M. Haghighi, K. Maraslis, T. Tryfonas, G. Oikonomou, A. Burrows, P. Woznowski

Abstract:
Current applications of Internet of Things (IoT) often require nodes to implement logical decision-making on aggregated data, which involves more processing and wider interactions amongst network peers, resulting in higher energy consumption and shorter node lifetime. This paper presents a game theoretic approach used in Sensomax, an agent-based WSN middleware that facilitates seamless integration of mathematical functions in large-scale wireless sensor networks. In this context, we investigate game theoretic and auction-based techniques to optimise task distribution and energy consumption in IoT networks of multiple concurrent WSNs. We also demonstrate how our proposed game theoretic approach affects the performance of WSN applications with different operational paradigms.
Reference:
M. Haghighi, K. Maraslis, T. Tryfonas, G. Oikonomou, A. Burrows, P. Woznowski, "Game Theoretic Approach Towards Optimal Multi-tasking and Data-distribution in IoT", in Proc. IEEE World Forum on Internet of Things (WF-IoT), pp. 406-411, 2015
Bibtex Entry:
@INPROCEEDINGS{Haghighi-2015-wf-iot,
  title = {Game Theoretic Approach Towards Optimal Multi-tasking and Data-distribution in IoT},
  author = {Mo Haghighi and Konstantinos Maraslis and Theo Tryfonas and George Oikonomou and Alison Burrows and Woznowski, {Przemyslaw R.}},
  publisher = {IEEE},
  year = {2015},
  month = dec,
  booktitle = {Proc. IEEE World Forum on Internet of Things (WF-IoT)},
  pages = {406--411},
  doi = {10.1109/WF-IoT.2015.7389089},
  oa-url = {http://research-information.bristol.ac.uk/en/publications/game-theoretic-approach-towards-optimal-multitasking-and-datadistribution-in-iot(b712d5cf-feb7-4576-9f43-49e5db8cecb1).html},
  gsid = {13613663511745904563},
  abstract = {Current applications of Internet of Things (IoT) often require nodes to implement logical decision-making on aggregated data, which involves more processing and wider interactions amongst network peers, resulting in higher energy consumption and shorter node lifetime. This paper presents a game theoretic approach used in Sensomax, an agent-based WSN middleware that facilitates seamless integration of mathematical functions in large-scale wireless sensor networks. In this context, we investigate game theoretic and auction-based techniques to optimise task distribution and energy consumption in IoT networks of multiple concurrent WSNs. We also demonstrate how our proposed game theoretic approach affects the performance of WSN applications with different operational paradigms.},
}

Game Theoretic Approach Towards Optimal Multi-tasking and Data-distribution in IoT