Service Engineering Analytics - (SEA) - Team concentrates and consolidates research activities, resources, results, and collaborations on Systems, Software and Data Service Engineering Analytics carried out under the lead of Hong-Linh Truong at Faculty of Informatics, TU Wien.

Service Engineering Analytics

Engineering analytics is concerned with the techniques and tools for desiging, monitoring, analyzing, and optimizing functions, performance, data quality, elasticity, and uncertainties associated with systems, software, data and services. . In our work, we focus on engineering analytics for: Systems (IoT, Cloud, and Edge Systems), Software (Middleware, Protocols, and Tools) , Data (Processing Models and Analytics), Services (Data Marketplace, Service Models, APIs, and Configuration). We apply our engineering analytics techniques to various applications, including smart cities, smart agriculture, enterprises, e-science, logistics, robotics, and e-health.
Many results of our research are also reflected in our Advanced Services Engineering course for PhD/Master students at TU Wien and the Distributed Systems Technologies course for master studies.


we focus on emerging complex distributed systems covering cloud systems, IoT, edge/fog systems, cyber-physical systems and social-cyber-physical systems. Some of our novel concepts are elastic systems, IoT Cloud systems and the ensembles of IoT, Cloud and Networks


We focus on system software, middleware, tools and applications in the IoT, cloud, edge/fog, cyber-physical systems, and social-cyber-physical systems. Application domains are smart agriculture, smart city, e-science, and industrial internet. Some recent tools are IoT management, Uncertainty Testing for CPS


We focus on data models and data analytics, including various types of data in complex distributed systems that are gathered, processed and provisioned under different services. Some our novel concepts are elastic data analytics


Services offer functions built on capabilities of the above-mentioned systems, software and data. We focus on novel technical service models (data-as-a-service, IoT services, e-science services, and several application-specific services), service API and execution management, and dynamic business models (e.g. pay-per-use) for consumers. Some of our novel conconcepts are Data-as-a-Service, data contracts for data marketplaces, human sensing data marketplace, and IoT data marketplaces


Lead: Hong-Linh Truong

PhD Students

Master Students

  • Christian Proinger: Resource slice monitoring
  • Daniel Hopfer: Data lake for cloud forensics
  • Michael Hammerer: IoT Interoperability
  • Filip Rydzi: Blockchain and edge services

Current/past visitors

Liang Zhang, The-Vu Tran, Huu-Hung Huynh, Nam Huynh

Past members

Postdocs: Dr. Bunjamin Memishi, Dr. Luca Berardinelli, Dr. Georgiana Copil, Dr. Daniel Moldovan,
Master Students: Lingfan Gao, Juraj Cik, Florin Balint, Manfred Halper, Matthias Karan, Peter Klein


Our GitHub prototypes: https://github.com/rdsea

Our Docker Hub: https://hub.docker.com/u/rdsea/

Concepts & Prototypes


See our full list here. Recent publications:

Events & News

15 October 2018

ACM IoT 2018

We gave a tutorial on dynamic solutions for IoT interoperability at ACM IoT 2018

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19-20 Aug 2016

Talk at Workshop on IoT/Cloud-based CPS at Fudan University, Shanghai, China

Luca Berardinelli gives a talk about Modeling, Provisioning, Deployment of IoT/Cloud-based CPS at Fudan University, Shanghai, China Aug 19-20 2016.

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13 June 2017

Ericsson R & D Bangalore

We talk about Resource Slices of IoT, network functions, and cloud and their uncertainties and testing

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