Advanced cloud computing topics

1.

Subject title

Advanced cloud computing topics

Напредни теми од пресметување во облак

2.

Code

CC-Z-04

3.

Study program

Cloud Computing, Data science in computer science and engineering, IT management, Bioinformatics, Security, Cryptography and Coding, Еducation with ICT, Eco-informatics, Inteligent Systems, Computer Science, Cloud Computing, Software for embedded systems, Software Engineering, IT management, Bioinformatics, Security, Cryptography and Coding, Software Engineering, Internet Technologies and cyber security, Statistics and Data Analytics, Statistics and Data Analytics,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Магдалена Костоска Ѓорчевска проф. д-р Марјан Гушев

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

This course represents and studies current topics in cloud calculation as applying serverless calculation, advanced algorithms, system models and techniques for monitoring and analyzing top -notch cloud services, software systems, IoT and EDGE calculation, complex and complex and complex Cloud hybrid systems such as IoT systems and federations in the cloud as a continuous computer environment where complex applications will develop and execute.

11.

Subject content:

Overview of Advanced Cloud Calculation Topics and Service Calculation for Different Domains, such as Serverless Calculation, EDGE Calculation. Cloud robotics, large data analysis, industry 4.0, etc. Advanced algorithms and how they are used in real scenarios. Examples are for high availability, data separation, geographical balance of multiple cloud loads, automatic detection and formation of container groups, interactions between IoT and Cloud, etc. Algorithms to control elasticity in cloud, IoT, and fog and how they are used in real scenarios. Examples of elasticity in well -known cloud systems, elastic coordination algorithms in many clouds, fog and NFV elasticity algorithms, etc. Techniques and tools for tracking/monitoring of cloud, IoT, cloud and fog systems. Examples are the monitoring of end -to -end review performance, cloud and IoT instrumentation techniques.

12.

Learning methods:

Предавања, вежби, самостојна работа, проектни задачи, семинарски работи

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

40 + 30 + 20 + 60 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

40 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

30 hours

16.

Other forms of activities

16.1.

Project tasks

60 hours

16.2.

Independent tasks

20 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

60 points

17.3.

Activities and learning

0 points

17.4.

Final exam

0 points

18.

Grading criteria (points / grade)

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.

Condition for signature and taking final exam

реализирани активности 15.1 и 15.2

20.

Language of instruction

македонски или англиски

21.

Quality assurance method

интерна евалуација и анкети, според модел образложен претходно

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature