Distributed Processing in Grids and Clouds
| Title | Κατανεμημένη Επεξεργασία σε Πλέγματα και Νέφη / Distributed Processing in Grids and Clouds |
| Code | CNSS103 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter |
| Coordinator | Eleni Karatza |
| Common | Yes |
| Status | Active |
| Course ID | 600016159 |
Programme of Study: PMS DIKTYA EPIKOINŌNIŌN KAI ASFALEIA SYSTĪMATŌN (2018 éōs sīmera) PF
Registered students: 12
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| Díktya Epikoinōniṓn | Elective Courses | 1 | 1 | 7.5 |
| Asfáleia Systīmátōn | Elective Courses | 1 | 1 | 7.5 |
| Academic Year | 2021 – 2022 |
| Class Period | Winter |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Class ID | 600200240
|
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600200240
- eLearning (Moodle): https://elearning.auth.gr/auth/saml/login.php
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Basic knowledge in distributed processing.
Learning Outcomes
Knowledge: Thorough grasp of distributed processing. Acquaintance with advanced distributed algorithms for new large scale distributed computing environments such as computational clouds.
Skills: Practice in solving exercises and problems based on taught theory. Capacity to develop and to employ efficient distributed algorithms.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Work in teams
- Be critical and self-critical
- Advance free, creative and causative thinking
Course Content (Syllabus)
Distributed Processing in computational grids and clouds. Real time distributed systems – Soft / Hard deadlines: Scheduling of Independent tasks - Scheduling of dependent tasks. P2P systems. Performance versus energy efficiency, economics and trust management in large scale distributed systems. Synchronization in distributed systems. Distributed consensus. Failures – Tolerance – Checkpointing – Recovery – Stabilization.
Keywords
Distributed Processing, Grids, Clouds
Educational Material Types
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
Description
Use of computer for teaching.
Use of eLearning for communication.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 39 | ✓ | |||
| Reading Assigment | 75 | ✓ | |||
| Project | 75 | ✓ | ✓ | ||
| Solving exercises to understand the theory | 36 | ✓ | ✓ | ||
| Total | 225 |
Student Assessment
Description
Written exams 50%, project with presentation 30% (research project, or programming assignment), exercises solving 20%.
The exact procedure is announced at the course site.
Student Assessment methods
- Written Exam with Short Answer Questions (Summative)
- Written Exam with Extended Answer Questions (Summative)
- Written Assignment (Summative)
- Written Exam with Problem Solving (Summative)
Bibliography
Additional bibliography for study
Προτεινόμενη βιβλιογραφία και υλικό
1. Σημειώσεις παραδόσεων (Διαφάνειες μαθημάτων), https://elearning.auth.gr/auth/saml/login.php.
2. Distributed Algorithms, Nancy A. Lynch (The Morgan Kaufmann Series in Data Management Systems), 1996.
3. Grid Computing: Techniques and Applications, Barry Wilkinson, (Chapman & Hall/CRC Computational Science), 2010.
4. Cloud Computing: Implementation, Management, and Security, John W. Rittinghouse, James F. Ransome, CRC Press, 2010.
Επιπρόσθετη βιβλιογραφία
1. Cloud Computing, K. Jamsa, Jones & Bartlett Learning, 2013.
2. Scheduling: theory algorithms and systems, M. Pinedo, Springer, 2012.
3. Principles of Sequencing and Scheduling, Kenneth R. Baker, Dan Trietsch, Wiley, 2009.
4. Cloud Computing: Principles and Paradigms, Rajkumar Buyya, James Broberg,Andrzej M. Goscinski, Wiley, 2011.
5. Achieving Real-Time in Distributed Computing: From Grids to Clouds, Dimosthenis Kyriazis, Editor, Theodora Varvarigou, Kleopatra G. Konstanteli, IGI Global, 2012.
6. Handbook of Scheduling: Algorithms, Models, and Performance Analysis, Joseph Y-T. Leung, James H. Anderson, Chapman and Hall/CRC, 2004.
7. Hierarchical Scheduling in Parallel and Cluster Systems, S. Dandamudi, 2003, Kluwer Academic/Plenum Publishers.
8. Quantitative Quality of Service for Grid Computing: Applications for Heterogeneity, Large-scale Distribution, and Dynamic Environments, Lizhe Wang, Jinjun Chen, Wei Jie, IGI Global, 2009.
9. Dependable Computing Systems: Paradigms, Performance Issues, and Applications, Hassan B. Diab, Albert Y. Zomaya, Wiley Series on Parallel and Distributed Computing, 2005.
10. Soft Real-Time Systems: Predictability vs. Efficiency, Giorgio Buttazzo, Giuseppe Lipari, Luca Abeni, Marco Caccamo, Springer 2005.
11. Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications, Giorgio Buttazzo, 2005 Springer.
12. Ερευνητικές Εργασίες
Last Update
27-10-2022
