Scheduling and Scheduler's Process and Premptive

Scheduling
 Goal
– To understand the role that scheduling and schedulability analysis
plays in predicting that real-time applications meet their deadlines
 Topics
– Simple process model
– The cyclic executive approach
– Process-based scheduling
– Utilization-based schedulability tests
– Response time analysis for FPS and EDF
– Worst-case execution time
– Sporadic and aperiodic processes
– Process systems with D < T
– Process interactions, blocking and priority ceiling protocols
– An extendible process model
– Dynamic systems and on-line analysis
– Programming priority-based systems

Scheduling
 In general, a scheduling scheme provides two features:
– An algorithm for ordering the use of system resources (in
particular the CPUs)
– A means of predicting the worst-case behaviour of the system
when the scheduling algorithm is applied
 The prediction can then be used to confirm the temporal
requirements of the application

Simple Process Model
 The application is assumed to consist of a fixed set of
processes
 All processes are periodic, with known periods
 The processes are completely independent of each
other
 All system's overheads, context-switching times and so
on are ignored (i.e, assumed to have zero cost)
 All processes have a deadline equal to their period (that
is, each process must complete before it is next
released)
 All processes have a fixed worst-case execution time

Standard Notation
B
C
D
I
J
N
P
R
T
U
a-z
Worst-case blocking time for the process (if applicable)
Worst-case computation time (WCET) of the process
Deadline of the process
The interference time of the process
Release jitter of the process
Number of processes in the system
Priority assigned to the process (if applicable)
Worst-case response time of the process
Minimum time between process releases (process period)
The utilization of each process (equal to C/T)
The name of a process

Cyclic Executives
 One common way of implementing hard real-time
systems is to use a cyclic executive
 Here the design is concurrent but the code is produced
as a collection of procedures
 Procedures are mapped onto a set of minor cycles that
constitute the complete schedule (or major cycle)
 Minor cycle dictates the minimum cycle time
 Major cycle dictates the maximum cycle time
Has the advantage of being fully deterministic

Consider Process Set
Process Period,T Computation Time,C
a 25 10
b 25 8
c 50 5
d 50 4
e 100 2

Cyclic Executive
loop
wait_for_interrupt;
procedure_for_a; procedure_for_b; procedure_for_c;
wait_for_interrupt;
procedure_for_a; procedure_for_b; procedure_for_d;
procedure_for_e;
wait_for_interrupt;
procedure_for_a; procedure_for_b; procedure_for_c;
wait_for_interrupt;
procedure_for_a; procedure_for_b; procedure_for_d;
end loop;

Time-line for Process Set
a b c
Interrupt
a b d
Interrupt
e a b c
Interrupt Interrupt

Properties
 No actual processes exist at run-time; each minor cycle
is just a sequence of procedure calls
 The procedures share a common address space and
can thus pass data between themselves. This data does
not need to be protected (via a semaphore, for example)
because concurrent access is not possible
 All “process” periods must be a multiple of the minor
cycle time

Problems with Cycle Executives
 The difficulty of incorporating processes with long periods;
the major cycle time is the maximum period that can be
accommodated without secondary schedules
 Sporadic activities are difficult (impossible!) to incorporate
 The cyclic executive is difficult to construct and difficult to
maintain — it is a NP-hard problem
 Any “process” with a sizable computation time will need to
be split into a fixed number of fixed sized procedures (this
may cut across the structure of the code from a software
engineering perspective, and hence may be error-prone)
 More flexible scheduling methods are difficult to support
 Determinism is not required, but predictability is

Process-Based Scheduling
 Scheduling approaches
– Fixed-Priority Scheduling (FPS)
– Earliest Deadline First (EDF)
– Value-Based Scheduling (VBS)

Fixed-Priority Scheduling (FPS)
 This is the most widely used approach and is the main
focus of this course
 Each process has a fixed, static, priority which is
computer pre-run-time
 The runnable processes are executed in the order
determined by their priority
 In real-time systems, the “priority” of a process is
derived from its temporal requirements, not its
importance to the correct functioning of the system or its
integrity

Earliest Deadline First (EDF) Scheduling
 The runnable processes are executed in the order
determined by the absolute deadlines of the processes
 The next process to run being the one with the shortest
(nearest) deadline
 Although it is usual to know the relative deadlines of
each process (e.g. 25ms after release), the absolute
deadlines are computed at run time and hence the
scheme is described as dynamic

