Real-Time Scheduling

Real-Time Scheduling
CIS700
Insup Lee
By
SATHISHKUMAR G
(sathishsak111@gmail.com)

Outline
• Real-time systems
• Real-time scheduling algorithms
– Fixed-priority algorithm (RM)
– Dynamic-priority algorithm (EDF)

Real-Time Systems
• Definition
– Systems whose correctness depends on their temporal
aspects as well as their functional aspects
• Performance measure
– Timeliness on timing constraints (deadlines)
– Speed/average case performance are less significant.
• Key property
– Predictability on timing constraints

Real-Time System Example
• Digital control systems
– periodically performs the following job:
senses the system status and
actuates the system according to its current status
Control-Law
Computation
Sensor
Actuator

Real-Time System Example
Multimedia
• Multimedia applications
– periodically performs the following job:
reads, decompresses, and displays video and audio
streams

Fundamental Real-Time Issue
• To specify the timing constraints of real-time
systems
• To achieve predictability on satisfying their timing
constraints, possibly, with the existence of other
real-time systems

Scheduling Framework Example
CPU
OS Scheduler
Digital Controller Multimedia

Real-Time Workload
• Job (unit of work)
– a computation, a file read, a message transmission, etc
• Attributes
– Resources required to make progress
– Timing parameters
Released
Absolute
deadline
Relative deadline
Execution time

Real-Time Task
• Task : a sequence of similar jobs
– Periodic task (p,e)
• Its jobs repeat regularly
• Period p = inter-release time (0 < p)
• Execution time e = maximum execution time (0 < e < p)
• Utilization U = e/p
5 10 150

Deadlines: Hard vs. Soft
• Hard deadline
– Disastrous or very serious consequences may occur if
the deadline is missed
– Validation is essential : can all the deadlines be met,
even under worst-case scenario?
– Deterministic guarantees
• Soft deadline
– Ideally, the deadline should be met for maximum
performance. The performance degrades in case of
deadline misses.
– Best effort approaches / statistical guarantees

Schedulability
• Property indicating whether a real-time system (a set
of real-time tasks) can meet their deadlines
(4,1)
(5,2)
(7,2)

Real-Time Scheduling
• Determines the order of real-time task executions
• Static-priority scheduling
• Dynamic-priority scheduling
(4,1)
(5,2)
(7,2)
5
5
10
10 15
15

RM (Rate Monotonic)
• Optimal static-priority scheduling
• It assigns priority according to period
• A task with a shorter period has a higher priority
• Executes a job with the shortest period
(4,1)
(5,2)
(7,2)
5
5
10
10 15
15
T1
T2
T3

RM (Rate Monotonic)
(4,1)
(5,2)
(7,2)
5
5
10
10 15
15
T1
T2
T3

RM (Rate Monotonic)
(4,1)
(5,2)
(7,2)
Deadline Miss !
5
5
10
10 15
15
T1
T2
T3

Response Time
• Response time
– Duration from released time to finish time
(4,1)
(5,2)
(10,2)
5
5
10
10 15
15
T1
T2
T3

Response Time
• Response time
– Duration from released time to finish time
(4,1)
(5,2)
(10,2)
Response Time
5
5
10
10 15
15
T1
T2
T3

Response Time
• Response Time (ri) [Audsley et al., 1993]
• HP(Ti) : a set of higher-priority tasks than Ti
(4,1)
(5,2)
(10,2)
k
THPT k
i
ii e
p
r
er
ik
⋅





+= ∑∈ )(
5
5
10
10
T1
T2
T3

RM - Schedulability Analysis
• Real-time system is schedulable under RM
if and only if ri ≤ pi for all task Ti(pi,ei)
Joseph & Pandya,
“Finding response times in a real-time system”,
The Computer Journal, 1986.

RM – Utilization Bound
• Real-time system is schedulable under RM if
∑Ui ≤ n (21/n
-1)
Liu & Layland,
“Scheduling algorithms for multi-programming in a
hard-real-time environment”, Journal of ACM, 1973.

∑Ui ≤ n (21/n
-1)
• Example: T1(4,1), T2(5,1), T3(10,1),
∑Ui = 1/4 + 1/5 + 1/10
= 0.55
3 (21/3
-1) ≈ 0.78
Thus, {T1, T2, T3} is schedulable under RM.

RM Utilization Bounds
0.5
0.6
0.7
0.8
0.9
1
1.1
1 4 16 64 256 1024 4096
The Number of Tasks
Utilization
∑Ui ≤ n (21/n
-1)

EDF (Earliest Deadline First)
• Optimal dynamic priority scheduling
• A task with a shorter deadline has a higher priority
• Executes a job with the earliest deadline
(4,1)
(5,2)
(7,2)
5
5
10
10 15
15
T1
T2
T3

• Executes a job with the earliest deadline
(4,1)
(5,2)
(7,2)
5
5
10
10 15
15
T1
T2
T3

• Optimal scheduling algorithm
– if there is a schedule for a set of real-time tasks,
EDF can schedule it.
(4,1)
(5,2)
(7,2)
5
5
10
10 15
15
T1
T2
T3

Processor Demand Bound
• Demand Bound Function : dbf(t)
– the maximum processor demand by workload over any
interval of length t
(4,1)
(5,2)
(7,2)
t
5
5
10
10 15
15
T1
T2
T3

EDF - Schedulability Analysis
• Real-time system is schedulable under EDF
if and only if dbf(t) ≤ t for all interval t
Baruah et al.
“Algorithms and complexity concerning the preemptive
scheduling of periodic, real-time tasks on one
processor”, Journal of Real-Time Systems, 1990.
• Demand Bound Function : dbf(t)
– the maximum processor demand by workload over any
interval of length t

EDF – Utilization Bound
• Real-time system is schedulable under EDF if and only
if
∑Ui ≤ 1
Liu & Layland,
“Scheduling algorithms for multi-programming in a
hard-real-time environment”, Journal of ACM, 1973.

• Domino effect during overload conditions
– Example: T1(4,3), T2(5,3), T3(6,3), T4(7,3)
EDF – Overload Conditions
T1
50 7
T2 T3 T4
3 6
Deadline Miss !
T1
50 7
T3
3 6
Better schedules :
T1
50 7
T4
3 6

RM vs. EDF
• Rate Monotonic
– Simpler implementation, even in systems without explicit
support for timing constraints (periods, deadlines)
– Predictability for the highest priority tasks
• EDF
– Full processor utilization
– Misbehavior during overload conditions
• For more details: Buttazzo, “Rate monotonic vs. EDF:
Judgement Day”, EMSOFT 2003.

Real-Time Scheduling

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