Course Information

This course is for Summer Semester 2018. For registration, please use the TISS site. New information will be updated soon

  • Instructor: Hong-Linh Truong
  • TISS Course Number: 184.742
  • Level: Elective course for Master degree in Informatics and Business Informatics and PhD students

Course Description

The objective of this course is to introduce new concepts and techniques for developing and engineering advanced services in emerging distributed computing systems including IoT (Internet of Things), cloud services, and human-based services. In this course, we will introduce concepts of data-as-a-service, data concerns, data market places and techniques for developing data intensive services by utlizing data services with compute services in cloud environments. We will focus on advanced services to analyze IoT data, e.g., for reactive monitoring and predictive maintenance. Furthermore, we will investigate human-based services in engineering advanced data analytics and how to combine them with data and compute services. The course will provide hand-on experiences via real-world exercises and mini programming projects. The course will provide a great interaction between students and the instructor.



This year the course receives support from Google Cloud Platform Education Grant for running experiments atop Google Cloud!

As the IoT integration is quite mature w.r.t. the technologies and platforms for integrating IoT devices, we will focus less on IoT integration and more on making sense of IoT data for offering advanced services.

Course dates

Lectures are held on Friday from 10-12. Note that lectures are NOT held every week! See lecture notes for lecture dates.

Location: Ersatzraum SR Argentinierstrasse, Institutsgebäude (Favoritenstr. 9-11) - 1. Stock Room Number: HE0108.

Also Check TISS web page

Lecture notes

Note: everything here is under construction

Lectures will be held at: Ersatzraum SR Argentinierstrasse, Institutsgebäude (Favoritenstr. 9-11) - 1. Stock Room Number: HE0108

IMPORTANT NOTE: The lecture room is Ersatzraum SR Argentinierstrasse, Institutsgebäude (Favoritenstr. 9-11) - 1. Stock Room Number: HE0108

Date Topics Notes
2 Mar 2018, 10 am Course Overview Motivation and expectation of the course, and course administration
9 Mar 2018 Emerging distributed systems and challenges for services engineering Discuss new types of distributed systems, challenges, emerging services engineering issues, and application scenarios
First assignment
16 Mar 2018 The role of IoT, Cloud systems, Blockchain and Machine Learning as a service Overview of IoT, Cloud systems, Blockchain and Machine learning roles in complex services and engineering challenges
Second assignment
23 Mar 2018 NO LECTURE
30 Mar 2018 Easter break
6 April 2018 Easter break
13 April 2018 Scenario, application-specific services and platform services Student presentation and discussion.
27 April 2018 Data-as-a-Service, Data marketplace, data lakes: Models, Data Concerns, and Engineering Models of Data services, data lakes, data concerns, and data concern evaluation
Third assignment
4 May 2018 Big data service systems: Models, Elasticity, and Platforms Big data services, big data platforms and services
Fourth assignment
18 May 2018 Assignment discussion, Presentation of mini project proposals
25 May 2018 Algorithms & Quality-aware Data Analytics data analytics, quality of analytics, elasticity based on quality of analytics
8 June 2018 Human-machine in advanced services we will discuss about human-based services could be integrated with software-based services to provide advanced analytics
22 June 2018 Mini project presentation Student presentation and demo of mini projects
25- June 2018- Final exam Oral examination

Assignments and Projects

Assignments and project reports must be submitted to TUWEL.

Assignment 1

Develop your scenario. See the template is here.

Assignment 2

Design application-specific services and platform services. See the description here

Assignment 3

Assignment 4

Proposing and designing a mini project

Mini project

Concrete topics are based on the proposal and design presented in the 4th assignment.

you will (i) create an open source mini project using public git (such as github, bitbucket, or gitlab), (ii) develop the project, (iii)document the project with README file or HTML, (iv) Submit a presentation to TUWEL and make the code public, (v) finally you make a presentation/demo your project.

The prototpyes of the mini projects will be posted in Github


Student projects

Student projects are open source under GitHub.

Peter Klein, Summer 2015

IOT- sensors and data services

Thomas Hiessl, Summer 2015

Open Survey Data Lab

Ivan Pavkovic, Summer 2015

IoT Approach To Accommodation & Booking Related Web Services:Slides and Video

Georgiana Copil, Summer 2014

Xively and data concerns

Erum Naz & Duc-Hung Le, Summer 2014

Evaluating Crime Data for UK Police

Daniel Moldovan, Summer 2014

Windows Azure Marketplaces

Juraj Cik, Summer 2014

Xively and Data Analytics Services