Distributed Processing in Grids and Clouds

Course Information
TitleΚατανεμημένη Επεξεργασία σε Πλέγματα και Νέφη / Distributed Processing in Grids and Clouds
CodeCNSS103
FacultySciences
SchoolInformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorEleni Karatza
CommonYes
StatusActive
Course ID600016159

Programme of Study: PMS DIKTYA EPIKOINŌNIŌN KAI ASFALEIA SYSTĪMATŌN (2018 éōs sīmera) PF

Registered students: 9
OrientationAttendance TypeSemesterYearECTS
Díktya EpikoinōniṓnElective Courses117.5
Asfáleia SystīmátōnElective Courses117.5

Class Information
Academic Year2026 – 2027
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
600312368
Course Type 2021
Specialization / Direction
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
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
  • Research Papers
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
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures39✓
Reading Assigment75✓
Project75✓✓
Exams3✓
Solving exercises to understand the theory 33✓✓
Total225
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
06-09-2024