Speaker: Dr. Maryline Chetto, Nantes Universite, France

Title of Talk: What real-time operating system for energy autonomous sensors?

Biography: Maryline Chetto is currently a full professor in computer engineering with Nantes Université, France and researcher with CNRS. She received the degree of Docteur de 3ème cycle in control engineering and the degree of Habilitée à Diriger des Recherches in Computer Science from the University of Nantes, France, in 1984 and 1993, respectively. From 1984 to 1985, she held the position of Assistant professor of Computer Science at the University of Rennes, while her research was with the Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Rennes. In 1986, she returned to Nantes and has been from 2002 a full professor with the University of Nantes. She is conducting her research at Laboratoire des Sciences du Numérique de Nantes (LS2N, UMR CNRS n° 6004) in the Real Time System group.

Her research has been focused on development and formal validation of solutions regarding Scheduling, Fault-tolerance and Dynamic Power Management in real time embedded applications. Her current research is specifically targeting real-time scheduling issues in energy neutral sensors. She has more than 150 papers published in international journals and conferences. She was the editor of the books Real-time Systems Scheduling (Elsevier, 2014) with volume 1 Fundamentals and Volume 2 Focusses. She was the co-author of the book Energy Autonomy of real-time systems (Elsevier, 2016). She was general chair of the 2020 IEEE International Conference on Green Computing and Communications (GreenCom-2020). Since 2011, she was elected member of the French National Council for Universities.

Talk description: With the rapid development of the Internet of Things, energy autonomous systems have been in the focus of researchers in recent years. Such systems, mainly including wireless sensors, should be designed to function perpetually without any human intervention because either costly or impractical. Energy harvesting has emerged as a feasible option to supply wireless sensors and to permit them energy neutral operation. Nonetheless, the energy environmental source is fluctuating and not controllable. Hence, specific power management and scheduling solutions have to be conceived so as to prevent energy starvation and guarantee real-time responsiveness. Task scheduling in the sensor node should take into account not only the timing parameters of the deadline constrained tasks but also the characteristics of the energy source and the capacity of the energy storage unit. Neither the classical greedy scheduler Earliest Deadline First (EDF) nor Rate Monotonic (RM) are suitable for this novel operational context. This keynote addresses state of the art as well as our findings in real-time scheduling and dynamic processor management for energy harvesting small electronic devices with real-time requirements.