynamically assigns process priorities based on their current deadlines – Can achieve 100 percent CPU utilization – Practical performance is lower because of the overhead of dynamic priority assignment Shrishail Bhat, AITM Bhatkal
Scheduling in Unix • Pure time-sharing operating system – In Unix 4.3 BSD, priorities are in the range 0 to 127 • Processes in user mode have priorities between 50 and 127 • Processes in kernel mode have priorities between 0 and 49
• Uses a multilevel adaptive scheduling policy Process priority = base priority for user processes + f (CPU time used recently) + nice value
• For fair share – Add f (CPU time used by processes in group) Process priority = base priority for user processes + f (CPU time used by process) + f (CPU time used by processes in group) + nice value Shrishail Bhat, AITM Bhatkal
Example: Process Scheduling in Unix
Process
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Arrival time
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Service time
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Shrishail Bhat, AITM Bhatkal
Example: Fair Share Scheduling in Unix
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