Value-Based Scheduling (VBS)
 If a system can become overloaded then the use of
simple static priorities or deadlines is not sufficient; a
more adaptive scheme is needed
 This often takes the form of assigning a value to each
process and employing an on-line value-based
scheduling algorithm to decide which process to run
next

Preemption and Non-preemption
 With priority-based scheduling, a high-priority process may
be released during the execution of a lower priority one
 In a preemptive scheme, there will be an immediate switch
to the higher-priority process
 With non-preemption, the lower-priority process will be
allowed to complete before the other executes
 Preemptive schemes enable higher-priority processes to be
more reactive, and hence they are preferred
 Alternative strategies allow a lower priority process to
continue to execute for a bounded time
 These schemes are known as deferred preemption or
cooperative dispatching
 Schemes such as EDF and VBS can also take on a pre-
emptive or non pre-emptive form

FPS and Rate Monotonic Priority Assignment
 Each process is assigned a (unique) priority based on
its period; the shorter the period, the higher the priority
 I.e, for two processes i and j,
 This assignment is optimal in the sense that if any
process set can be scheduled (using pre-emptive
priority-based scheduling) with a fixed-priority
assignment scheme, then the given process set can
also be scheduled with a rate monotonic assignment
scheme
 Note, priority 1 is the lowest (least) priority
P j
Pi
T j
Ti 



Example Priority Assignment
Process Period, T Priority, P
a 25 5
b 60 3
c 42 4
d 105 1
e 75 2

Utilisation-Based Analysis
 For D=T task sets only
 A simple sufficient but not necessary schedulability test
exists
)
1
2
( /
1
1


 

N
N
i i
i
N
T
C
U


 N
U as
69
.
0

Utilization Bounds
N Utilization bound
1 100.0%
2 82.8%
3 78.0%
4 75.7%
5 74.3%
10 71.8%
Approaches 69.3% asymptotically

Process Period ComputationTime Priority Utilization
T C P U
a 50 12 1 0.24
b 40 10 2 0.25
c 30 10 3 0.33
Process Set A
 The combined utilization is 0.82 (or 82%)
 This is above the threshold for three processes (0.78)
and, hence, this process set fails the utilization test

Time-line for Process Set A
0 10 20 30 40 50 60
Time
Process
a
b
c
Process Release Time
Process Completion Time
Deadline Met
Process Completion Time
Deadline Missed
Executing
Preempted

Gantt Chart for Process Set A
c b a c b
0 10 20 30 40 50
Time

T C P U
a 80 32 1 0.400
b 40 5 2 0.125
c 16 4 3 0.250
Process Set B
 The combined utilization is 0.775
 This is below the threshold for three processes (0.78)
and, hence, this process set will meet all its deadlines

T C P U
a 80 40 1 0.50
b 40 10 2 0.25
c 20 5 3 0.25
Process Set C
 This is above the threshold for three processes (0.78)
but the process set will meet all its deadlines

Time-line for Process Set C
0 10 20 30 40 50 60
Time
Process
a
b
c
70 80

Criticism of Utilisation-based Tests
 Not exact
 Not general
 BUT it is O(N)
The test is said to be sufficient but not necessary

1
1



N
i
i
i
T
C
Utilization-based Test for EDF
 Superior to FPS; it can support high utilizations. However
 FPS is easier to implement as priorities are static
 EDF is dynamic and requires a more complex run-time
system which will have higher overhead
 It is easier to incorporate processes without deadlines into
FPS; giving a process an arbitrary deadline is more artificial
 It is easier to incorporate other factors into the notion of
priority than it is into the notion of deadline
 During overload situations
– FPS is more predictable; Low priority process miss their deadlines first
– EDF is unpredictable; a domino effect can occur in which a large
number of processes miss deadlines
A much simpler test

Response-Time Analysis
 Here task i's worst-case response time, R, is calculated
first and then checked (trivially) with its deadline
Where I is the interference from higher priority tasks
i
i
i I
C
R 

R  Di
i

Calculating R
During R, each higher priority task j will execute a number of
times:









j
i
T
R
Releases
of
Number
Total interference is given by:
j
j
i
C
T
R








The ceiling function gives the smallest integer greater than the fractional
number on which it acts. So the ceiling of 1/3 is 1, of 6/5 is 2, and of 6/3 is 2.
 

