Seminar System Architecture and Networking (2IMN00) autumn 2017 (for BIS, CSE, and ES)


Last update: November 28th, 2017.




·         2017-11-28: Allocation of topics and papers + 2 new papers added.

·         2017-11-21: (Minor) changes to the schedule.

·         2017-11-15: The topics have been updated.

·         2017-11-13: The web-page has been created.



On this site the current status of the course will be maintained in terms of the contents, and expected reading. Assignments and presented slides will only be available from CANVAS.



This seminar the SAN group addresses the latest developments in the system and software architecture and networking areas, which did not yet find a place in the regular curriculum. We involve students in ongoing research, and give them practical training in presenting material, scientific writing and studying the literature. This course is especially, but not exclusively, intended for students that want to graduate in the area of system architecture and networking.

Previous topics were transport protocols, wireless networks, software architecture, wireless sensor networks, resource management in networked systems, and cloud-supported multimedia services for smart homes.

This year, we address the following topics:

1.    Applications of machine learning;

2.    Virtualized Decentralized IoT;

3.    Resource management in networked systems: Resource Access Protocols (RAPs) for Multi-processor Systems.

For each individual topic there will be an assignment, which needs to be made by a team of 2 to 3 students.


Course objectives (content-wise):

Knowledge: Students can explain aspects (principles, techniques, and metrics) of cloud-based services, multi-media services, smart context-aware service, and resource management.


·         Applications of machine learning: Students have an insight into the implementation of a machine learning application on an example of face recognition solution.

·         Virtualized Decentralized IoT: Students have insight into how to create virtual IoT networks out of legacy systems and how to realize fully decentralized applications on them, considering interoperability with other IoT systems. 

·         RAPs for Multi-processor Systems: Students have an insight in the approaches for RAPs for Multi-processor Systems, their relative strength and weaknesses, and their demands on a developer as well as the platform.


Course objectives (field):

The students have become acquainted with typical issues in the System Architecture and Networking field. They can study scientific literature and have improved presentation and writing skills.




There will be a set of lectures accompanied by a practical assignment.

Registration is via CANVAS.


Students are expected to:

·         be present at all lectures;

·         give one presentation (i.e. a lecture of 1 hour) addressing a specific article from a given set provided by the teachers;

·         read all articles that will be presented and to hand-in (two or) three questions (to the responsible lecturer) concerning every article prior to the lecture addressing it;

·         do an assignment (as a team of 2 or 3 students), for which a research paper has to be written.

The assignment will be based on studying some given papers and writing about a given research question, which may involve experiments.

The research paper consists of 6-8 pages, normal margins, 11pt.

Course program (preliminary):

Quartile 2 (November 13th, 2017 - February 2nd, 2018):

Week 1: (15 - 11) Cancelled due to problems with the “MyTimetable

: (17 - 11) Overview of the course.
                Introductory lectures on some other topics.
                Distribution of papers to read and assignments to make.

Week 2: (22 - 11) No classes!

          : (24 - 11) Introductory lecture on “Doing research” by dr. Tanir Ozcelebi.
                         Introduction on “Applications of Machine Learning” by Mike Holenderski.

                         Allocation of papers to present and discussion about the assignment to make

Week 3: (29 - 11) No classes! (Preparation for presentations)

          : (01 - 12) No classes! (Preparation for presentations)

Week 4: (06 - 12) No classes! (Preparation for presentations)

          : (08 - 12) No classes! (Preparation for presentations)

Week 5: (13 - 12) Student presentations (Preliminary) Topic 1 (Applications of Machine Learning):

·         T. van Tien - [3] Otto, Klare & Jain, 2015;

·         J. Li           - [2] Lin et al., 2017.

          : (15 - 12) Student presentations (Preliminary) Topic 1 (Applications of Machine Learning):

·         S. Sharma  - [1] Otto & Jain, 2017.

Week 6: (20 - 12) Student presentations (Preliminary) Topic 2 (Virtualized Decentralized IoT):

·         S. Ravi        - [1] Rahman et al. 2016;

·         K. Bimpisidis - [2] Derhamy et al., 2015;

          : (22 - 12) Student presentations (Preliminary) Topic 2 (Virtualized Decentralized IoT):

·         J. Nagdeo    - [3] Bui et al., 2011;

·         S. Sistu       - [4] Mataric, 1993.

