Object-Oriented Design and Implementation of the OE-Scheduler in Real-time Environments

Ilhyun Lee Cherry K. Owen Haesun K. Lee

The University of Texas of the Permian Basin

Outline

Introduction Motivation and Objective UML Diagram for OE-Scheduler Implementation for OE-Scheduler Conclusion Future Work

Introduction

Real-Time System Periodic Task Model Object Oriented Design OE-Scheduler

Real-Time System

Computing system with a set of execution models that have timing constraints

Hard Real-Time System Soft Real-Time System

Hard Real-Time System

System Value Time

Start Time Deadline

Soft Real-Time System

System Value Time Start Time Deadline

Periodic Task Model

A sequence of the same type of event occurring at constant intervals

Task : scheduling entity Event : recurring instance of scheduling entity

Event 1 Event 2 Event 3 Event 4 Time constant interval

Object Oriented Design

Problems are modeled using objects The object-oriented approach has the

potential to reduce complexity, improve flexibility, and reduce expenses

Object reusability

OE-Scheduler

Scheduler that generates a schedule of periodic tasks by the principle of eliminating unnecessary context switches under the rate monotonic algorithm

Guarantee the hard deadlines of an arbitrary number of periodic tasks in hard real-time environments

Object-oriented design

Motivation

Future real-time system will run in highly dynamic behavior environments

Current our procedural scheduling algorithms cannot be efficiently applied to future real-time system

This observation motivated us to work on developing an object-oriented view-point of the OE-scheduler in hard real-periodic environments

Objective

Developing an object-oriented view-point of the OE-scheduler that generates a schedule of periodic tasks by the principle of eliminating unnecessary context switches under the rate monotonic algorithm in hard real-periodic environments

UML Diagram for OE-Scheduler

Class Diagram for OE-Scheduler Sequence Diagram to Produce a OE-

Schedule

Class Diagram for OE-Scheduler

+Methods()

-Attributes

Periodic Task

+Methods()

-Attributes

RM Scheduler

+Methods()

-Attributes

OE-Scheduler

+Methods()

-Attributes

OE-Schedule

+Methods()

-Attributes

CRP-Slack

1

1..*

1 11..* 1

Sequence Diagram to Produce a OE-Schedule

Peridoc Task OE_Scheduler RM_Scheduler OE-Schedule

Request scheduling

Request CRP and Slack

Notify

Produce OE-Schedule

CRP-Slack

Notify

Request RM Information

Implementation for OE-Scheduler

Scheduling algorithm for OE-Scheduler Test result of the object-oriented OE-

Scheduler Comparison table

Scheduling Algorithm for OE-Scheduler

Step1. If Pij {i: 1..n, j: 0..n} arrives the system at the

same time, pick the highest priority event of Pij {i: 1..n, j: 0..n}. Determine the Current Request

Period (CRP) of the selected event.

Scheduling Algorithm for OE-Scheduler

Step2. If the CRP of the selected event is odd, then go to Step3. Otherwise, if the CRP of the selected event is even, then calculate the Slack, the maximum amount of time that a scheduler can delay running the task without missing its current deadline, for the selected event. Delay the execution of the selected event until the Slack of the selected event becomes empty. When the Slack of the selected event becomes empty, schedule the selected event under the Rate Monotonic Algorithm. Go to Step4

Scheduling Algorithm for OE-Scheduler

Step3. Immediately schedule the selected event under the Rate Monotonic Algorithm.

Step4. Go to Step1 until the final event is processed

Scheduling Algorithm for OE-Scheduler

Reference [1] Haesun Kang Lee, Ilhyun Lee, and Martha Evens “Scheduling Periodic Tasks with Reduced Context Switches,” Proceedings of the ACIS 1st International Conference on Software Engineering Applied to Networking & parallel/Distributed Computing (SNPD ’00), pp. 209-215, May 18-21, 2000, Champagne-Ardenne, France.

Test Result of the Object-oriented OE-Scheduler

Record structure of the periodic task Workload file: OE-schedule.txt Menu-based user interface The scheduling points with CRP Schedule for 4 periodic task by OE-

Scheduler

Record Structure of the Periodic Task Workload

<PID, PE. P, AT> where, PID: Process-Id of periodic task, an integer number PE: Execution time of periodic task P: Period of periodic task AT: The arrival time of the periodic process, an integer value greater than or equal to 0

Workload File: OE-schedule.txt

Workload File: 1 // Periodic task #1 1 4 0 2 // Periodic task #2 1 8 0 3 // Periodic task #3 2 10 0 4 // Periodic task #4 5 20 0

Menu-based User Interface

1. Generate Workload file 2. Produce the scheduling points with CRP 3. Run OE-Scheduler 4. Exit

The Scheduling Points with CRP

Tasks Arrival Time Current Request Period of Pij

P10 0 even P20 0 even P30 0 even P40 0 even P11 4 odd P12 8 even P21 8 odd P31 10 odd P13 12 odd P14 16 even P22 16 even P15 20 odd P32 20 even P41 20 odd P16 24 even P23 24 odd P17 28 odd P33 30 odd P18 32 even P24 32 even P19 36 odd

Schedule for 4 Periodic Task by OE-Scheduler

Schedule for 4 periodic task by OE-Scheduler Time Instance Context-Switch 0 Idle No 1 Idle No 2 Idle No 3 P10 Yes 4 P11 No 5 P20 Yes 6 P30 Yes 7 P30 No 8 P21 Yes 9 P40 Yes 10 P31 Yes 11 P12 Yes 12 P13 No 13 P31 Yes 14 P40 Yes 15 P40 No 16 P40 No 17 P40 No 18 Idle No 19 P14 Yes 20 P15 No

Schedule for 4 periodic task by OE-Scheduler

21 P22 Yes 22 P41 Yes 23 P32 Yes 24 P23 Yes 25 P32 Yes 26 P41 Yes 27 P16 Yes 28 P17 No 29 P41 Yes 30 P33 Yes 31 P33 No 32 P41 Yes 33 P41 No 34 Idle No 35 P18 Yes 36 P19 No 37 P24 Yes* 38 Idle No 39 Idle No 40 Idle No * 2 context switches occur except the last instance

Comparison Table

Number of context switches for times 0 to 40

Time 0 6 12 18 24 30 36 40 Algorithm

RMA 0 9 15 23 29 39 47 49 EDFA 0 9 15 23 29 39 47 49 OE 0 3 13 17 25 35 41 43

Conclusion

A study of dynamic behavior property in hard real-time environments

Robust design facilitates easier extension of the system to include more dynamic environments

Provide the real-time system engineers with greater flexibility to design future real-time systems

Helping the designer of real-time operating systems

Future Work

Extend our scheduling algorithms to distributed and multiprocessor environments