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Microwave_Oven_Controller
- 1. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Microwave Oven Controller
Sree Nikhilendra Prasad DJ
FT 2014 Batch, Reg. No.: 14ETCS037010
M. Tech. in Real Time Embedded Systems
Module Leader: Padma Priya Darshini P.
Module Name: Embedded Computer Architecture and
Programming
Module Code : CSE502
- 2. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Marking
Head Maximum Score
Technical Content 5
Grasp and Explanation 5
Quality of Slides and
Delivery
5
Q & A 5
Total 20
- 3. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Presentation Outline
• Introduction
• Linear Programming
• Integer Linear Programming
• Implicit Path Enumeration Techniques
• State Transition Diagram
• System Requirements
• CDFG
• Output
• Test Cases
• Conclusion
• References
- 4. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Introduction
• Worst Case Execution Time is vital for real-time
embedded software.
• Worst Case Execution bounds are useful to
determine whether the given software
implementation will provide stable performance
or not.
- 5. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Linear Programming
• Linear programming is methodology to code the
requirements of the system in form of a linear
constraints
• The main elements of any constrained
optimization problem
– Variables
– Object function
– Variable bounds
- 6. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Integer Linear Programming
• An integer linear programming problem is a
mathematical optimization or
feasibility program in which some or all of the
variables are restricted to be integers.
• Components of integer linear programming
– Integer hulls
– Branch-and-bound
– Branch-and-cut
- 7. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Implicit Path Enumeration Techniques
• Implicit path enumeration technique is used to
find the WCET of control-intensive programs.
• Considers path of execution as sets of basic blocks.
• It can be used to analyze hardware schemes.
• It expresses the search of the worst case execution
time as an integer linear programming.
- 8. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
State Transition Diagram
- 9. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
System Requirements
• The system should read the mode and perform the cooking.
• The system should read the cooking time given as input
through keypad.
• The system should display the time required for cooking on
LCD display.
• The system shall ON the LED during cooking.
• The system shall OFF the LED at the end of the cooking.
• The system shall raise the alarm at the end of the cooking
for 5 seconds.
- 10. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
CDFG
- 11. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Output
- 12. ©M. S. Ramaiah University of Applied Sciences
12
Faculty of Engineering & Technology
Output contd..
- 13. ©M. S. Ramaiah University of Applied Sciences
13
Faculty of Engineering & Technology
Test Cases
Test Case Test Procedure Expected Result Result
Test1 Input the mode value and select the mode according
to inputted value
The system should show “respective
mode”
Pass
Test2 Output timer running for the given timer value The system should show “timer running” Pass
Test3 Output the cooking end when timer is elapsed The system should show “cooking is
done”
Pass
Test4 Buzzer is made on when cooking progress is
completed
The system should enable the buzzer
sound
Pass
Test5 Buzzer is made off after the delay of buzzer on
progress
The system should stop the buzzer sound pass
- 14. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
Conclusion
• To calculate WCET with less calculation overhead
implicit path enumeration technique is best
suited.
• Mixed-integer linear programming introduces less
calculation overhead.
- 15. ©M. S. Ramaiah University of Applied Sciences
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Faculty of Engineering & Technology
References
• Padma Priya Darshini P. Embedded Computer Architecture and
Programming, Course Notes, M.S. Ramaiah University of Applied
Sciences, Bangalore, October, 2014.
• John W. Chinneck, Practical Optimization: A Gentle Introduction, 2001.
• Reinhard Wilhelm, Jakob Engblom, Adreas Ermedahl, Niklas Holsti,
Stephan Thesing, David Whalley, Guillem Bernat, Christian Fedinand,
Reinhold Heckmann, Tulika Mitra, Frank Mueller, Isabelle Puaut, Peter
Puschner, Jan Staschulat and Per Stenstrom, The Worst-Case Execution
Time Problem – Overview of Methods and Survey of Tools, ACM
Transactions on Programming Languages and Systems.
• Ambros M. Gleixner, Daniel E. Steffy and Kati Wolter, Improving the
Accuracy of Linear Programming Solves with Iterative Refinement, Berlin,
Germany, May, 2012.