This document describes the winning solution to the GNN Challenge 2020 organized by the Barcelona Neural Networking Center for the ITU Artificial Intelligence/Machine Learning in 5G Challenge. We first describe our methodology, then give the set of hyper-parameters that allowed us to achieve the best score with an average relative...
For Internet operators, on-line service providers and end-users, representative operational measurements are crucial to monitor and diagnose the performance of networks and on-line services. While numerous approaches have been proposed to measure performance, only a few works fully adopt an end-user perspective by taking measurements from within web browsers. In...
This paper investigates the task management for cooperative mobile edge computing (MEC), where a set of geographically distributed heterogeneous edge nodes not only cooperate with remote cloud data centers but also help each other to jointly process tasks and support real-time IoT applications at the edge of the network. Especially,...
Mobile edge computing (MEC) is an emerging paradigm that integrates computing resources in wireless access networks to process computational tasks in close proximity to mobile users with low latency. In this paper, we propose an online double deep Q networks (DDQN) based learning scheme for task assignment in dynamic MEC...
This chapter presents the Integrated Lens Antenna (ILA) technology as it evolved since its introduction aiming to respond to the needs of emerging applications such as high-data-rate communication, intelligent transport, and mm-wave imaging. The topics covered include the ILA design concepts as well as the electromagnetic phenomena intrinsic to dielectric...