Response Time Equation
j
i
hp
j
j
i
i
i
C
T
R
C
R  







 )
(
Where hp(i) is the set of tasks with priority higher than task i
Solve by forming a recurrence relationship:
j
i
hp
j
j
n
i
i
n
i
C
T
w
C
w  









)
(
1
The set of values is monotonically non decreasing
When the solution to the equation has been found,
must not be greater that (e.g. 0 or )
1

 n
i
n
i w
w
,..
,...,
,
, 2
1
0 n
i
i
i
i w
w
w
w
0
i
w
i
R i
C

Response Time Algorithm
for i in 1..N loop -- for each process in turn
n := 0
loop
calculate new
if then
exit value found
end if
if then
exit value not found
end if
n := n + 1
end loop
end loop
i
n
i C
w 
:
1

n
i
w
n
i
n
i w
w 
1
n
i
i w
R 
i
n
i T
w 
1

Process Period ComputationTime Priority
T C P
a 7 3 3
b 12 3 2
c 20 5 1
Process Set D
3

a
R
6
6
3
7
6
3
6
3
7
3
3
3
2
1
0



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















b
b
b
b
R
w
w
w

17
3
12
14
3
7
14
5
14
3
12
11
3
7
11
5
11
3
12
5
3
7
5
5
5
3
2
1
0

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
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
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

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







c
c
c
c
w
w
w
w
20
20
3
12
20
3
7
20
5
20
3
12
17
3
7
17
5
5
4

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
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
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

c
c
c
R
w
w

Process Period ComputationTime Priority Response time
T C P R
a 80 40 1 80
b 40 10 2 15
c 20 5 3 5
Revisit: Process Set C
 This was above the ulilization threshold for three
processes (0.78), therefore it failed the test
 The response time analysis shows that the process set
will meet all its deadlines
 RTA is necessary and sufficient

Response Time Analysis
 Is sufficient and necessary
 If the process set passes the test they will meet all their
deadlines; if they fail the test then, at run-time, a
process will miss its deadline (unless the computation
time estimations themselves turn out to be pessimistic)

Worst-Case Execution Time - WCET
 Obtained by either measurement or analysis
 The problem with measurement is that it is difficult to be
sure when the worst case has been observed
 The drawback of analysis is that an effective model of
the processor (including caches, pipelines, memory wait
states and so on) must be available

WCET— Finding C
Most analysis techniques involve two distinct activities.
 The first takes the process and decomposes its code
into a directed graph of basic blocks
 These basic blocks represent straight-line code.
 The second component of the analysis takes the
machine code corresponding to a basic block and uses
the processor model to estimate its worst-case
execution time
 Once the times for all the basic blocks are known, the
directed graph can be collapsed

Need for Semantic Information
for I in 1.. 10 loop
if Cond then
-- basic block of cost 100
else
-- basic block of cost 10
end if;
end loop;
 Simple cost 10*100 (+overhead), say 1005.
 But if Cond only true on 3 occasions then cost is 375

Sporadic Processes
 Sporadics processes have a minimum inter-arrival time
 They also require D<T
 The response time algorithm for fixed priority scheduling
works perfectly for values of D less than T as long as
the stopping criteria becomes
 It also works perfectly well with any priority ordering —
hp(i) always gives the set of higher-priority processes
i
n
i D
W 
1

Hard and Soft Processes
 In many situations the worst-case figures for sporadic
processes are considerably higher than the averages
 Interrupts often arrive in bursts and an abnormal sensor
reading may lead to significant additional computation
 Measuring schedulability with worst-case figures may
lead to very low processor utilizations being observed in
the actual running system

General Guidelines
Rule 1 — all processes should be schedulable using
average execution times and average arrival rates
Rule 2 — all hard real-time processes should be
schedulable using worst-case execution times and
worst-case arrival rates of all processes (including soft)
 A consequent of Rule 1 is that there may be situations in
which it is not possible to meet all current deadlines
 This condition is known as a transient overload
 Rule 2 ensures that no hard real-time process will miss
its deadline
 If Rule 2 gives rise to unacceptably low utilizations for
“normal execution” then action must be taken to reduce
the worst-case execution times (or arrival rates)

Aperiodic Processes
 These do not have minimum inter-arrival times
 Can run aperiodic processes at a priority below the
priorities assigned to hard processes, therefore, they
cannot steal, in a pre-emptive system, resources from
the hard processes
 This does not provide adequate support to soft
processes which will often miss their deadlines
 To improve the situation for soft processes, a server can
be employed.
 Servers protect the processing resources needed by
hard processes but otherwise allow soft processes to
run as soon as possible.
 POSIX supports Sporadic Servers

Process Sets with D < T
 For D = T, Rate Monotonic priority ordering is optimal
 For D < T, Deadline Monotonic priority ordering is
optimal
j
i
j
i
P
P
D
D 



