This course is for Summer Semester 2018. For registration, please use the TISS site. New information will be updated soon
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.
|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
|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
|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
|4 May 2018||Big data service systems: Models, Elasticity, and Platforms||Big data services, big data platforms and services
|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 project reports must be submitted to TUWEL.
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 are open source under GitHub.