Ph.D. thesis Safe, efficient and low-energy self-adaptation for Cyber Physical Systems-Application to a scientific observatory in the Arctic tundra

In the DAO project (https://en.uit.no/project/dao), led by Otto Anshus, a scientific observatory, consisting of a set of autonomous distributed observation units (OUs), is deployed on the arctic tundra during the polar winter to study the impact of climate change on ecosystems. A Cyber-Physical System (CPS) is being built in the DAO project. It is composed of OUs with sensors (e.g. temperature, pressure, CO2 sensors), actuators (e.g flash lights), computing, and storage resources (e.g., Raspberry Pi) on which are available a set of small services (i.e., micro-services) for observations, storage, computations, network, etc. Each OU is deployed during the summer and can be inaccessible for more than 6 months due to weather conditions and the dangers of the Arctic Tundra during the winter. Hence, once deployed those OUs have to be autonomous and have to collaborate to make and coordinate scientific observations for scientists. This requires that OUs are able to self-manage, in other words to self-adapt to dynamic changes in their environment (faults, dynamic requirements from scientists, new point of interest in the environment, etc.). Furthermore, each OU is subject to strong uncertainties and constraints. First, energetic constraints, because OUs are only equipped with batteries [5]. Second, computing and storage constraints, because resources in CPS are limited and possibly heterogeneous. Third, autonomous constraints, because most of the time OUs are disconnected from a network (for energy savings and unavailability of the network) [4].