Distributed Computing (CMPE537) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Distributed Computing CMPE537 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type N/A
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The objective of this course is to introduce students to advanced concepts of distributed computing.
Course Learning Outcomes The students who succeeded in this course;
  • Gather problem solving skills to distributed application
  • Identify and decompose a complex systems into its components
  • Apply programming language concepts in solving the distributed components
  • Develop service oriented applications
Course Content Introduction to the core concepts and principles of distributed programming techniques, computing paradigms, protocols, and application program interfaces (APIs), sockets, multicast, Remote Method Invocation (RMI), Common Object Request Broker Architecture (CORBA), Interface Definition Language (IDL), applets, servlets, Common Gateway Interface (CG

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to distributed computing Chapter 1
2 Interprocess Communication Chapter 2
3 Interprocess Communication Chapter 2
4 Distributed Computing Paradigms. Chapter 3
5 The Socket API Chapter 4
6 The Client-server Paradigm Chapter 5
7 Group Communications Chapter 6
8 Distributed objects Chapter 7
9 Advanced Remote Method Invocations Chapter 8
10 Internet applications Chapter 9
11 Internet applications (cont.) Chapter 11
12 MPI Based distributed computing Lecture Notes
13 Service based distribution (REST, SOAP,etc) Lecture Notes
14 Advanced Distributed Computing Paradigms Chapter 12
15 Review
16 Review

Sources

Course Book 1. “Distributed Computing: Principles and Applications”, M. L. Liu, Pearson/Addison-Wesley, ISBN: 0-201-79644-9.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 3 30
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 35
Final Exam/Final Jury 1 35
Toplam 5 100
Percentage of Semester Work 65
Percentage of Final Work 35
Total 100

Course Category

Core Courses
Major Area Courses
Supportive Courses X
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 To become familiar with the state-of-the art and the literature in the software engineering research domain X
2 An ability to conduct world-class research in software engineering and publish scholarly articles in top conferences and journals in the area
3 Be able to conduct quantitative and qualitative studies in software engineering X
4 Acquire skills needed to bridge software engineering academia and industry and to develop and apply scientific software engineering approaches to solve real-world problems X
5 An ability to access information in order to follow recent developments in science and technology and to perform scientific research or implement a project in the software engineering domain.
6 An understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering.
7 Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards of excellence for software engineering practices standards and methodologies.
8 An understanding about the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions.
9 Promote the development, adoption and sustained use of standards of excellence for software engineering practices.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration
Project 3 5 15
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 20 20
Total Workload 125