Process Period Deadline ComputationTime Priority Response time
T D C P R
a 20 5 3 4 3
b 15 7 3 3 6
c 10 10 4 2 10
d 20 20 3 1 20
D < T Example Process Set

Proof that DMPO is Optimal
 Deadline monotonic priority ordering (DMPO) is optimal
if any process set, Q, that is schedulable by priority
scheme, W, is also schedulable by DMPO
 The proof of optimality of DMPO involves transforming
the priorities of Q (as assigned by W) until the ordering is
DMPO
 Each step of the transformation will preserve
schedulability

DMPO Proof Continued
 Let i and j be two processes (with adjacent priorities) in Q
such that under W
 Define scheme W’ to be identical to W except that
processes i and j are swapped
Consider the schedulability of Q under W’
 All processes with priorities greater than will be
unaffected by this change to lower-priority processes
 All processes with priorities lower than will be
unaffected; they will all experience the same interference
from i and j
 Process j, which was schedulable under W, now has a
higher priority, suffers less interference, and hence must
be schedulable under W’
j
i
j
i
D
D
P
P 


i
P
j
P

 All that is left is the need to show that process i, which
has had its priority lowered, is still schedulable
 Under W
 Hence process j only interferes once during the
execution of i
 It follows that:
 It can be concluded that process i is schedulable after
the switch
 Priority scheme W’ can now be transformed to W" by
choosing two more processes that are in the wrong
order for DMP and switching them
i
i
i
j
j
j
T
D
and
D
D
D
R 

 ,
i
j
j
i
D
D
R
R 


'
DMPO Proof Continued

Process Interactions and Blocking
 If a process is suspended waiting for a lower-priority
process to complete some required computation then
the priority model is, in some sense, being undermined
 It is said to suffer priority inversion
 If a process is waiting for a lower-priority process, it is
said to be blocked

Priority Inversion
 To illustrate an extreme example of priority inversion,
consider the executions of four periodic processes: a, b, c
and d; and two resources: Q and V
Process Priority Execution Sequence Release Time
a 1 EQQQQE 0
b 2 EE 2
c 3 EVVE 2
d 4 EEQVE 4

Example of Priority Inversion
Process
a
b
c
d
0 2 4 6 8 10 12 14 16 18
Executing
Executing with Q locked
Preempted
Executing with V locked
Blocked

Priority Inheritance
 If process p is blocking process q, then q runs with p's
priority
a
b
c
d
0 2 4 6 8 10 12 14 16 18
Process

Calculating Blocking
 If a process has m critical sections that can lead to it
being blocked then the maximum number of times it can
be blocked is m
 If B is the maximum blocking time and K is the number
of critical sections, the process i has an upper bound
on its blocking given by:



K
k
i k
C
i
k
usage
B
1
)
(
)
,
(

Response Time and Blocking
i
i
i
i I
B
C
R 


j
i
hp
j j
i
i
i
i C
T
R
B
C
R 
 










)
(
j
i
hp
j
j
n
i
i
i
n
i
C
T
w
B
C
w  

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


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)
(
1

Priority Ceiling Protocols
Two forms
 Original ceiling priority protocol
 Immediate ceiling priority protocol

On a Single Processor
 A high-priority process can be blocked at most once
during its execution by lower-priority processes
 Deadlocks are prevented
 Transitive blocking is prevented
 Mutual exclusive access to resources is ensured (by the
protocol itself

OCPP
 Each process has a static default priority assigned
(perhaps by the deadline monotonic scheme)
 Each resource has a static ceiling value defined, this is
the maximum priority of the processes that use it
 A process has a dynamic priority that is the maximum of
its own static priority and any it inherits due to it blocking
higher-priority processes.
 A process can only lock a resource if its dynamic priority
is higher than the ceiling of any currently locked
resource (excluding any that it has already locked itself)
)
(
)
,
(
max
1
k
C
i
k
usage
B
k
k
i



OCPP Inheritance
a
b
c
d
0 2 4 6 8 10 12 14 16 18
Process

ICPP
 Each process has a static default priority assigned
(perhaps by the deadline monotonic scheme).
 Each resource has a static ceiling value defined, this is
the maximum priority of the processes that use it.
 A process has a dynamic priority that is the maximum of
its own static priority and the ceiling values of any
resources it has locked
 As a consequence, a process will only suffer a block at
the very beginning of its execution
 Once the process starts actually executing, all the
resources it needs must be free; if they were not, then
some process would have an equal or higher priority
and the process's execution would be postponed

