1. Chapter 5:
Process Scheduling

2. Outline Scheduling Criteria Scheduling Algorithms Basic Concepts
CPU-I/O Burst Cycle
CPU Scheduler
Preemptive Scheduling
Dispatcher
Scheduling Criteria
Scheduling Algorithms
First-Come, First-Serve Scheduling
Shortest-Job-First Scheduling
Priority Scheduling
Round-Robin Scheduling
Multilevel Queue Scheduling
Multilevel Feedback-Queue Scheduling

3. Basic Concepts CPU: One of the primary computer resource
Maximum CPU utilization obtained with multiprogramming
Several processes are kept in memory
CPU–I/O Burst Cycle – Process execution consists of a cycle of CPU execution and I/O wait.
CPU burst distribution determines how to schedule the processes.

4. Alternating Sequence of CPU And I/O Bursts

5. Histogram of CPU-burst Times
Normally a process starts with frequent
short CPU bursts and then it stabilizes
and shifts to long but infrequent
CPU bursts
I/O bound processes usually have many small CPU bursts
CPU bound programs usually have few but long CPU bursts
CPU-bound program

6. CPU Scheduler
Selects from among the processes in memory that are ready to execute, and allocates the CPU to one of them.
Is it the same as Short-term scheduler? … Yes
CPU scheduling decisions may take place when a process:
1. Switches from running to waiting state.
2. Switches from running to ready state.
3. Switches from waiting to ready.
4. Terminates.(Own will)
Scheduling Scheme given at 1 and 4 is nonpreemptive (Cooperative).
All other scheduling is preemptive.

7. Preemptive vs Non Preemptive Scheduling
If a process is being executed then it keeps the CPU until one or four conditions of previous slide occur.
MS Windows 3.x which was sort of multitasking system used this method
Not at all efficient.
Preemptive
A process in running state can be brought back to ready state without any of the conditions of previous slide being met.
Can you guess how it is done? 

8. Problems with preemptive
Although better than non-preemptive still suffers from synchronization problems
E.g.
Process P and Q share some data (can be memory location or a file)
P does some calculations changes some of the data but before it finishes its time expires
Q reads the data but is the data valid?

9. Dispatcher
Dispatcher module gives control of the CPU to the process selected by the short-term scheduler; this involves:
switching context
switching to user mode
jumping to the proper location in the user program to restart that program
Dispatch latency – time it takes for the dispatcher to stop one process and start another running.
Should be minimum.

10. Scheduling Criteria Following criteria is kept under consideration while designing a scheduler
CPU utilization – Keep the CPU as busy as possible
Throughput – # of processes that complete their execution per unit time (Given Time).
Turnaround time – Amount of time to execute a particular process (Sum of ready, waiting, running, loading times,I/O)
Waiting time – Amount of time a process has been waiting in the ready queue
Response time – Amount of time it takes from when a request was submitted until the first response is produced, not output (for interactive environment)
Time it takes to start responding
Not the time it takes to output the response

11. Optimization Criteria
So the best CPU Scheduling algorithm is which …
Maximizes CPU utilization
Maximizes throughput
Minimizes turnaround time
Minimizes waiting time
Minimizes response time

12. Outline Scheduling Criteria Scheduling Algorithms Basic Concepts
CPU-I/O Burst Cycle
CPU Scheduler
Preemptive Scheduling
Dispatcher
Scheduling Criteria
Scheduling Algorithms
First-Come, First-Serve Scheduling
Shortest-Job-First Scheduling
Priority Scheduling
Round-Robin Scheduling
Multilevel Queue Scheduling
Multilevel Feedback-Queue Scheduling

13. First-Come, First-Served (FCFS) Scheduling
Process Burst Time
P1 24
P2 3
P3 3
Suppose that the processes arrive in the order: P1 , P2 , P3 The Gantt Chart for the schedule is:
Waiting time for P1 = 0; P2 = 24; P3 = 27
Average waiting time: ( )/3 = 17 P1 P2 P3 24 27 30

14. FCFS Scheduling (Cont.)
Suppose that the processes arrive in the order
P2 , P3 , P1 .
The Gantt chart for the schedule is:
Waiting time for P1 = 6; P2 = 0; P3 = 3
Average waiting time: ( )/3 = 3
Much better than previous case.
CPU bound processes will get and hold the CPU
Convoy effect short process behind long process (Bad CPU utilization) P1 P3 P2 6 3 30

