The increasing demand for efficient resource allocation in mobile networks has catalyzed the exploration of innovative solutions that could enhance the task of real-time cellular traffic prediction. Under these circumstances, federated learning (FL) stands out as a distributed and privacy-preserving solution to foster collaboration among different sites, thus enabling responsive near-the-edge solutions. In this paper, we comprehensively study the potential benefits of FL in telecommunications through a case study on federated traffic forecasting using real-world data from base stations (BSs) in Barcelona (Spain). Our study encompasses relevant aspects within the federated experience, including model aggregation techniques, outlier management, the impact of individual clients, personalized learning, and the integration of exogenous sources of data. The performed evaluation is based on both prediction accuracy and sustainability, thus showcasing the environmental impact of employed FL algorithms in various settings. The findings from our study highlight FL as a promising and robust solution for mobile traffic prediction, emphasizing its twin merits as a privacy-conscious and environmentally sustainable approach, while also demonstrating its capability to overcome data heterogeneity and ensure high-quality predictions, marking a significant stride towards its integration in mobile traffic management systems.

Harnessing the network slicing feature of the 5G architecture and the mobile cloud computing capabilities offered by Mobile Edge Computing (MEC), mobile edge communication systems are emerging that contribute to the convergence of telecom and cloud services. In this scenario, mobile edge slices can be created and deployed by leveraging multi-cloud infrastructure. However, it becomes difficult for potential users, such as mobile edge slice tenants, to evaluate and select the Cloud Infrastructure Provider (CIP) which best meets their heterogeneous require-ments. Therefore, mobile edge systems require slice brokering to mediate with resource and infrastructure providers, so that mobile edge slice tenants can specify a single set of network and cloud service Key Performance Indicator (KPI) requirements. In this paper we present a new type of broker, the Mobile Edge Slice Broker, that allows designing, provisioning, and orchestrating the deployment and operation of end-to-end mobile edge slices over edge and multi-cloud environments, while maintaining dynamic monitoring, reconfiguration and optimization capabilities.

Deterministic networking allows carrying data flows with low data-loss rates and with bounded latency. A typical use-case is the convergence of Operational Technology (OT) with Information Technology (IT), also known as the Industrial Internet. Wireless networks operate on a shared communication medium where the potential external interference along with multi-path fading impact data packet delivery. By employing diversity in the time, frequency and spatial domains, wireless technologies with scheduled transmissions, such as IEEE Std 802.15.4-2015 Time Slot Channel Hopping (TSCH), can mitigate those effects and provide Reliable and Available Wireless (RAW) communications that approach determinism. Nevertheless, a radio link operating in the ISM band still needs to handle collisions and possibly re-transmission. Therefore, It takes redundant links and paths to provide both the high availability and the near consistent reliability that industrial applications require. In this paper, we present the Packet Automatic Repeat reQuest (ARQ), Replication and Elimination (RE), and Overhearing (PAREO) functions to further increase the Quality of Service (QoS) in industrial networks, even when implemented on top of best-effort traffic in a shared network. The results show that PAREO provides up to approximately 6 times lower Packet Error Rate (PER) and up to approximately 10% higher energy consumption than the default RPL implementation with 7 retransmissions, while keeping jitter and latency as low as default RPL with 1 retransmission.

IEEE Std 802.15.4-2015 Time Slotted Channel Hopping (TSCH) is the de facto Medium Access Control (MAC) mechanism for industrial applications. It renders communications more resilient to interference by spreading them over the time (time slotted) and the frequency (channel hopping) domains. The 6TiSCH architecture bases itself on this new MAC layer to enable high reliability communication in Wireless Sensor Networks (WSNs). In particular, it manages the construction of a distributed communication schedule that continuously adapts to changes in the network. In this paper, we first provide a thorough description of the 6TiSCH architecture, the 6TiSCH Operation Sublayer (6top), and the Minimal Scheduling Function (MSF). We then study its behavior and reactivity from low to high traffic rates by employing the python-based 6TiSCH simulator. Our performance evaluation results demonstrate that the convergence pattern of MSF is the root cause of the majority of packet losses observed in the network. We also show that MSF is subject to over-provisioning of the network resources, especially in the case of varying traffic load.

