Parallel and distributed computing enable the execution of large and complex simulations. Yet, the usual separation of (headless) simulation execution and (subsequent, offline) output analysis often renders the simulation endeavor long and inefficient. ...

Reinforcement Learning (RL) has gained significant momentum in the development of network protocols. However, RL-based protocols are still in their infancy, and substantial research is required to build deployable solutions. Developing a protocol based on ...

Reinforcement learning (RL) is an attractive way to implement high-level decision-making policies for autonomous driving, but learning directly from a real vehicle or a high-fidelity simulator is variously infeasible. We therefore consider the problem ...

The large diffusion of multi-core machines has pushed the research in the field of Parallel Discrete Event Simulation (PDES) toward new programming paradigms, based on the exploitation of shared memory. On the opposite side, the advent of Cloud ...

Software-defined networking (SDN) enables efficient network management. As the technology matures, utilities are looking to integrate those benefits to their operations technology (OT) networks. To help the community to better understand and evaluate ...

In this article, we present the design of a novel parallel architecture simulator called ParTejas. ParTejas is a timing simulation engine that gets its execution traces from instrumented binaries using a fast shared-memory-based mechanism. Subsequently, ...

The emerging software-defined networking (SDN) technology decouples the control plane from the data plane in a computer network with open and standardized interfaces, and hence opens up the network designers’ options and ability to innovate. The wide ...