TU BRAUNSCHWEIG
| Carl-Friedrich-Gauß-Fakultät | Informatik
Informatikzentrum

Design, Implementation and Evaluation of an online-system for the INGA platform to learn temperature dependency

BetreuerRobert Hartung
ProfessorProf. Dr.-Ing. Lars Wolf
Projektreap
potatonet
petrus
IBR GruppeCM (Prof. Wolf)
ArtBachelorarbeit, Masterarbeit
Statusoffen

Introduction

Wireless Sensor Networks (WSNs) have been researched for many years. However, more recently deployments are focused to be outdoors and therefore are exposed to harsh or challenging environmental conditions. This requires new research on robusness, reliability and efficiency in these networks.

Our experiments have shown that performance of a WSN is dependent on these environmental conditions and especially temperature. Temperature influences metrics - such as the Packet Reception Ratio (PRR) - the most and therefore needs to be supervised. However, the influence and resulting effects are not the same across all sensor nodes. Specifically, it varies on each individual node and pairs of nodes with a few common models.

The effect is that the PRR drops either not at all, at higher temperatures or even at ambient temperature. Therefore, when nowing that the PRR is above a certain threshold (e.g. 50%), not sending packets at all and delaying sending packets until temperature changes can save energy, as retransmissions do not have be made.

Tasks

As the model is not only different for individual types of sensor nodes, but also identical nodes but different links, these temperature dependency should be self-learned on each node separately.

Your tasks in this theses are as following:

  • Design and implement a software that dynamically adapts to environmental conditions
  • Learn about the temperature dependency to all neighbors (links) and react accordingly
  • Integrate your implementation into the RIOT OS
  • Make evaluations on how good your implementation detects the influences by temperature and how reliable it is
  • Both simulations and real experiments are part of your thesis

Skills

The following skills are helpful for the execution of this thesis (not all of them are required!):
  • C
  • Cooja
  • RIOT / Contiki
  • INGA

Links


aktualisiert am 17.11.2017, 14:02 von Robert Hartung
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