ICPP Inheritance
a
b
c
d
0 2 4 6 8 10 12 14 16 18
Process

OCPP versus ICPP
 Although the worst-case behaviour of the two ceiling
schemes is identical (from a scheduling view point),
there are some points of difference:
– ICCP is easier to implement than the original (OCPP) as
blocking relationships need not be monitored
– ICPP leads to less context switches as blocking is prior to first
execution
– ICPP requires more priority movements as this happens with all
resource usage
– OCPP changes priority only if an actual block has occurred
 Note that ICPP is called Priority Protect Protocol in
POSIX and Priority Ceiling Emulation in Real-Time Java

An Extendible Process Model
So far:
 Deadlines can be less than period (D<T)
 Sporadic and aperiodic processes, as well as periodic
processes, can be supported
 Process interactions are possible, with the resulting
blocking being factored into the response time
equations

Extensions
 Cooperative Scheduling
 Release Jitter
 Arbitrary Deadlines
 Fault Tolerance
 Offsets
 Optimal Priority Assignment

Cooperative Scheduling
 True preemptive behaviour is not always acceptable for
safety-critical systems
 Cooperative or deferred preemption splits processes
into slots
 Mutual exclusion is via non-preemption
 The use of deferred preemption has two important
advantages
– It increases the schedulability of the system, and it can lead to
lower values of C
– With deferred preemption, no interference can occur during the
last slot of execution.

Cooperative Scheduling
 Let the execution time of the final block be
 When this converges that is, , the response
time is given by:
i
F
j
i
hp
j
j
n
i
i
i
MAX
n
i
C
T
w
F
C
B
w  


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
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



)
(
1
1

 n
i
n
i w
w
i
n
i
i F
w
R 


Release Jitter
 A key issue for distributed systems
 Consider the release of a sporadic process on a
different processor by a periodic process, l, with a
period of 20
Time
l
t t+15 t+20
First execution l finishes at R
Second execution of l finishes after C
Release sporadic process at time 0, 5, 25, 45

Release Jitter
 Sporadic is released at 0, T-J, 2T-J, 3T-J
 Examination of the derivation of the schedulability
equation implies that process i will suffer
– one interference from process s if
– two interfernces if
– three interference if
 This can be represented in the response time equations
 If response time is to be measured relative to the real
release time then the jitter value must be added
)
,
0
[ J
T
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Arbitrary Deadlines
 To cater for situations where D (and hence potentially R)
> T
 The number of releases is bounded by the lowest value
of q for which the following relation is true:
 The worst-case response time is then the maximum
value found for each q:
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Arbitrary Deadlines
 When formulation is combined with the effect of release
jitter, two alterations to the above analysis must be
made
 First, the interference factor must be increased if any
higher priority processes suffers release jitter:
 The other change involves the process itself. If it can
suffer release jitter then two consecutive windows could
overlap if response time plus jitter is greater than period.
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Fault Tolerance
 Fault tolerance via either forward or backward error
recovery always results in extra computation
 This could be an exception handler or a recovery block.
 In a real-time fault tolerant system, deadlines should still
be met even when a certain level of faults occur
 This level of fault tolerance is know as the fault model
 If the extra computation time that results from an error in
process i is
 where hep(i) is set of processes with priority equal to
or higher than i
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Fault Tolerance
 If F is the number of faults allows
 If there is a minimum arrival interval
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Offsets
 So far assumed all processes share a common release
time (critical instant)
Process T D C R
a 8 5 4 4
b 20 10 4 8
c 20 12 4 16
 With offsets
Process T D C O R
a 8 5 4 0 4
b 20 10 4 0 8
c 20 12 4 10 8
Arbitrary offsets are
not amenable to
analysis

Non-Optimal Analysis
 In most realistic systems, process periods are not
arbitrary but are likely to be related to one another
 As in the example just illustrated, two processes have a
common period. In these situations it is ease to give one
an offset (of T/2) and to analyse the resulting system
using a transformation technique that removes the offset
— and, hence, critical instant analysis applies.
 In the example, processes b and c (having the offset of
10) are replaced by a single notional process with
period 10, computation time 4, deadline 10 but no offset

Non-Optimal Analysis
 This notional process has two important properties.
– If it is schedulable (when sharing a critical instant with all other
processes) then the two real process will meet their deadlines
when one is given the half period offset
– If all lower priority processes are schedulable when suffering
interference from the notional process (and all other high-
priority processes) then they will remain schedulable when the
notional process is replaced by the two real process (one with
the offset).
 These properties follow from the observation that the
notional process always uses more (or equal) CPU time
than the two real process
Process T D C O R
a 8 5 4 0 4
n 10 10 4 0 8

