Biblio

The Internet of Things (IoT) is a ubiquitous system connecting many different devices - the things - which can be accessed from the distance. The cyber-physical systems (CPSs) monitor and control the things from the distance. As a result, the concepts of dependability and security get deeply intertwined. The increasing level of dynamicity, heterogeneity, and complexity adds to the system's vulnerability, and challenges its ability to react to faults. This paper summarizes the state of the art of existing work on anomaly detection, fault-tolerance, and self-healing, and adds a number of other methods applicable to achieve resilience in an IoT. We particularly focus on non-intrusive methods ensuring data integrity in the network. Furthermore, this paper presents the main challenges in building a resilient IoT for the CPS, which is crucial in the era of smart CPS with enhanced connectivity (an excellent example of such a system is connected autonomous vehicles). It further summarizes our solutions, work-in-progress and future work to this topic to enable ``Trustworthy IoT for CPS''. Finally, this framework is illustrated on a selected use case: a smart sensor infrastructure in the transport domain.

Multirotor Unmanned Aerial Vehicles (UAV) have grown in popularity for research and education, overcoming challenges associated with fixed wing and ground robots. Unfortunately, extensive physical testing can be expensive and time consuming because of short flight times due to battery constraints and safety precautions. Simulation tools offer a low barrier to entry and enable testing and validation before field trials. However, most of the well-known simulators today have a high barrier to entry due to the need for powerful computers and the time required for initial set up. In this paper, we present OpenUAV, an open source test bed for UAV education and research that overcomes these barriers. We leverage the Containers as a Service (CaaS) technology to enable students and researchers carry out simulations on the cloud. We have based our framework on open-source tools including ROS, Gazebo, Docker, PX4, and Ansible, we designed the simulation framework so that it has no special hardware requirements. Two use-cases are presented. First, we show how a UAV can navigate around obstacles, and second, we test a multi-UAV swarm formation algorithm. To our knowledge, this is the first open-source, cloud-enabled testbed for UAVs. The code is available on GitHub: https://github.com/Open-UAV.