15. Shortest-Job-First (SJR) Scheduling
Associate with each process the length of its next CPU burst. Use these lengths to schedule the process with the shortest time.
Two schemes:
nonpreemptive – once CPU given to the process it cannot be preempted until it completes its CPU burst.
preemptive – if a new process arrives with CPU burst length less than remaining time of current executing process, preempt. This scheme is know as the Shortest-Remaining-Time-First (SRTF).
SJF is optimal – gives minimum average waiting time for a given set of processes.
Shortest-next-cpu-burst algorithm

16. Example of Non-Preemptive SJF
Process Burst Time
P1 6
P2 8
P3 7
P4 3
SJF
Average waiting time = ( )/4= FCFS=10.25 8 P4 P1 P3 P2 3 9 16 24

17. Shortest-Job-First (SJR) Scheduling
Good for long-term Scheduler in batch systems
User specifies process time during job submission
Lower value may mean faster response
Too low a value will cause a time-limit-exceeded error
Difficult to implement at the level of short-term CPU scheduler
Determining Length of Next CPU Burst
Can only predict/ estimate the length of next CPU burst.
Can be done by using the length of previous CPU bursts, using exponential averaging.

18. Examples of Exponential Averaging
 =0
n+1 = n
Recent history does not count.
 =1
n+1 = tn
Only the actual last CPU burst counts.
Since both  and (1 - ) are less than or equal to 1, each successive term has less weight than its predecessor.
n+1 =αtn +(1- α) n
tn: length of the nth CPU burst
n+1 : Our predicted Value
α: weight of recent & past history
0<= α<=1

19. Prediction of the Length of the Next CPU Burst
Initial guess for T(1) = 10 ms Actual 6
Determination of 2 Cycle based on actual (6) and last guess (10)
T(2) = 0.5 x x 10 = 8 ms
Determination of 3 cycle based on actual(4) and last guess (8)
T(3) = 0.5 x x 8 = 6 ms
… Now you can do it 

20. For example: Suppose a process p is given a default expected burst length of 5 time units. When it is run, the actually burst lengths are 10,10,10,1,1,1 (although this information is not known in advance to any algorithm). The prediction of burst times for this process works as follows.
Let e(1) = 5, as a default value.
When process p runs, its first burst actually runs 10 time units, so,
a(1) = 10.
e(2) =0.5 * e(1) * a(1) = * * 10 = 7.5
This is the prediction for the second cpu burst
The actual second cpu burst is 10. So the prediction for the third cpu burst is:
e(3) = 0.5 * e(2) * a(2) = 0.5 * * = 8.75
e(4) = 0.5 * e(3) * a(3) = 0.5 * * 10 = 9.38,
So, we predict that the next burst will be close to 10 (9.38) because the recent bursts have been of length 10. At this point, it happens that the process starts having shorter bursts, with a(4) = 1, so the algorithm gradually adjusts its estimated cpu burst (prediction)
e(5) = 0.5 * e(4) * a(4) = 0.5 * * 1 = 5.19
e(6) = 0.5 * e(5) * a(5) = 0.5 * * 1 = 3.10
e(7) = 0.5 * e(6) * a(6) = 0.5 * * 1 = 2.05

21. Example of Preemptive SJF (Shortest Remaining Time first)
Process Arrival Time Burst Time
P1 0 8
P2 1 4
P3 2 9
P4 3 5
SJF (preemptive)
Average waiting time = 6.5
Non-Preemptive Average waiting time = 6.5 P1 P2 P1 P3 P4 1 5 10 17 26

22. Outline Scheduling Criteria Scheduling Algorithms Basic Concepts
CPU-I/O Burst Cycle
CPU Scheduler
Preemptive Scheduling
Dispatcher
Scheduling Criteria
Scheduling Algorithms
First-Come, First-Serve Scheduling
Shortest-Job-First Scheduling
Priority Scheduling
Round-Robin Scheduling
Multilevel Queue Scheduling
Multilevel Feedback-Queue Scheduling

23. Priority Scheduling
A priority number (integer) is associated with each process
The CPU is allocated to the process with the highest priority (smallest integer  highest priority).
Preemptive
Non-preemptive
SJF is a priority scheduling where priority is the predicted next CPU burst time.
Problem  Starvation – low priority processes may never execute.
Solution  Aging – as time progresses increase the priority of the process.

