Poster: Towards a Cognitive MAC Layer: Predicting the MAC-level Performance in Dynamic WSN using Machine Learning

نویسندگان

  • Merima Kulin
  • Eli De Poorter
  • Tarik Kazaz
  • Ingrid Moerman
چکیده

Predictable network performance is key in many lowpower wireless sensor network applications. In this paper, we use machine learning as an effective technique for realtime characterization of the communication performance as observed by the MAC layer. Our approach is data-driven and consists of three steps: extensive experiments for data collection, offline modeling and trace-driven performance evaluation. From our experiments and analysis, we find that a neural networks prediction model shows best performance.

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تاریخ انتشار 2017