This course is for Winter Semester 2017. For registration, please use the TISS site. New information will be updated soon
In the age of IoT, big data and deep learning, we handle a massive number of devices generating huge amount of data which are stored and analyzed by advanced aglorithms in a large scale of edge and cloud computing infrastructures. What would be key foundational concepts of services computing and cloud computing that enable seamless integration and execution of such big data, complex algorithms and diverse services?
The goal of this lecture is to discuss and study advanced theoretical foundations, system designs, algorithms and system analysis of recent developments regarding Service Computing and Cloud Computing in large-scale distributed systems that enable contemporary data science, IoT analytics and deep learning. We do not learn how to program IoT Cloud Systems (as shown in Advanced Services Engineering), Web services (as shown in Advanced Internet Computing) or particular distributed systems technologies. But we will focus on on advanced algorithms, system models, and performance monitoring and analysis techniques for state-of-the-art cloud services, software service systems, IoT, and edge computing that are essential and foundational for building today and tomorrow's reliable and high-quality applications in cloud robotics, Industry 4.0, data science, deep learning, to name just a few.
Students will learn and research state-of-the-art algorithms and techniques through literature study, individual and team development project with real-world case studies and questions.
The key format of the course is to discuss and debate. For this format, students will be required to read key papers for certain topics and present their findings. Key papers will refect the state-of-the-art work in the topics of the course.
|6 Oct 2017||Course Overview||Motivation and expectation of the course, and course administration (PDF)|
|13 Oct 2017||Service-oriented and Cloud Computing: Recap and Outlook||Lecture and discussion on key advanced topics of cloud and service computing for various domains, like cloud robotics, big data analytics, Industry 4.0, etc. (PDF)|
|20 Oct & 17 Nov, 2017||Advanced algorithms for Complex and Hybrid cloud systems||Study advanced algorithms and discuss how they are used in real-world scenarios. Examples are for high availability, data sharding, geographical multi-cloud load balancing, automatic discovery and formation of container clusters, interactions between IoT and cloud, cloud robotics, etc.
|24 Nov, 1 Dec & 15 Dec, 2017||Elasticity principles and control algorithms||Study algorithms for elasticity controls in IoT, Cloud and fog computing and discuss how they are used in real-world scenarios. Examples are elasticity in well-known cloud systems, algorithms for elasticiy coordination in multi-cloud environments, elasticity algorithms for fog and NFV, coordination and control in cloud robotics
Elasticity Engineering: Foundations
Elasticity Engineering: Real-world and Academic Implementation
|22 Dec, 2017, 12 Jan 2018||Complex big data analytics system design||Study techniques and algorithms for big data ingest and analytics. Examples are algorithms for large-scale data ingest and analytics, analytics in Industry 4.0, analytics and robotics, etc. Topic introduction|
|19 & 26 Jan, 2018||End-to-End Service Performance and Dependability Analytics||Study techniques and tools for monitoring IoT, cloud and fog systems. Examples are performance monitoring for end-to-end view, instrumentation techniques for IoT and cloud Discussion slides|
|TBD||Final exam||Oral examination|
Since the course is highly interactive and focused on reading, analyzing and presenting state-of-the-art (reviewing topics), assignments will be mainly about the presentation of your findings. Assignment presentations must be submitted to TUWEL.