Bachelor and Master Theses

IEC 61499 [1] is an international standard for distributed automation systems that introduces a component-based and event-driven approach to industrial control, offering greater flexibility than the traditional IEC 61131-3 standard. It centers around function blocks, which encapsulate both data and behavior, enabling modular and reusable design. Unlike the cyclic scan model of IEC 61131-3, IEC 61499 uses event-based execution, allowing for more responsive and efficient control. The standard supports the distribution of control logic across multiple devices, making it well-suited for Industry 4.0 and Industrial IoT applications, where scalability, interoperability, and adaptability are key.

In distributed real-time distributed systems, analyzing end-to-end data-propagation delays [2]—such as data age and reaction time—is essential for demonstrating timing predictability. These delays must be computed during the design phase and validated against system timing constraints [3]. While some existing research addresses worst-case execution time [4] and response-time analysis [5] for IEC 61499-based systems, there is currently no method for extracting end-to-end timing models [6,7] from such systems, nor for performing end-to-end data-propagation delay analysis.

This thesis aims to develop a technique to provide model transfromation of software architectures from IEC 61499 to an industrial component model, namely Rubus Component Model [8]. The transformed archtiecture can then be utilized  to perform model-based end-to-end data-propagation delay analysis supported by the Rubus tool chain

Thesis Tasks:

1. Study the modeling of software architectures using function blocks in IEC 61499.
2. Study the modeling of software architectures using Rubus Component Model.
3. Develop a model-transformation approach to automatically translate IEC 61499-based software architectures to Rubus-complaint software architectures.
4. Perform end-to-end data-propagation delay analysis of the translated software architectures with Rubus tool chain.
5. Evaluate the approach using industry-inspired use cases.
6. Document the methodology, approach, results, findings and conclusions in a thesis report.

References:

[1] IEC, IEC 61499-1:2012 Standard- Function blocks – Part 1: Architecture, International

Electrotechnical Commission, Geneva, Switzerland, Nov. 2012.

[2] Matthias Becker, Dakshina Dasari, Saad Mubeen, Moris Behnam, Thomas Nolte, End-to-end timing analysis of cause-effect chains in automotive embedded systems, Journal of Systems Architecture, Volume 80, 2017.

[3] Mubeen, S., Nolte, T., Sjödin, M. et al. Supporting timing analysis of vehicular embedded systems through the refinement of timing constraints. Softw Syst Model 18, 39–69 (2019)

[4] L. Lednicki, J. Carlson, and K. Sandström. Model level worst-case execution time analysis for IEC 61499, 16th International ACM Sigsoft symposium on Component-based software engineering (CBSE), 2013.

[5] P. Lindgren, J. Eriksson, M. Lindner, A. Lindner, D. Pereira and L. M. Pinho, "Response time for IEC 61499 over Ethernet," 13th IEEE International Conference on Industrial Informatics (INDIN), 2015.

[6] Mubeen, S., Gålnander, M., Lundbäck, J., Lundbäck, KL. (2018). Extracting Timing Models from Component-Based Multi-Criticality Vehicular Embedded Systems. In: Latifi, S. (eds) Information Technology - New Generations. Advances in Intelligent Systems and Computing, vol 738. Springer, Cham.

[7] B. Houtan et al., "End-to-end Timing Modeling and Analysis of TSN in Component-Based Vehicular Software," 26th IEEE International Symposium on Real-Time Distributed Computing (ISORC), 2023.

[8] K. Hanninen, J. Maki-Turja, M. Nolin, M. Lindberg, J. Lundback and K. Lundback, "The Rubus component model for resource constrained real-time systems," 2008 International Symposium on Industrial Embedded Systems, Le Grande Motte, France, 2008.

1      The students should be familiar with model-driven engineering, model-based development, component-based software engineering, and model transformations.

2      The students should be familiar with real-time systems, real-time scheduling and schedulability analysis.

3      Good programming/modelling skills.

Potential Compnay collaboration/support: Arcticus Systems AB