CEN489 Modeling of Computer Networks

6 ECTS - 3-0 Duration (T+A)- 7. Semester- 3 National Credit

Information

Code CEN489
Name Modeling of Computer Networks
Term 2023-2024 Academic Year
Semester 7. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. MEHMET FATİH AKAY
Course Instructor
1


Course Goal / Objective

Understanding parameters and test methods for optimal network protocol design, prediction of next generation network architectures and protocols

Course Content

Introduction to network modeling, network calculus, dynamic scheduling and resource allocation, network games, protocol analysis

Course Precondition

There is no prerequisite.

Resources

Computer Networking: A Top-Down Approach by Kurose & Ross 7th edition, ISBN-10: 9780133594140

Notes

Computer Networking: A Top-Down Approach by Kurose & Ross 7th edition, ISBN-10: 9780133594140


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Understanding network protocols
LO02 Concept of optimal network protocol
LO03 The use of tools, methods and tests in network modeling
LO04 Ability to apply optimal network modeling methods to real world problems.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Has capability in the fields of mathematics, science and computer that form the foundations of engineering 2
PLO02 Bilgi - Kuramsal, Olgusal Identifies, formulates, and solves engineering problems, selects and applies appropriate analytical methods and modeling techniques, 3
PLO03 Bilgi - Kuramsal, Olgusal Analyzes a system, its component, or process and designs under realistic constraints to meet the desired requirements,gains the ability to apply the methods of modern design accordingly. 4
PLO04 Bilgi - Kuramsal, Olgusal Ability to use modern techniques and tools necessary for engineering practice and information technologies effectively. 3
PLO05 Bilgi - Kuramsal, Olgusal Ability to design and to conduct experiments, to collect data, to analyze and to interpret results 5
PLO06 Bilgi - Kuramsal, Olgusal Has ability to work effectively as an individual and in multi-disciplinary teams, take sresponsibility and builds self-confidence 2
PLO07 Beceriler - Bilişsel, Uygulamalı Can access information,gains the ability to do resource research and uses information resources 5
PLO08 Beceriler - Bilişsel, Uygulamalı Awareness of the requirement of lifelong learning, to follow developments in science and technology and continuous self-renewal ability 4
PLO09 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Ability to communicate effectively orally and in writing, and to read and understand technical publications in at least one foreign language
PLO10 Yetkinlikler - Öğrenme Yetkinliği Professional and ethical responsibility,
PLO11 Yetkinlikler - Öğrenme Yetkinliği Awareness about project management, workplace practices, employee health, environmental and occupational safety, and the legal implications of engineering applications,
PLO12 Yetkinlikler - Öğrenme Yetkinliği Becomes aware of universal and social effects of engineering solutions and applications, entrepreneurship and innovation, and knowledge of contemporary issues 2


Week Plan

Week Topic Preparation Methods
1 Network models There is no prerequisite. Öğretim Yöntemleri:
Anlatım
2 Modeling and measurement tools There is no prerequisite. Öğretim Yöntemleri:
Anlatım
3 Network performance metrics There is no prerequisite. Öğretim Yöntemleri:
Anlatım
4 Models for data flows There is no prerequisite. Öğretim Yöntemleri:
Anlatım
5 Stochastic scheduling There is no prerequisite. Öğretim Yöntemleri:
Anlatım
6 Markov process and its application for analyzing network resource allocation There is no prerequisite. Öğretim Yöntemleri:
Anlatım
7 Available bandwidth estimation There is no prerequisite. Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam There is no prerequisite. Ölçme Yöntemleri:
Yazılı Sınav
9 Detecting network anomalies There is no prerequisite. Ölçme Yöntemleri:
Yazılı Sınav
10 Introduction to game theory There is no prerequisite. Öğretim Yöntemleri:
Anlatım
11 Resource sharing games There is no prerequisite. Öğretim Yöntemleri:
Anlatım
12 Congestion games There is no prerequisite. Öğretim Yöntemleri:
Anlatım
13 Petri nets There is no prerequisite. Öğretim Yöntemleri:
Anlatım
14 Detecting congestion with Markov There is no prerequisite. Öğretim Yöntemleri:
Anlatım
15 Case studies There is no prerequisite. Öğretim Yöntemleri:
Anlatım
16 Term Exams There is no prerequisite. Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams There is no prerequisite. Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 10.05.2023 10:01