Notional Process Parameters
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D
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Can be extended to more than two processes

Priority Assignment
Theorem
 If process p is assigned the lowest priority and is
feasible then, if a feasible priority ordering exists for the
complete process set, an ordering exists with process p
assigned the lowest priority
procedure Assign_Pri (Set : in out Process_Set; N : Natural;
Ok : out Boolean) is
begin
for K in 1..N loop
for Next in K..N loop
Swap(Set, K, Next);
Process_Test(Set, K, Ok);
exit when Ok;
end loop;
exit when not Ok; -- failed to find a schedulable process
end loop;
end Assign_Pri;

Dynamic Systems and Online Analysis
 There are dynamic soft real-time applications in which
arrival patterns and computation times are not known a
priori
 Although some level of off-line analysis may still be
applicable, this can no longer be complete and hence
some form of on-line analysis is required
 The main task of an on-line scheduling scheme is to
manage any overload that is likely to occur due to the
dynamics of the system's environment
 EDF is a dynamic scheduling scheme that is an optimal
 During transient overloads EDF performs very badly. It is
possible to get a cascade effect in which each process
misses its deadline but uses sufficient resources to result
in the next process also missing its deadline.

Admission Schemes
 To counter this detrimental domino effect many on-line
schemes have two mechanisms:
– an admissions control module that limits the number of
processes that are allowed to compete for the processors, and
– an EDF dispatching routine for those processes that are
admitted
 An ideal admissions algorithm prevents the processors
getting overloaded so that the EDF routine works
effectively

Values
 If some processes are to be admitted, whilst others
rejected, the relative importance of each process must
be known
 This is usually achieved by assigning value
 Values can be classified
– Static: the process always has the same value whenever it is
released.
– Dynamic: the process's value can only be computed at the time
the process is released (because it is dependent on either
environmental factors or the current state of the system)
– Adaptive: here the dynamic nature of the system is such that the
value of the process will change during its execution
 To assign static values requires the domain specialists
to articulate their understanding of the desirable
behaviour of the system

Programming Priority-Based Systems
 Ada
 POSIX
 Real-Time Java

Ada: Real-Time Annex
 Ada 95 has a flexible model:
– base and active priorities
– priority ceiling locking
– various dispatching policies using active priority
– dynamic priorities
subtype Any_Priority is Integer
range Implementation-Defined;
subtype Priority is Any_Priority range
Any_Priority'First .. Implementation-Defined;
subtype Interrupt_Priority is Any_Priority range
Priority'Last + 1 .. Any_Priority'Last;
Default_Priority : constant Priority :=
(Priority'First + Priority'Last)/2;
An implementation must support a range of Priority of at
least 30 and at least one distinct Interrupt_Priority

Assigning Base Priorities
 Using a pragma
task Controller is
pragma Priority(10);
end Controller;
task type Servers(Pri : System.Priority) is
-- each instance of the task can have a
-- different priority
entry Service1(...);
entry Service2(...);
pragma Priority(Pri);
end Servers;

Priority Ceiling Locking
 Protected objects need to maintain the consistency of
their data
 Mutual exclusion can be guaranteed by use of the
priority model
 Each protected object is assigned a ceiling priority
which is greater than or equal to the highest priority of
any of its calling tasks
 When a task calls a protected operation, its priority is
immediately raised to that of the protected object
 If a task wishing to enter a protected operation is
running then the protected object cannot be already
occupied

Ceiling Locking
 Each protected object is assigned a priority using a
pragma
 If the pragma is missing, Priority'Last is assumed
 Program_Error is raised if the calling task's active
priority is greater than the ceiling
 If an interrupt handler is attached to a protected
operation and the wrong ceiling priority has been set,
then the program becomes erroneous
 With ceiling locking, an effective implementation will use
the thread of the calling task to execute not only the
protected operation but also to execute the code of any
other tasks that are released as a result of the call

Example of Ceiling Priority
protected Gate_Control is
pragma Priority(28);
entry Stop_And_Close;
procedure Open;
private
Gate : Boolean := False;
end Gate_Control;
protected body Gate_Control is
entry Stop_And_Close
when Gate is
begin
Gate := False;
end;
procedure Open is
begin
Gate := True;
end;
end Gate_Control;

