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Software-defined networking (SDN) is an innovative technology that aims to improve the network control, while providing an improved usage of virtual resources deployed across modern networks. Recently, telco operators started to adapt the SDN technology in their transport networks, thus boosting the research activities around the Transport-SDN (T-SDN) paradigm. The integration of SDN in transportation networks, however, poses numerous challenges related to the design of efficient routing approaches, working in large-scale and distributed networks. In this context, this paper investigates the design issues addressed by the current scientific literature and provides a cross-comparison of routing techniques published during recent years. The analysis of key features and drawbacks characterizing the reviewed methodologies reveals the lack of routing strategies that could ensure both energy effectiveness and better bandwidth requirements also known as quality of service in a real-time scenario, which is the primary requirement of the modern large-scale telecommunication networks.

Smart mobility embraces many services that require the exchange of huge amount of data between mobile consumers (e.g., vehicles, drones, smartphones) and fixed producers (e.g., cloud servers). Information Centric Networking emerged more than one decade ago as a suitable approach to build the Future Internet, offering flexible communication primitives for data exchange and native support to mobility. Unfortunately, baseline schemes do not take care of stale forwarding information generated into the core network because of consumer mobility and, as a consequence, it leads to an important waste of bandwidth and a higher energy consumption. An SDN-aided Information-Centric Networking approach has been recently formulated by the same authors of this contribution as a valid solution for the aforementioned issue. This paper further extends these promising research results by evaluating the impact of the amount of energy consumed by intermediary routers. The conducted tests demonstrate the proposed solution effectiveness through computer simulations, by considering different network, mobility, and application scenarios.

In Industrial Internet of Things (IIoT) networks, end-nodes may disconnect or become no longer reachable, due to manifold causes, such as battery discharge, network interference and/or packet collisions. Overall, this could lead to low Quality of Service (QoS) levels. To satisfy application requirements, i.e., reliability, it is mandatory to continuously monitor connectivity and properly managing disconnections, without causing signaling overhead. The optimization of the exchange of messages can be pursued thanks to dedicated communication slots, eventually rescheduled in cases of deletion, replacement or dynamic reassignments. This solution lowers energy consumption while accounting for a number of improvements in network operative conditions. In this work, network formation optimization mechanisms for IPv6 over the TSCH mode of IEEE 802.15.4 (6TiSCH) networks are analyzed in real use cases in which the number of nodes in the network varies over time. Once the network was fully connected, a performance analysis has been carried out in order to measure typical networks parameters, such as latencies and Packet Loss Ratio (PLR). The study has proven the effectiveness of dedicated slots dynamic assignment. In particular, it has been measured a sensible reduction of latencies and losses of information. The obtained results pave the way towards robotics-aided set up of Internet of Things (IoT) networks in industrial contexts.

The many fold capacity magnification promised by 5G vehicular networks will likely provide massive multimedia services, including infotainment, augmented reality, location services, etc. However, the large-scale and stochastic characteristic of these burgeoning multimedia applications will lead to an exponential increase of traffic in vehicular networks. Meanwhile, the diversified requirements introduced by the coexistence with traditional services will also bring new challenges to the efficient usage of resources. To cope with the above challenges, we propose a novel Stochastic Optimization framework for Pricing-aware Multimedia Services (SOPMS) in this paper, which targets the maximization of utility with the constraints of system stability and traffic pricing policy. Specifically, we leverage the Lyapunov function to address this optimization objective, which is decomposed into three tractable subproblems. For each problem, a distinct algorithm is conceived, i.e. Quality of Experience (QoE) based utility maximization, cooperative resource allocation and pricing-based transmission control. Finally, validated by the simulations, our proposed SOPMS preserves the optimality and significantly improves the queue stability and service utility, in comparison with other state-of-the-art solutions.

Detecting disruptive events, such as earthquakes, using environmental monitoring systems is a particularly promising, but rather challenging, opportunity. The Internet of Things (IoT) can play a significant role in characterizing and predicting seismic events. The present contribution introduces QuakeSense, an open-source earthquake and weather monitoring system. The implemented IoT system is configured as a Long Range (LoRa)-based star topology with a fully energy-autonomous sensor node. The system leverages some of the most useful features of two emerging IoT technologies, e.g., LoRa and Message Queue Telemetry Transport (MQTT), and enables the near real-time monitoring of seismic events through a web-based interface. An experimental campaign has been carried out to verify the current consumption and, therefore, the battery lifetime of the sensor node. Moreover, LoRa parameters have been extensively tested as to evaluate performances in several configurations. The obtained results in terms of latency and Packet Delivery Ratio (PDR) demonstrated the reliability of the proposal.

Smart agriculture is a promising Internet of Things (IoT) application domain in the Industry 4.0 framework. Climate changes affect the natural resources exploitation policies becoming a serious matter in the agricultural and food production context. Continuous monitoring of environmental parameters and agricultural processes automation can lead to resources optimization and production maximization. This work proposes both the conceptual model and the design of Solarfertigation, an IoT system, specifically designed for smart agriculture. In particular, the envisioned solution is able to detect some of the most meaningful terrain parameters to feed a decision-making process that drives automated fertilization and irrigation subsystems. In addition, to attain energy self-sustainability, Solarfertigation is powered by a photovoltaic plant. The key features of Solarfertigation are illustrated throughout this contribution together with its preliminary prototype implementation.