24. Round Robin (RR)
Each process gets a small unit of CPU time (time quantum), usually milliseconds. After this time has elapsed, the process is preempted and added to the end of the ready queue.
If there are n processes in the ready queue and the time quantum is q, then each process gets 1/n of the CPU time in chunks of at most q time units at once. No process waits more than (n-1)q time units.
Performance
q large  FIFO
q small  q must be large with respect to context switch, otherwise overhead is too high.

25. Example of RR with Time Quantum = 20
Process Burst Time
P1 53
P2 17
P3 68
P4 24
The Gantt chart is:
Typically, higher average turnaround than SJF, but better response. P1 P2 P3 P4 20 37 57 77 97
117
121
134
154
162

26. Time Quantum and Context Switch Time
If context switching time is approx 10 percent of the time quantum, then about 10 percent of the CPU time will be spent in context switching
Most modern systems have time quanta ranging from 10 to 100 milliseconds
Context switch typically takes less than 10 microseconds
Remember: Context switch takes time 

27. Turnaround Time Varies With The Time Quantum
80% of CPU bursts should be shorter than the time quantum
Average Turnaround time doesn’t necessarily improve as the time-quantum size increases)

28. Outline Scheduling Criteria Scheduling Algorithms Basic Concepts
CPU-I/O Burst Cycle
CPU Scheduler
Preemptive Scheduling
Dispatcher
Scheduling Criteria
Scheduling Algorithms
First-Come, First-Serve Scheduling
Shortest-Job-First Scheduling
Priority Scheduling
Round-Robin Scheduling
Multilevel Queue Scheduling
Multilevel Feedback-Queue Scheduling

29. Multilevel Queue
Ready queue is partitioned into separate queues: foreground (interactive) background (batch)
Each queue has its own scheduling algorithm, foreground – RR background – FCFS
Scheduling must be done between the queues.
Fixed priority scheduling; (i.e., serve all from foreground then from background). Possibility of starvation.
Time slice – each queue gets a certain amount of CPU time which it can schedule amongst its processes; i.e., 80% to foreground in RR
20% to background in FCFS

30. Multilevel Queue Scheduling

31. Multilevel Feedback Queue
A process can move between the various queues; aging can be implemented this way.
Multilevel-feedback-queue scheduler defined by the following parameters:
number of queues
scheduling algorithms for each queue
method used to determine when to upgrade a process
method used to determine when to demote a process
method used to determine which queue a process will enter when that process needs service

32. Example of Multilevel Feedback Queue
Consider a case if we have three queues:
Q0 – time quantum 8 milliseconds
Q1 – time quantum 16 milliseconds
Q2 – FCFS
Scheduling
A new job enters queue Q0 which is served FCFS. When it gains CPU, job receives 8 milliseconds. If it does not finish in 8 milliseconds, job is moved to tail of queue Q1.
At Q1 job is again served FCFS and receives 16 additional milliseconds. If it still does not complete, it is preempted and moved to tail of queue Q2.

33. Multilevel Feedback Queues

34. Outline Multi-Processor Scheduling Scheduling Criteria
Basic Concepts
CPU-I/O Burst Cycle
CPU Scheduler
Preemptive Scheduling
Dispatcher
Scheduling Criteria
Scheduling Algorithms
First-Come, First-Serve Scheduling
Shortest-Job-First Scheduling
Priority Scheduling
Round-Robin Scheduling
Multilevel Queue Scheduling
Multilevel Feedback-Queue Scheduling
Multi-Processor Scheduling

35. Multiple-Processor Scheduling
CPU scheduling more complex when multiple CPUs are available.
Consider Homogeneous processors within a multiprocessor system.
Load sharing
Asymmetric multiprocessing – only one processor accesses the system data structures, alleviating the need for data sharing.
SMP: Each processor is self scheduling
May have separate ready queues

36. Multiple-Processor Scheduling –Process Affinity
Cache memory?
The Data most recently accessed populates it
Process migration to another process
Invalidation & Repopulation
Some OS attempt to keep a process running on the same processor –Affinity
Soft Affinity: Attempt to keep a process running on the same processor but not guaranteeing
Hard Affinity: Process cannot migrate to another processor

37. Multiple-Processor Scheduling –Load Balancing
Utilize the full benefits of multi-processors
Load balancing: Distribute the workload evenly across all processors.
Necessary where each processors has its own private queue of eligible processes
Not necessary where processors have common run queue
Modern OS --private queue or common?
Push Migration: move processes from overloaded to idle processors
Pull Migration: Idle processor pulls a waiting process from a busy processor
Any link with Process Affinity?

