Abstract
Next generation communication networks will be characterized by the coexistence of multiple technologies and user devices in an integrated fashion. The increasing number of devices owned by a single user will lead to a new communication paradigm: users owning multiple devices that form cooperative networks, and networks of different users that communicate with each other, e.g., acquiring Internet access through each other. In this communication scenario no user intervention should be required and technology should seamlessly adapt to the user's context, preferences, and needs. In this paper we address one of those scenarios, interworking between Personal Area Networks, using legacy technologies and the Ambient Network and Network Composition concepts, herein explained. We argue that new functionalities should be introduced to enable effortless use of legacy technologies in such dynamic and heterogeneous environments. © 2005 IEEE.

Abstract
Ubiquitous Internet access is becoming a major requirement for end-users due to the increasing number of services and applications supported over the Internet. Extending the coverage of current Wi-Fi infrastructures installed in companies, universities and cities, has been considered a solution to help in fulfilling this requirement, namely when it comes to wireless and nomadic Internet access. This paper describes and analyses a new and simple solution, called Wi-Fi network Infrastructure eXtension (WiFIX), aimed at extending current Wi-Fi infrastructures. WiFIX is based on standard IEEE 802.1D bridges and a single-message protocol that is able to self-organize the network, and it only requires software changes in IEEE 802.11 access points (APs); no changes to IEEE 802.11 stations are needed. Overhead analysis and experimental results show both the higher efficiency of the solution compared to the IEEE 802.11s draft standard and its good performance as far as data throughput, delay and packet loss are concerned. Copyright (C) 2010 John Wiley & Sons, Ltd.

Abstract

Abstract

Abstract
Digital twins have been emerging as a hybrid approach that combines the benefits of simulators with the realism of experimental testbeds. The accurate and repeatable set-ups replicating the dynamic conditions of physical environments, enable digital twins of wireless networks to be used to evaluate the performance of next-generation networks. In this paper, we propose the Position-based Machine Learning Propagation Loss Model (P-MLPL), enabling the creation of fast and more precise digital twins of wireless networks in ns-3. Based on network traces collected in an experimental testbed, the P-MLPL model estimates the propagation loss suffered by packets exchanged between a transmitter and a receiver, considering the absolute node's positions and the traffic direction. The P-MLPL model is validated with a test suite. The results show that the P-MLPL model can predict the propagation loss with a median error of 2.5 dB, which corresponds to 0.5x the error of existing models in ns-3. Moreover, ns-3 simulations with the P-MLPL model estimated the throughput with an error up to 2.5 Mbit/s, when compared to the real values measured in the testbed.

Abstract
Flying networks, composed of Unmanned Aerial Vehicles (UAVs) acting as mobile Base Stations and Access Points, have emerged to provide on-demand wireless connectivity, especially due to their positioning capability. Still, existing solutions are focused on improving aggregate network performance using a best-effort approach. This may compromise the use of multiple services with different performance requirements. Network slicing has emerged in 5G networks to address the problem, allowing to meet different Quality of Service (QoS) levels on top of a shared physical network infrastructure. However, Mobile Network Operators typically use fixed Base Stations to satisfy the requirements of different network slices, which may not be feasible due to limited resources and the dynamism of some scenarios.We propose an algorithm for enabling the joint placement and allocation of communications resources in Slicing-aware Flying Access and Backhaul networks- SurFABle. SurFABle allows the computation of the amount of communications resources needed, namely the number of UAVs acting as Flying Access Points and Flying Gateways, and their placement. The performance evaluation carried out by means of ns-3 simulations and an experimental testbed shows that SurFABle makes it possible to meet heterogeneous QoS levels of multiple network slices using the minimum number of UAVs.