In the upcoming decade and beyond, the Cooperative, Connected and Automated Mobility (CCAM) initiative will play a huge role in increasing road safety, traffic efficiency and comfort of driving in Europe. While several individual vehicular wireless communication technologies exist, there is still a lack of real flexible and modular platforms that can support the need for hybrid communication. In this paper, we propose a novel vehicular communication management framework (CAMINO), which incorporates flexible support for both short-range direct and long-range cellular technologies and offers built-in Cooperative Intelligent Transport Systems’ (C-ITS) services for experimental validation in real-life settings. Moreover, integration with vehicle and infrastructure sensors/actuators and external services is enabled using a Distributed Uniform Streaming (DUST) framework. The framework is implemented and evaluated in the Smart Highway test site for two targeted use cases, proofing the functional operation in realistic environments. The flexibility and the modular architecture of the hybrid CAMINO framework offers valuable research potential in the field of vehicular communications and CCAM services and can enable cross-technology vehicular connectivity.

The increase of Internet of Things devices and the rise of more computationally intense applications presents challenges for future Internet of Things architectures. We envision a future in which edge, fog, and cloud devices work together to execute future applications. Because the entire application cannot run on smaller edge or fog devices, we will need to split the application into smaller application components. These application components will send event messages to each other to create a single application from multiple application components. The execution location of the application components can be optimized to minimize the resource consumption. In this paper, we describe the Distributed Uniform Stream (DUST) framework that creates an abstraction between the application components and the middleware which is required to make the execution location transparent to the application component. We describe a real-world application that uses the DUST framework for platform transparency. Next to the DUST framework, we also describe the distributed DUST Coordinator, which will optimize the resource consumption by moving the application components to a different execution location. The coordinators will use an adapted version of the Contract Net Protocol to find local minima in resource consumption.

Learning to communicate in order to share state information is an active problem in the area of multi-agent reinforcement learning. The credit assignment problem, the non-stationarity of the communication environment and the problem of encouraging the agents to be influenced by incoming messages are major challenges within this research field which need to be overcome in order to learn a valid communication protocol. This paper introduces the novel multi-agent counterfactual communication learning (MACC) method which adapts counterfactual reasoning in order to overcome the credit assignment problem for communicating agents. Next, the non-stationarity of the communication environment, while learning the communication Q-function, is overcome by creating the communication Q-function using the action policy of the other agents and the Q-function of the action environment. As the exact method to create the communication Q-function can be computationally intensive for a large number of agents, two approximation methods are proposed. Additionally, a social loss function is introduced in order to create influenceable agents, which is required to learn a valid communication protocol. Our experiments show that MACC is able to outperform the state-of-the-art baselines in four different scenarios in the particle environment. Finally, we demonstrate the scalability of MACC in a matrix environment.

More and more devices are connected to the internet. These devices could be used to help execute applications that otherwise would need to be executed on the cloud or on a system with more computational resources. To execute the application on multiple devices, we will split it up into multiple application components that stream events to each other. In this paper we present a framework that allows application components to stream events to each other. On top of this we present a coordinator system to move application components to other devices. This elasticity allows the coordinators to run application components on different devices based on the context, in order to optimize resources such as network usage, response times and battery life. The coordinators use an adapted version of the Contract Net Protocol which allows them to find a local minima in resource consumption. In order to verify this, three use cases are implemented.