Example
 Assume task T, priority 20, calls Stop_And_Close and
is blocked. Later task S, priority 27, calls Open. The
thread executing S will undertake the following
operations:
– the code of Open for S
– evaluate the barrier on the entry and note that T can now
proceed
– the code Stop_And_Close for T
– evaluate the barrier again
– continue with the execution of S after its call on the protected
object
 There is no context switch

Active Priorities
 A task entering a protected operation has its priority
raised
 A task’s active priority might also change during:
– task activation  a task inherits the active priority of the parent
task which created it (to avoid priority inversion)
– during a rendezvous  the task executing a rendezvous will
inherit the active priority of the caller if it is greater than its
current active priority
– Note: no inheritance when waiting for task termination

Dispatching
 The order of dispatching is determined by the tasks'
active priorities
 Default is preemptive priority based
 Not defined exactly what this means on a multi-
processor system
 One policy defined by annex:
FIFO_Within_Priority
 When a task becomes runnable it is placed at the back
on the run queue for its priority; when it is preempted, it
is placed at the front

Entry Queue Policies
 A programmer may choose the queuing policy for a
task's entry queue and the select statement
 Two predefined policies: FIFO_Queuing (default) and
Priority_Queuing
 With Priority_Queuing and the select statement, an
alternative that is open and has the highest priority task
queued (of all open alternatives) is chosen
 If there are two open with equal priority tasks, the one
which appears textually first in the program is chosen
 Tasks are queued in active priority order, if active priority
changes then no requeuing takes place; if the base
priority changes, the task is removed and requeued

Dynamic Priorities
 Some applications require the base priority of a task to
change dynamically: e.g., mode changes, or to
implement dynamic scheduling schemes such as
earliest deadline scheduling

Package Specification
with Ada.Task_Identification; use Ada;
package Ada.Dynamic_Priorities is
procedure Set_Priority(Priority : System.Any_Priority;
T : Task_Identification.Task_Id :=
Task_Identification.Current_Task);
function Get_Priority(T : T_Identification.Task_Id
:= Task_Identification.Current_Task)
return System.Any_Priority;
-- raise Tasking_Error if task has terminated
-- Both raise Program_Error if a Null_Task_Id is passed
private
-- not specified by the language
end Ada.Dynamic_Priorities;

Dynamic Priorities
 The effect of a change of base priorities should be as
soon as practical but not during an abort deferred
operation and no later than the next abort completion
point
 Changing a task's base priority can affect its active
priority and have an impact on dispatching and queuing

POSIX
 POSIX supports priority-based scheduling, and has options
to support priority inheritance and ceiling protocols
 Priorities may be set dynamically
 Within the priority-based facilities, there are four policies:
– FIFO: a process/thread runs until it completes or it is blocked
– Round-Robin: a process/thread runs until it completes or it is blocked
or its time quantum has expired
– Sporadic Server: a process/thread runs as a sporadic server
– OTHER: an implementation-defined
 For each policy, there is a minimum range of priorities that
must be supported; 32 for FIFO and round-robin
 The scheduling policy can be set on a per process and a per
thread basis

POSIX
 Threads may be created with a system contention
option, in which case they compete with other system
threads according to their policy and priority
 Alternatively, threads can be created with a process
contention option where they must compete with other
threads (created with a process contention) in the
parent process
– It is unspecified how such threads are scheduled relative to
threads in other processes or to threads with global contention
 A specific implementation must decide which to support

Sporadic Server
 A sporadic server assigns a limited amount of CPU
capacity to handle events, has a replenishment period,
a budget, and two priorities
 The server runs at a high priority when it has some
budget left and a low one when its budget is exhausted
 When a server runs at the high priority, the amount of
execution time it consumes is subtracted from its budget
 The amount of budget consumed is replenished at the
time the server was activated plus the replenishment
period
 When its budget reaches zero, the server's priority is set
to the low value

Other Facilities
POSIX allows:
 priority inheritance to be associated with mutexes
(priority protected protocol= ICPP)
 message queues to be priority ordered
 functions for dynamically getting and setting a thread's
priority
 threads to indicate whether their attributes should be
inherited by any child thread they create

RT Java Threads and Scheduling
 There are two entities in Real-Time Java which can be
scheduled:
– RealtimeThreads (and NoHeapRealtimeThread)
– AsynEventHandler (and BoundAyncEventHandler)
 Objects which are to be scheduled must
– implement the Schedulable interface
– specify their
• SchedulingParameters
• ReleaseParameters
• MemoryParameters

