Cloud-Based Data Processing
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
IN2386 is a semester module in English language at Bachelor’s level and Master’s level which is offered in winter semester.
This Module is included in the following catalogues within the study programs in physics.
- Focus Area Bio-Sensors in M.Sc. Biomedical Engineering and Medical Physics
- Focus Area Imaging in M.Sc. Biomedical Engineering and Medical Physics
|Total workload||Contact hours||Credits (ECTS)|
|150 h||60 h||5 CP|
Content, Learning Outcome and Preconditions
* Intro to Data-centers
* Latest trends in Cloud Computing
Fundamentals for managing distributed data
* Data replication and quorums
* Data partitioning
* Fault-tolerance and unreliable components
* Distributed system model
* Consensus protocols and coordination services
* Consistency models and distributed key value stores
Design of cloud-based data processing systems
* Distributed transactions
* Cloud-native OLTP databases
* Cloud-native data warehouses
* Dataflow computing (i.e., derived data)
* Cloud-scale data streaming systems
* Query-as-a-Service (QaaS) (serverless data processing)
* Resource management and scheduling
Other related topics:
* Novel data storage formats (e.g., data lakes, data-mash, etc.)
* Security and Privacy for data processing in the cloud
* Accelerators and impact of new hardware technology
* define the requirements and challenges when architecting, building and managing a large-scale data processing service in the cloud.
* use the theoretical foundations of distributed algorithms to construct the building blocks for a scalable data system design in relation to distributed storage, coordination and computation.
* understand and analyze the different trade-offs when designing scalable data processing systems that need to run in the public cloud.
* design, implement and evaluate a three-tier system using current cloud technologies.
* identify the scalability bottlenecks and vulnerabilities of a complex computer system.
IN0009 Basic Principles: Operating Systems and System Software
IN0010 Introduction to Computer Networking and Distributed Systems
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
|VI||5||Cloud-Based Data Processing (IN2386)||Giceva Makreshanska, J. Gruber, F.||
Wed, 10:00–13:00, MI 02.09.014
Learning and Teaching Methods
The module consists of lectures and accompanying tutorials. The contents of the course will be primarily presented in the form of lectures and discussions of real-world system designs. Solutions to exercises will be discussed in the tutorials.
• Distributed Systems by Maarten van Steen, Andrew S. Tanenbaum
• Principles of Distributed Database Systems by M. Tamer Ozsu, Patrick Valduriez
Description of exams and course work
The exam may be repeated at the end of the semester.