Embedded Systems Exercise 3 - HS 20204./6.11.2020Stefan Draskovic

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 1

Exercise structure

• Goal of today’s exercise:– Scheduling Aperiodic Tasks

• Agenda:– Wednesday 16:15 - 17:00 Introduction and solving a sample question (recorded)– Friday 16:15 - 17:00 Solutions (recorded)

• Available assistants:– Stefan Drašković– Luca Rufer

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 2

Exercise structure

• Interactions:– Exercise Zoom: Questions can be asked throughout the exercise in this room by

raising your hand. Please feel free to write in the chat in case we oversee yourquestion.

– Help Zoom: Student assistants are available after the session for questions and1-on-1 meetings.

– Matrix Chatroom: Questions that are relevant for everyone can be asked in theMatrix chatroom where the responsible assistants can answer as quickly as possible.

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Content of today’s exercise

Scheduling Aperiodic Tasks: EDD, LDF, EDF, EDF*

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 4

Definitions Recap

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Overview

• Last time: Cyclic Executive Scheduling– easy to implement– hard to derive Schedule– not so easy to analyze

• Today: EDD, EDF, LDF, EDF*– impractical or impossible to implement– easy to derive optimal schedule– easy to analyze

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Scheduling aperiodic tasks with realtime constraints

Some known algorithms:

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Earliest Due Deadline (EDD)

• Optimization goal:– minimize the maximum lateness

• Assumptions on the task set:– independent tasks– synchronous arrival times

• EDD is non preemptive

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Earliest Due Deadline (EDD)

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Task 1: Solution (and Clicker Question)

The task is schedulable

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 10

Latest Deadline First (LDF)

• Optimization goal:– minimize the maximum lateness

• Assumptions on the task set:– tasks with precedence constraints– synchronous arrival times

• LDF is non preemptive

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Latest Deadline First (LDF)

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 12

Latest Deadline First (LDF)

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 13

Task 2: Solution

J1 J2

J3

J4

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J8

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 14

Task 2: Solution

J1 J2

J3

J4

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J8

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 15

Task 2: Solution

J1 J2

J3

J4

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J8

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 16

Task 2: Solution

J1 J2

J3

J4

J5

J6

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J8

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 17

Task 2: Solution

J1 J2

J3

J4

J5

J6

J7

J8

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 18

Task 2: Solution

J1 J2

J3

J4

J5

J6

J7

J8

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Task 2: Solution

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 20

Earliest Deadline First (EDF)

• Optimization goal:– minimize the maximum lateness

• Assumptions on the task set:– independent tasks– arbitrary arrival times (dynamic arrivals)

• EDF is preemptive

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Earliest Deadline First (EDF)

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Earliest Deadline First (EDF)Guarantee:• Worst case finishing time of task i : fi = t +

∑ik=1 Ck (t)

• EDF guarantee condition: ∀t = 1, ..., n t +∑i

k=1 Ck (t) ≤ di• Algorithm:

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Task 3: Solution

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Task 3: Solution

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Earliest Deadline First - Star (EDF*)

• Optimization goal:– minimize the maximum lateness

• Assumptions on the task set:– tasks with precedence relations– arbitrary arrival times (dynamic arrivals)

• EDF* is preemptive

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Earliest Deadline First - Star (EDF*)

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 27

Earliest Deadline First - Star (EDF*)

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 28

Earliest Deadline First - Star (EDF*)

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Task 4: Solution

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Task 4: Solution

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Task 5: Solution

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Task 5: Solution

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Task 5: Solution

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Task 5: Solution

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Questions?

Stefan DraskovicETZ G81+41 44 63 27033stefan.draskovic@tik.ee.ethz.ch

Institut für Technische Informatikund KommunikationsnetzeComputer Engineering andNetworks Laboratory Stefan Draskovic 4./6.11.2020 36