Internet of Things (IoT) is a key pillar in various smart-* domains, including smart home, smart building, intelligent transportation systems, industrial Internet, to name a few. Its potential in terms of value creation is extraordinary, according to economic estimates from many market sectors. At the same time, there are some technical challenges to face, which could refrain IoT adoption. In this study, the attention is focused on interoperability and data quality issues from a pragmatic standpoint. In particular, a real smart building testbed has been set-up by integrating two different IoT platforms: TLSensing and NetwOrked Smart Object (NOS). The former has been developed to enable the quick deployment of a IPv6 over the TSCH mode of IEEE 802.15.4e (6tisch) IoT network and to expose the data gathered from sensors through a web interface. The latter is a middleware that handles heterogeneous data sources and offers a unifying view to users. The resulting IoT system is able to: (i) gather data from multiple sources, including multimedia ones; (ii) expose network resources to user through a common interface; (iii) enforce security and data quality checks. The performance of this system has been experimentally analyzed to demonstrate a satisfactory responsiveness and ability to meet the aforementioned requirements.

Cyber foraging techniques have been proposed in edge computing to support resource-intensive and latency-sensitive mobile applications. In a natural or man-made disaster scenario, all cyber foraging challenges are exacerbated by two problems: edge nodes are scarce and hence easily overloaded and failures are common due to the ad-hoc hostile conditions. In this paper, we study the use of efficient load profiling and migration strategies to mitigate such problems. In particular, we propose FORMICA, an architecture for cyber foraging orchestration, whose goal is to minimize the completion time of a set of jobs offloaded from mobile devices. Existing service offloading solutions are mainly concerned with outsourcing a job out of the mobile responsibility. Our architecture supports both mobile-based offloading and backend-driven onloading i.e., the offloading decision is taken by the edge infrastructure and not by the mobile node. FORMICA leverages Gelenbe networks to estimate the load profile of each node of the edge computing infrastructure to make proactive load profiling decisions. Our evaluation on a proof-of-concept implementation shows the benefits of our policy-based architecture in several (challenged disaster) scenarios but its applicability is broad to other IoT-based latency-sensitive applications.

Information-Centric Networking (ICN) focuses on data dissemination instead of host communication, and it is a promising solution for video streaming in Vehicular Ad-hoc Networks (VANETs). In Information-Based VANETs, content copies can be cached by arbitrary mobile nodes in the networks. Thus, it is required to optimize the routing of content requests (referred to as Interest packets) in order to quickly locate potential content providers as soon as possible. This article proposes a Preference-aware Fast Interest Forwarding for video streaming in ICN-based VANETs (PaFF). In PaFF, each mobile user creates a Highly Preferred Content Table (HPCT) to maintain the content caching status of nodes who have similar mobility patterns and video playback behavior. Based on HPCT, a preference-aware forwarder selection mechanism is proposed to select the next hop of Interest packets in order to minimize latencies and maximize reliability. Simulation results show that PaFF achieves a considerable improvement in terms of start-up delay and cache hit ratio while incurring almost the same overhead with respect to state-of-art solutions.

Security, interoperability, scalability, and mobility support are key challenges for the Internet of Things (IoT). Information Centric Networking (ICN) is an emerging paradigm for the Future Internet design that brings all the potential to face these challenges thanks to name-driven networking primitives. As a matter of fact, ICN natively supports multicast, mobility, content oriented security, and can be effectively used to design de-verticalizing middlewares for the IoT. In this context, the so called ICN-IoT middleware has been proposed within an initiative of the ICNRG (Information Centric Networking Research Group) of the Internet Research Task Force (IRTF) to encompass the key requirements of IoT systems. An important issue to be addressed is how to guarantee the security and the privacy of the information transmitted over the network, which may include sensitive data. Herein, the current security functionalities of ICN-IoT are analyzed and enriched in order to strengthen its resilience to violation attempts. The proposed approach is validated, at a design level, by means of a running example.

Originally envisioned to tackle the massive content distribution in today's Internet, the Information-Centric Networking (ICN) has turned out to be a promising paradigm for different network scenarios, including Vehicular Ad Hoc Networks (VANETs). Data retrieval independent from specific recipients bound to fixed physical locations could be a key enabler for future vehicular networks, fixing old unsolved issues of mobility management in classical IP-based systems. As an evidence, several preliminary investigations have been performed on a widely known ICN instance, i.e., the Named-Data Networking (NDN). Nevertheless, the NDN architecture presents a new set of security vulnerabilities. Interest flooding attacks, cache poisoning attacks and privacy violation attacks by means of content names represent concrete NDN threats. While the benefits offered by NDN to vehicular networks have been partially investigated, the impact of major security threats stays unclear. Therefore, this paper opens a more comprehensive discussion of the security risks brought by the application of NDN solutions in VANETs. This is a fundamental first step toward the future design of suitable related countermeasures.