This paper describes our work on a flexible centralized controller for scheduling wireless networks. The context of this work encompasses wireless networks within the wider Internet of Things (IoT) field and in particular addresses the requirements and limitations within the narrower Industrial Internet of Things (IIoT) sub-field. The overall aim of this work is to produce wireless networking solutions for industrial applications. The challenges include providing high reliability and low latency guarantees, comparable to existing wired solutions, within a noisy wireless medium and using generally computationally- and energy-restrained network nodes. We describe the development of a centralized controller for Wireless Industrial Networks, currently aimed at IEEE Std 802.15.4-2015 Time Slotted Channel Hopping protocol. Our controller takes a high-level network-centric problem description as input, translates it to a low-level representation and uses that to retrieve a solution from a Satisfiability Modulo Theories (SMT) solver, translating the solution back to a higher-level network-centric representation. The advantages of our solution are the ability to gain the added flexibility, higher ease of deployment, and lower deployment cost offered by wireless networks by generating configurable and flexible schedules for these applications.

The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is the de facto routing protocol for Low Power and Lossy Networks (LLNs). It is a proactive and link-layer agnostic routing protocol standardized as RFC 6550 by the Internet Engineering Task Force (IETF). Based on the distance-vector technique, RPL builds a Destination Oriented Directed Acyclic Graph (DODAG) topology. To establish and maintain the routes, RPL uses DODAG Information Object (DIO) control packets, that are transmitted in broadcast, for RPL nodes to propagate the DODAG related information, while its transmission frequency depends on Trickle timer algorithm, i.e., the less stable the network the more DIOs are transmitted. Thus, when a new node intends to join the RPL DODAG, it listens for a DIO message from nearby nodes, which may take a very long time if the network is in a stable state. Therefore, RFC 6550 is equipped with the DODAG Informational Solicitation (DIS) message to solicit DIOs from nearby RPL nodes, similar to the Router Solicitation in IPv6 Neighbor Discovery. However, the solicitation procedure is not the most efficient one, since it resets the Trickle timers in the nodes that receive the DIS message and, thus, they transmit an unnecessarily large number of DIOs that congest the network and consume energy in the nodes. In this paper, we propose to augment RFC 6550, the RPL routing protocol, with additional DIS flags and options that allow a RPL node to better control how the nearby RPL nodes will respond to its solicitation for DIOs. Our performance evaluation in Contiki-NG & COOJA demonstrates that we can reduce the control packets in the network by up to 45.5%.

Wireless industrial networks require reliable and deterministic communication. Determinism implies that there must be a guarantee that each data packet will be delivered within a bounded delay. Moreover, it must ensure that the potential congestion or interference will not impact the predictable properties of the network. In 2016, IEEE 802.15.4 time-slotted channel hopping (TSCH) emerged as an alternative medium access control to the industrial standards such as WirelessHART and ISA100.11a. However, TSCH is based on traditional collision detection and retransmission, and cannot guarantee reliable delivery within a given time. This paper proposes LeapFrog Collaboration (LFC) to provide deterministic and reliable communication over a routing protocol (RPL) based network. LFC is a novel multipath routing algorithm that takes advantage of route diversity by duplicating the data flow onto an alternate path. Simulations and analytical results demonstrate that LFC significantly outperforms the single-path retransmission-based approach of RPL + TSCH and the state-of-the-art LinkPeek solution.

Spam over Internet Telephony (SPIT) is a potential source of disruption in Voice over IP (VoIP) systems. The use of anti-SPIT mechanisms, such as filters and audio CAPTCHA (Completely Automated Public Turing Test to Tell Computer and Humans Apart) can prevent unsolicited calls and lead to less unwanted traffic. In this paper, we present a game-theoretic model, in which the game is played between SPIT senders and internet telephony users. The game includes call filters and audio CAPTCHA, so as to classify incoming calls as legitimate or malicious. We show how the resulting model can be used to decide upon the trade-offs present in this problem and help us predict the SPIT sender’s behavior. We also highlight the advantages in terms of SPIT call reduction of merely introducing CAPTCHA, and provide experimental verification of our results.