Advanced Techniques for Communication Data Processing and Computation in Mobile and Wireless Networks

Објавено: July 3, 2023
1. Course Title Advanced Techniques for Communication Data Processing and Computation in Mobile and Wireless Networks
2. Code 4ФЕИТ10017
3. Study program 11-IBS, 12-KIT, 20-IMSA
4. Organizer of the study program (unit, institute, department) Faculty of Electrical Engineering and Information Technologies
5. Degree (first, second, third cycle) Second cycle
6. Academic year/semester I/1   7.    Number of ECTS credits 6.00
8. Lecturer Dr Tomislav Shuminoski
9. Course Prerequisites
10. Course Goals (acquired competencies):

The student will be enriched with theoretical and practical work in advanced computations of communication data over mobile and wireless networks and systems. The students will work and get knowledge for distributive systems and future generation of mobile and wireless systems and services. With the knowledge given in this course, the student will have opportunity to get skills and competitions for Mobile Cloud Computing (MCC) and fog computing, design of computation systems, infrastructures and services which are using advanced Cloud computation and processing. Also, the student will get practical and theoretical knowledge for modern advanced data computation and processing in wireless and mobile systems and Delay-Tolerant Networking (DTN).

11. Course Syllabus:

Historical development of techniques for data processing and computations. Overview of distributive and parallel data systems. Overview of Mobile applications and services. ITU framework for Cloud Computing, Cloud ecosystem, cloud types and general recommendations for Cloud Computing. Mobile Cloud and fog computing systems and architectures. Service models for mobile cloud computing and communication data processing in mobile and wireless networks (IaaS, PaaS, SaaS, NaaS, CaaS). Advanced services for Mobile Cloud Computing (Location Base Services and context-aware services). Security mechanisms in Mobile Cloud Computing and processing of communication data. Management techniques and data computation in DTNs. Regulation and business aspects of data computation and processing in mobile and wireless networks.

12. Learning methods:

Lectures, presentations, interactive learning, practical and theoretical exercises (using simulations, software and hardware), team work, case study, invited lecturer(s), homework, project work and/or seminar work, e-learning (forums), consultations.

13. Total number of course hours 180
14. Distribution of course hours 3 + 3
15. Forms of teaching 15.1 Lectures-theoretical teaching 45 hours
15.2 Exercises (laboratory, practice classes), seminars, teamwork 45 hours
16. Other course activities 16.1 Projects, seminar papers 30 hours
16.2 Individual tasks 30 hours
16.3 Homework and self-learning 30 hours
17. Grading
17.1 Exams 0 points
17.2 Seminar work/project (presentation: written and oral) 50 points
17.3. Activity and participation 10 points
17.4. Final exam 40 points
18. Grading criteria (points) up to 50 points 5 (five) (F)
from 51 to 60 points 6 (six) (E)
from 61 to 70 points 7 (seven) (D)
from 71 to 80 points 8 (eight) (C)
from 81 to 90 points 9 (nine) (B)
from 91 to 100 points 10 (ten) (A)
19.

Conditions for acquiring teacher’s signature and for taking final exam

Regular realization of the activities from 15.1 up to 16.3.
20. Forms of assessment

During the semester, two partial written exams are provided (at the middle and at the end of the semester, lasting 90 minutes) and a practical project (after the theoretical classes). The points from the partial exams, the points form the project work, the points from the homework assignments and the points from the study activity. In the planned exam sessions, a written exam is taken (duration 90 minutes). The final grade includes the points from the written exam, the points of the project work, the points from the homework assignments and the points from the study activity. It is not allowed to use books, scripts, manuscripts or notes of any kind during the exam, as well as a calculator, mobile phone, tablet or any other electronic device.

21. Language Macedonian and English
22. Method of monitoring of teaching quality Self-evaluation
23. Literature
23.1.       Required Literature
No. Author Title Publisher Year
1. Debashis De Mobile Cloud Computing: Architectures, Algorithms and Applications CRC Press/ Chapman and Hall 2015
2. Gai, Keke; Qiu, Meikang Mobile cloud computing models, implementation, and security Chapman and Hall/CRC 2017
3. Constandinos X. Mavromoustakis, George Mastorakis, Ciprian Dobre (Editors) Advances in Mobile Cloud Computing and Big Data in the 5G Era Springer 2017
23.2.       Additional Literature
No. Author Title Publisher Year
1.  A. Galati  Delay Tolerant Network  LAP LAMBERT  2010