Course Name | Queueing Systems |
Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
---|---|---|---|---|---|
IE 339 | Fall/Spring | 3 | 0 | 3 | 6 |
Prerequisites |
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Course Language | English | ||||||||
Course Type | Elective | ||||||||
Course Level | First Cycle | ||||||||
Mode of Delivery | - | ||||||||
Teaching Methods and Techniques of the Course | |||||||||
Course Coordinator | - | ||||||||
Course Lecturer(s) | - | ||||||||
Assistant(s) | - |
Course Objectives | The purpose of this course is to introduce students to a general framework for modeling queueing systems and to the basic methodologies used for their analysis. |
Learning Outcomes | The students who succeeded in this course;
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Course Description | The purpose of this course is to introduce students to a general framework for modeling queueing systems and to the basic methodologies used for their analysis. Since queueing phenomenon is in general due to randomness, the course requires extensive use of probability theory. The course will encompass the stochastic processes necessary for analyzing queueing systems. At the end the course, the students are supposed to be acquainted with the available analytical models for queueing systems and to be able to use them for performance analysis of service and production systems. |
Related Sustainable Development Goals | |
| Core Courses | |
Major Area Courses | ||
Supportive Courses | ||
Media and Managment Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Required Materials |
1 | Characteristics of Queueing Systems | Ch 1 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
2 | Performance Evaluation Concepts | Ch 1 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
3 | Poisson Process and Exponential Distribution | Ch 2 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
4 | Markov Chains | Ch 2 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
5 | Simple Markovian BirthDeath Queueing Models | Ch 3 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
6 | Simple Markovian BirthDeath Queueing Models | Ch 3 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
7 | Review and Midterm Exam | |
8 | Advanced Markovian Queueing Models | Ch 4 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
9 | Advanced Markovian Queueing Models | Ch 4 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
10 | Queueing Networks | Ch 5 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
11 | Queueing Networks | Ch 5 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
12 | General Distribution Models | Ch 6 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
13 | General Distribution Models | Ch 6 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
14 | Advanced Topics | Ch 7 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
15 | General review and evaluation | |
16 | Review of the Semester |
Course Notes/Textbooks | D. Gross, CM. Harris, Queueing Theory, Wiley, 2009. |
Suggested Readings/Materials |
Semester Activities | Number | Weigthing |
Participation | 1 | 10 |
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments | 3 | 10 |
Presentation / Jury | ||
Project | 1 | 20 |
Seminar / Workshop | ||
Oral Exam | ||
Midterm | 1 | 30 |
Final Exam | 1 | 30 |
Total |
Weighting of Semester Activities on the Final Grade | 6 | 70 |
Weighting of End-of-Semester Activities on the Final Grade | 1 | 30 |
Total |
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
Study Hours Out of Class | 14 | 4 | 56 |
Field Work | |||
Quizzes / Studio Critiques | |||
Portfolio | |||
Homework / Assignments | 3 | 7 | |
Presentation / Jury | |||
Project | 1 | 21 | |
Seminar / Workshop | |||
Oral Exam | |||
Midterms | 1 | 16 | |
Final Exams | 1 | 18 | |
Total | 180 |
# | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
1 | To have adequate knowledge in Mathematics, Science, Computer Science and Software Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems. | |||||
2 | To be able to identify, define, formulate, and solve complex Software Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose. | |||||
3 | To be able to design, implement, verify, validate, document, measure and maintain a complex software system, process, or product under realistic constraints and conditions, in such a way as to meet the requirements; ability to apply modern methods for this purpose. | |||||
4 | To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in software engineering applications; to be able to use information technologies effectively. | |||||
5 | To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex Software Engineering problems. | |||||
6 | To be able to work effectively in Software Engineering disciplinary and multi-disciplinary teams; to be able to work individually. | |||||
7 | To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to be able to present effectively, to be able to give and receive clear and comprehensible instructions. | |||||
8 | To have knowledge about global and social impact of engineering practices and software applications on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Engineering and Software Engineering solutions. | |||||
9 | To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications. | |||||
10 | To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development. | |||||
11 | To be able to collect data in the area of Software Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1) | |||||
12 | To be able to speak a second foreign language at a medium level of fluency efficiently. | |||||
13 | To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Software Engineering. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest