Digital Twins (DTs) have been proposed as digital replicas of physical entities (e.g., manufacturing equipment), which one can observe in real-time and interact with. Digital Twins of Networks (DTNs) are increasingly being discussed in the literature, as an enabler for efficient data-driven network management and performance-driven network optimization (e.g., to support dynamic reconfiguration, or anticipate the effects of faults). A DTN includes service mapping models, i.e. models that can be fed with acquired data to produce insight on the network itself - e.g., to run what-if scenarios, based on multiple underlying technologies, from Machine Learning to analytical models, e.g. Markov Chains. In this paper we examine the case of DTNs of mobile networks, DTMNs, tailored to 5G and beyond, where issues of dynamic reconfiguration and fault anticipation are critical. We argue that simulation services should be offered by the DTMN in order to allow performance-driven network optimization, and that discrete-event network simulators are ideal instruments to be employed for this purpose. We discuss the challenges that need be addressed to make this happen, e.g., centralized vs. distributed implementation, gathering input from the physical network, security issues and hosting, and we review the possibilities offered by network simulation in terms of what-if analysis, defining the concepts of lockstep and branching analysis. We present a framework to endow a DTMN with simulation services and we exemplify it using Simu5G, a popular 5G/B5G simulation library for OMNeT++, as a reference case study.

The quest for trustworthiness in Artificial Intelligence (AI) is increasingly urgent, especially in the field of next-generation wireless networks. Future Beyond 5G (B5G)/6G networks will connect a huge amount of devices and will offer innovative services empowered with AI and Machine Learning tools. Nevertheless, private user data, which are essential for training such services, are not an asset that can be unrestrictedly shared over the network, mainly because of privacy concerns. To overcome this issue, Federated Learning (FL) has recently been proposed as a paradigm to enable collaborative model training among multiple parties, without any disclosure of private raw data. However, the initiative to natively integrate FL services into mobile networks is still far from being accomplished. In this paper we propose a novel FL-as-a-Service framework that provides the B5G/6G network with flexible mechanisms to allow end users to exploit FL services, and we describe its applicability to a Quality of Experience (QoE) forecasting service based on a vehicular networking use case. Specifically, we show how FL of eXplainable AI (XAI) models can be leveraged for the QoE forecasting task, and induces a benefit in terms of both accuracy, compared to local learning, and trustworthiness, thanks to the adoption of inherently interpretable models. Such considerations are supported by an extensive experimental analysis on a publicly available simulated dataset. Finally, we assessed how the learning process is affected by the system deployment and the performance of the underlying communication and computation infrastructure, through system-level simulations, which show the benefits of deploying the proposed framework in edge-based environments.

Digital Twins (DTs) have been proposed as digital replicas of physical entities (e.g., manufacturing plants), which one can observe and interact with, e.g., to perform what-if analysis. In this paper, we argue that mobile networks need DTs as well, and network simulators appear to be promising candidates to fulfill that role. We discuss the challenges that need be addressed to make this happen, e.g., centralized vs. distributed implementation, gathering input from the physical network, security issues and hosting, and the possibilities offered by network simulation in terms of what-if analysis, defining the concepts of lockstep and branching analysis. We exemplify the above concepts using Simu5G, a popular 5G/B5G simulation library for OMNeT++, as a reference case study.

Bitcoin-based smart city services are an ever increasing up-and-coming reality. For these services, simulating the Bitcoin blockchain is important to parametrize the system and tailor the costs and the economic incentives. In this regard, SimBlock simulator is the current state-of-the-art tool for blockchain simulations. Unfortunately, based on an up-to-date parametrization, SimBlock turns out not to simulate the mining of blocks. Furthermore, it does not simulate the incentive mechanism. These limitations strongly confine SimBlock's effective usage towards evaluating Bitcoin-based services relevant to many application contexts, including smart cities. To overcome these limitations, we propose an improved SimBlock's implementation. Upon it, we assess whether SimBlock can abstract the current Bitcoin blockchain. The experimental analysis shows that the proposed implementation can effectively simulate the current Bitcoin blockchain. Though, introducing relay network modelling in SimBlock should even improve the accuracy of the simulation.

Multi-access Edge Computing (MEC) allows users to run applications on demand near their mobile access points. MEC applications will exploit 5G infrastructure, and they will have to be designed by taking into account the characteristics of 5G mobile networks. This work describes how to use a system-level simulator of 5G networks - namely Simu5G, which evolves the popular 4G network simulator SimuLTE - as a real-time 5G net-work emulator. This allows designers of networked applications - and MEC ones in particular - to use it as a testbed during the deployment. We describe the system setup of Simu5G as an emulator, and its emulation capabilities and scale. Moreover, we present a case study of a MEC testbed using Intel's Open Network Edge Services Software (OpenNESS) toolkit, based on a recent demon-stration in 5GAA (5G Automotive Association).

This paper presents Simu5G, a new OMNeT++-based system-level simulator of 5G networks. Simu5G is built starting from the SimuLTE simulation library, which models 4G (i.e., LTE/LTE-A) networks, and is compatible with the latter, thus allowing the simulation of 4G-5G coexistence and transition scenarios. We discuss the modelling of the protocol layers, network entities and functions, and validate our abstraction of the physical layer using 3GPP-based scenarios. Moreover, we report profiling results related to Simu5G execu-tion, and we describe how it can be employed to evaluate Radio Access Network configurations, as well as end-to-end scenarios involving communication and computation, e.g., with Multi-access Edge Computing ap-plications.

Cellular network nodes should be dynamically switched on/off based on the load requirements of the network, to save power and minimize inter-cell interference. This should be done keeping into account global interference effects, which requires a centralized approach. In this paper, we present an architecture, realized within the Flex5GWare EU project, that manages a large-scale cellular network, switching on and off nodes based on load requirements and context data. We describe the architectural framework and the optimization model that is used to decide the activity state of the nodes. We present simulation results showing that the framework adapts to the minimum power level based on the cell loads.

One-to-one device-to-device (D2D) communications are expected to play a major role in future releases of LTE-A, as well as in future 5G networks . Despite the abundance of works on resource allocation for D2D communications, few works, if any, discuss how D2D should be realized within the LTE-A protocol stack. While it is generally understood that D2D endpoints should be able to communicate both on the direct path or sidelink (SL) and on the relayed path (RP) through the eNB, little has been said on how this can be achieved in practice. In this paper we present a comprehensive proposal for a data-plane architecture for D2D communication: we define how communications should occur on the SL and the RP, and propose a solution for the challenges associated with mode switching between the SL and the RP. In particular, we argue that two different communication modes on the RP are required to allow D2D connections to be kept alive across cell borders in a multicell environment. Our proposal is scalable, since it does not require any signaling, and is guaranteed to not introduce losses. We evaluate our proposal through detailed system-level simulations, also focusing on its interplay with transport-layer protocols.

In an LTE-Advanced network, network-controlled Device-to-Device (D2D) communications can be combined in a multihop fashion to distribute broadcasts over user-defined (and possibly large) areas, with small latencies and occupying few resources. Such a service may be exploited for several purposes, (e.g. Internet of Things, Vehicular communications). Engineering a multihop D2D-based broadcast service requires working at both the application level on the User Equipment (UE) and at the resource-allocation level within the eNodeBs. This paper describes the necessary modifications at both the UE and the eNodeB, what the main issues are, and how to solve them efficiently. We evaluate the performance of the above service using system-level simulations, and demonstrate its advantages over standard broadcasting techniques.

Direct (or device-to-device, D2D) communications are being investigated in the framework of LTE- Advanced. They allow one-to-one communications between two endpoints, under the control of the eNodeB, which allocates resources for the d2d flow, but does not act as a relay for its traffic. The direct link can also be used for file transfer or proximity-based browsing, i.e. applications running on TCP. In this paper, we evaluate the performance of TCP-based traffic transported through the direct link, in several scenarios. We show and explain non-intuitive results, which arise from the interplay of TCP and LTE-A protocol mechanisms, and compare the existing TCP versions in a dynamic environment, where mode switches between the direct and the infrastructure link may induce periodic losses.

Direct (or D2D) communications allow two UEs to communicate without passing through the eNodeB. However, the two UEs may still need to relay their communication through the eNB from time to time, hence should be able to switch from the direct to the re-layed mode seamlessly, without this affecting the QoS. In this paper we show that in conventional systems a mode switching may cause relevant losses, and propose two architectures to miti-gate or solve this problem. Our proposals do not require extra signaling or additional functionalities to be added to the network, hence are scalable and inexpensive. We assess their effectiveness through detailed system-level simulations.