38. Multiple-Processor Scheduling Symmetric Multithreading
Multiple logical rather than physical processors to run several threads concurrently (HPT)
Create logical processors on the same physical processor—a view of many Processors to OS
Each has its own machine-state registers
Own interrupt handling
Logical
CPU
Physical CPU
System Bus

39. Multiple-Processor Scheduling Symmetric Multithreading
SMT: a feature provided by hardware
Os needn’t be designed differently
Performance gains –If OS is aware.
But why?
**Scheduler**

40. Outline Scheduling Criteria Scheduling Algorithms
Basic Concepts
CPU-I/O Burst Cycle
CPU Scheduler
Preemptive Scheduling
Dispatcher
Scheduling Criteria
Scheduling Algorithms
First-Come, First-Serve Scheduling
Shortest-Job-First Scheduling
Priority Scheduling
Round-Robin Scheduling
Multilevel Queue Scheduling
Multilevel Feedback-Queue Scheduling
Multi-Processor Scheduling
OS Examples –Self Study
Algorithm Evaluation

41. Algorithm Evaluation How do we select the best algorithm?
Defining a criteria
CPU Utilization, response time, throughput
Criteria may include several measures
e.g. Maximize CPU utilization |and| Response time is 1
e.g. Maximize Throughput |and| turnaround time
Analytic Evaluation Method
The algorithm and some system workload are used to produce a formula or number which gives the performance of the algorithm for that workload.
Deterministic modeling
Queuing models
Simulations
Implementation

42. Deterministic Modeling
Predetermined workload –defines performance of each algorithm for that workload. Use of Gantt charts.
Simple and fast
Exact numbers for comparison
Answers apply only for the cases considered.
Performance figures may not be true in general
Suitable: If we are running the same program over and over again. We can easily select an algorithm.
Over a set of examples certain trends can be analyzed, e.g. If all the processes arrive at time 0, the SJF policy will always result in min waiting time
If the Arriving time is different the SJF may not always result in min average waiting time.

43. Deterministic Modeling
Process Arrival Time Burst Time P P P P
Gantt chart
Average waiting time = ( )/4 = 3 P3 P2 4 2 11 P4 5 7 P1 16

44. Queuing Modeling
What if the processes that are run, vary from day to day? --Is deterministic method useful?
The distributions of CPU and I/O bursts can be determined/ approximated/ estimated.
Mathematical formula: probability of a particular CPU burst
Arrival times distribution can also be estimated.
Computer system viewed as a network of queues and servers: ready queue, I/O queue, event queues, CPUs, I/O device controllers, etc. e.g. CPU: ready queue, I/O system :device queue
Input: Arrival and service rates
Output: CPU utilization, average queue length, average waiting time, …

45. Queuing Modeling where Little’s Formula: n = λ* W
n = average queue length
λ = average arrival rate
W = average waiting time in a
queue

46. Average Queue Length(n)
Queuing Modeling
Let the average job arrival rate be 0.5
Algorithm
Average Wait Time
W=tw
Average Queue Length(n)
FCFS
4.6
2.3
SJF
3.6
1.8
SRTF
3.2
1.6
RR (q=1)
7.0
3.5
RR (q=4)
6.0
3.0

47. Queuing Modeling Complicated mathematics
Distributions (uniform, exponential, etc) for the arrival and departure rates can be difficult to work with
Assumptions may not be accurate
Approximation of the real system

48. Simulation To get more accurate evaluation
Workload generated by assuming some distribution and a random number generator, or by collecting data from the actual system.
The distributions can be defined mathematically or empirically.

49. Simulation

50. Expensive: hours of programming and execution time
Simulation
Characteristics
Expensive: hours of programming and execution time
May be erroneous because of the assumptions about distributions

51. Implementation
Even simulation is of limited accuracy
Best way: Code and implement the scheduling algorithm and see
High cost –coding the algorithm
Modify the OS to support it
Reaction of the users to changing OS
Environment changes: if short processes are given high priority then user may break their larger processes into many short ones
For example: Design of an automatic Interactive/ non-interactive process classifier Algorithm