Nc-CH : (27 - 12) No classes (Christmas Holidays).

          : (29 - 12) No classes (Christmas Holidays).

          : (03 - 01) No classes (Christmas Holidays).

          : (05 - 01) No classes (Christmas Holidays).

Week 7: (10 - 01) No classes! (Work on assignment)

          : (12 – 01) <Draft version of the report shall be delivered> No classes! (Work on assignment)

Week 8: (17 - 01) No classes! (Work on assignment)

          : (19 – 01) Student presentations and demos on assignments.

Week 9: (24 - 01) Examination week; no classes.

          : (26 - 01) Final version of the report to be delivered. Examination week; no classes.

Week 10:(31 - 01) Examination week; no classes.

          : (02 - 02) Examination week; no classes.

Time & Location:


Quart \ Day

Wednesday: 15:45 - 17:30

Friday: 10:45 - 12:30


PAV A12 b



Changes: see in the schedule above!

Examination: There will be no (written!) exam for 2IMN00. Instead, grading is based on the questions handed in (25%), presentation (35%), and the assignment (40%). All parts are mandatory.

Assignments: Will become available via CANVAS.

Lecturers: R.J. Bril

          Bldg.: MF 6.068, tel.: 5412, homepage

Dr. D.S. Jarnikov

          Bldg.: MF 6.122b, tel.: 8311, homepage

Dr. T. Ozcelebi

          Bldg.: MF 6.066, tel.: 4426, homepage


Expected reading (Final):

All articles listed below can be found by means of IEEE Xplore.

Topic 1: Application of machine learning

[1]   Otto, C., & Jain, A. (2017). Clustering millions of faces by identity. IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]   Lin, W. A., Chen, J. C., & Chellappa, R. (2017). A Proximity-Aware Hierarchical Clustering of Faces. arXiv preprint arXiv:1703.04835.

[3]   Otto, C., Klare, B., & Jain, A. K. (2015, May). An efficient approach for clustering face images. In Biometrics (ICB), 2015 International Conference on (pp. 2 43 -250), IEEE.

Topic 2: Virtualized Decentralized IoT

[1]  Hasan Derhamy, Jens Eliasson, Jerker Delsing, Peter Priller. “A survey of Commercial Frameworks for the Internet of Things”. In Proc. IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), pages 1-8, Sept 2015.

[2]  Leila F. Rahman, Tanir Ozcelebi and Johan J. Lukkien, "Choosing Your IoT Programming Framework: Architectural Aspects," In Proc. IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud), Vienna, 2016, pp. 293-300. doi: 10.1109/FiCloud.2016.49

[3]  V. Bui, J.J. Lukkien, E. Frimout, G. Broeksteeg, “Bridging light applications to the IP domain, IEEE International Conference on Consumer Electronics (ICCE), 2011.

[4]  M.J. Mataric, “Designing Emergent Behaviors: From Local Interactions to Collective Intelligence,” Proc.  2nd  Int’l  Conf.  Simulation of Adaptive Behavior,  1993,  pp. 432–441.


Topic 3: Resource management in networked systems not covered in 2017/2018


[1]  P. Gai, M. Di Natale, G. Lipari, A. Ferrari, C. Gabellini, and P. Marceca, A comparison of MPCP and MSRP when sharing resources in the Janus multiple-processor on a chip platform, In: Proc. 9th IEEE Real-Time and Embedded Techn. and Appl. Symp. (RTAS), pages 189–198, May 2003.

[2]  S. Afshar, M. Behnam, R. Bril, and T. Nolte, Flexible spin-lock model for resource sharing in multiprocessor real-time systems, In: Proc. 9th IEEE Int. Symp. on Industrial Embedded Systems (SIES), pages 41–51, June 2014.

[3]  S.M.N. Balasubramanian, S. Afshar, P. Gai, M. Behnam, and R.J. Bril, Incorporating implementation overheads in the analysis for the Flexible Spin-Lock Model, In: Proc. 43rd Annual Conference of the IEEE Industrial Electronics Society (IECON), October 2017.