Time-Triggered Internet of Things
Master Thesis Topic
Contact/Assistant Advisor: Bernhard Frömel <[email protected]>
Advisor: Prof. Peter Puschner
If we augment physical objects of the real world (i.e., things) with sensors,
actuators and communication as well as computational means, we can network
them and give them a virtual representation in a cyberworld called the Internet of
Things (IoT)[1]. These augmented objects can interact in the IoT to cooperatively
achieve diverse goals such as asset location tracking, avoidance of traffic jams, or
weather prediction. Enabling technologies for the IoT are the (mostly) TCP/IP
based Internet, availability of cheap and energy-efficient computing platforms and
the recent advancements in wireless communications (e.g., NFC, WiFi, RFID, . . . ).
In a time-less IoT, guarantees about response times are difficult to achieve.
However, guaranteed response times are a requirement for most cyber-physical
systems that rely on temporally accurate input such that the controlled physical
plant (efficiently) reaches a desired state. This master’s thesis topic concerns the
design and implications of a time-triggered IoT where guaranteed responsiveness
is established by:
• the introduction of a distributed, sparse global-time base with bounded precision,
• sufficient definitions of interfaces of things in information- and time-domain,
• self-organized service discovery, and
• a strong focus on robustness in the design of services realized by things.
Specific master’s thesis topics may be selected around designing, implementing,
or extending an IoT framework (e.g., Google ROS1 , Contiki-OS2 ). Besides a thorough literature study that compares related/existing research (e.g., distributed
sensor networks[2]) a suitable case-study showing the benefits of a time-controlled
IoT shall be developed, e.g.,
• WiFi/NFC based clock synchronization of things, Failure models, fault tolerance (e.g., w.r.t. common mode failures).
• Wifi based real-time location tracking service (possibly based on approaches
like [4][5]): obtain relative location to other things.
1
2
http://ros.org
http://contiki-os.org
• Deterministic wireless networks [6][7], routing and service discovery [3].
• Multi agent-based microscopic Time-Triggered IoT simulation framework.
References
[1] L. Atzori, A. Iera, and G. Morabito. The internet of things: A survey. Computer
networks, 54(15):2787–2805, 2010.
[2] L. P. Clare, G. J. Pottie, and J. R. Agre. Self-organizing distributed sensor
networks. In AeroSense’99, pages 229–237. International Society for Optics
and Photonics, 1999.
[3] Y. Ding, Y. Jin, L. Ren, and K. Hao. An intelligent self-organization scheme for
the internet of things. Computational Intelligence Magazine, IEEE, 8(3):41–53,
2013.
[4] B. Ferris, D. Haehnel, and D. Fox. Gaussian processes for signal strength-based
location estimation. In In Proc. of Robotics Science and Systems. Citeseer,
2006.
[5] J. Rekimoto, T. Miyaki, and T. Ishizawa. Lifetag: Wifi-based continuous
location logging for life pattern analysis. In LoCA, volume 2007, pages 35–49,
2007.
[6] H. Trsek, L. Wisniewski, E. Toscano, and L. Lo Bello. A flexible approach for
real-time wireless communications in adaptable industrial automation systems.
In Emerging Technologies & Factory Automation (ETFA), 2011 IEEE 16th
Conference on, pages 1–4. IEEE, 2011.
[7] Y.-H. Wei, Q. Leng, S. Han, A. K. Mok, W. Zhang, and M. Tomizuka. Rtwifi: Real-time high-speed communication protocol for wireless cyber-physical
control applications. In Real-Time Systems Symposium (RTSS), 2013 IEEE
34th, pages 140–149. IEEE, 2013.