Real-Time Java
 Real-Time Java implementations are required to support at
least 28 real-time priority levels
 As with Ada and POSIX, the larger the integer value, the
higher the priority
 Non real-time threads are given priority levels below the
minimum real-time priority
 Note, scheduling parameters are bound to threads at
thread creation time; if the parameter objects are changed,
they have an immediate impact on the associated thread
 Like Ada and Real-Time POSIX, Real-Time Java supports
a pre-emptive priority-based dispatching policy
 Unlike Ada and RT POSIX, RT Java does not require a
preempted thread to be placed at the head of the run
queue associated with its priority level

The Schedulable Interface
public interface Schedulable extends java.lang.Runnable
{
public void addToFeasibility();
public void removeFromFeasibility();
public MemoryParameters getMemoryParameters();
public void setMemoryParameters(MemoryParameters memory);
public ReleaseParameters getReleaseParameters();
public void setReleaseParameters(ReleaseParameters release);
public SchedulingParameters getSchedulingParameters();
public void setSchedulingParameters(
SchedulingParameters scheduling);
public Scheduler getScheduler();
public void setScheduler(Scheduler scheduler);
}

Scheduling Parameters
public abstract class SchedulingParameters
{ public SchedulingParameters(); }
public class PriorityParameters extends SchedulingParameters
{
public PriorityParameters(int priority);
public int getPriority(); // at least 28 priority levels
public void setPriority(int priority) throws
IllegalArgumentException;
...
}
public class ImportanceParameters extends PriorityParameters
{
public ImportanceParameters(int priority, int importance);
public int getImportance();
public void setImportance(int importance);
...
}

RT Java: Scheduler
 Real-Time Java supports a high-level scheduler whose
goals are:
– to decide whether to admit new schedulable objects according
to the resources available and a feasibility algorithm, and
– to set the priority of the schedulable objects according to the
priority assignment algorithm associated with the feasibility
algorithm
 Hence, whilst Ada and Real-Time POSIX focus on static
off-line schedulability analysis, Real-Time Java
addresses more dynamic systems with the potential for
on-line analysis

The Scheduler
public abstract class Scheduler
{
public Scheduler();
protected abstract void addToFeasibility(Schedulable s);
protected abstract void removeFromFeasibility(Schedulable s);
public abstract boolean isFeasible();
// checks the current set of schedulable objects
public boolean changeIfFeasible(Schedulable schedulable,
ReleaseParameters release, MemoryParameters memory);
public static Scheduler getDefaultScheduler();
public static void setDefaultScheduler(Scheduler scheduler);
public abstract java.lang.String getPolicyName();
}

The Scheduler
 The Scheduler is an abstract class
 The isFeasible method considers only the set of
schedulable objects that have been added to its
feasibility list (via the addToFeasibility and
removeFromFeasibility methods)
 The method changeIfFeasible checks to see if its
set of objects is still feasible if the given object has its
release and memory parameters changed
 If it is, the parameters are changed
 Static methods allow the default scheduler to be queried
or set
 RT Java does not require an implementation to provide
an on-line feasibility algorithm

The Priority Scheduler
class PriorityScheduler extends Scheduler
{
public PriorityScheduler()
protected void addToFeasibility(Schedulable s);
...
public void fireSchedulable(Schedulable schedulable);
public int getMaxPriority();
public int getMinPriority();
public int getNormPriority();
public static PriorityScheduler instance();
...
}
Standard preemptive priority-based scheduling

Other Facilities
 Priority inheritance and ICCP (called priority ceiling
emulation)
 Support for aperiodic threads in the form of processing
groups; a group of aperiodic threads can be linked
together and assigned characteristics which aid the
feasibility analysis

Summary
 A scheduling scheme defines an algorithm for resource
sharing and a means of predicting the worst-case
behaviour of an application when that form of resource
sharing is used.
 With a cyclic executive, the application code must be
packed into a fixed number of minor cycles such that the
cyclic execution of the sequence of minor cycles (the
major cycle) will enable all system deadlines to be met
 The cyclic executive approach has major drawbacks many
of which are solved by priority-based systems
 Simple utilization-based schedulability tests are not exact

Summary
 Response time analysis is flexible and caters for:
– Periodic and sporadic processes
– Blocking caused by IPC
– Cooperative scheduling
– Arbitrary deadlines
– Release jitter
– Fault tolerance
– Offsets
 Ada, RT POSIX and RT Java support preemptive
priority-based scheduling
 Ada and RT POSIX focus on static off-line schedulability
analysis, RT Java addresses more dynamic systems
with the potential for on-line analysis

Scheduling and Scheduler's Process and Premptive

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