It is anticipated that SDN coupled with NFV and cloud computing, will become a critical enabling technology to radically revolutionize the way network operators will architect and monetize their infrastructure. On the other hand, the Internet of Things (IoT) is transforming the interaction between cyberspace and the physical space with a tremendous impact on everyday life. The effectiveness of these technologies will require new methodological and engineering approaches due to the impressive scale of the problem and the new challenging requests in terms of performance, security and reliability. This paper presents a simple and general SDN-IoT architecture with NFV implementation with specific choices on where and how to adopt SDN and NFV approaches to address the new challenges of the Internet of Things. The architecture will accelerate innovations in the IoT sector, thanks to its flexibility opening new perspectives for fast deployment of software-enabled worldwide services. The paper also look at the business perspective by considering SDN and NFV as enablers of new added value services on top to the existing infrastructure providing more opportunities for revenues leveraging fast deployed services in the value chain.

Smart agriculture and wildlife monitoring are one of the recent trends of Internet of Things (IoT) applications, which are evolving in providing sustainable solutions from producers. This article details the design, development and assessment of a wildlife monitoring application for IoT animal repelling devices that is able to cover large areas, thanks to the low power wide area networks (LPWAN), which bridge the gap between cellular technologies and short range wireless technologies. LoRa, the global de-facto LPWAN, continues to attract attention given its open specification and ready availability of off-the-shelf hardware, with claims of several kilometers of range in harsh challenging environments. At first, this article presents a survey of the LPWAN for smart agriculture applications. We proceed to evaluate the performance of LoRa transmission technology operating in the 433 MHz and 868 MHz bands, aimed at wildlife monitoring in a forest vegetation area. To characterize the communication link, we mainly use the signal-to-noise ratio (SNR), received signal strength indicator (RSSI) and packet delivery ratio (PDR). Findings from this study show that achievable performance can greatly vary between the 433 MHz and 868 MHz bands, and prompt caution is required when taking numbers at face value, as this can have implications for IoT applications. In addition, our results show that the link reaches up to 860 m in the highly dense forest vegetation environment, while in the not so dense forest vegetation environment, it reaches up to 2050 m.

In the last years, Software-Defined Networking (SDN) has emerged as a flexible paradigm driving innovation in future network architectures. Unfortunately, resilience, a key requirement in IP networks, is not an inherent feature of the SDN architecture. Indeed, the automatic reconfigurability of traffic paths in case of links or nodes failures is no more available. This paper deals with the design and validation of an SDN control application for class-based traffic recovery with load balancing. The features of the OpenFlow protocol have been exploited to timely detect link failures as well as to estimate links utilization. The performance of different strategies for class-based traffic recovery has been evaluated in an emulated environment, based on the widely used Mininet tool, highlighting the effectiveness of the proposed solution in enterprise networks.

IEEE 802.15.4-2015 is the third revision of IEEE 802.15.4 Standard for Low-Rate Wireless Networks. The standard presents Time Slotted Channel Hopping (TSCH) Medium Access Control (MAC) protocol, which provides high reliability and low power consumption to various industrial applications. Despite the effectiveness and the importance of the TSCH protocol, the standard leaves out of its scope in defining how the schedule is built and maintained. In this work, we focus on scheduling in IEEE 802.15.4-2015 TSCH networks from the energy efficiency perspective in a centralized manner where the gateway makes frequency allocations and time slot assignments. At first, we derive an energy consumption model of a TSCH node to determine the network lifetime. Afterwards, we formulate the scheduling problem as an energy efficiency maximization problem, which is a nonlinear integer programming. Motivated by the high computational complexity of the problem, we propose a low-complexity Energy Efficient Scheduler (EES) and Vogel's Approximation Method Heuristic Scheduling Algorithm (VAM-HSA). We make a comparison with the Round Robin Scheduler (RRS) and analyse the schedulers in terms of success probability and energy efficiency. Performance evaluation indicates that EES and VAM-HSA perform better in terms of energy efficiency, while at the same time yielding a good throughput.

In response to the challenges posed by climate change, including extreme weather events, such as heavy rainfall and droughts, the agricultural sector is increasingly seeking solutions for the efficient use of resources, particularly water. Pivotal aspects of smart agriculture include the establishment of weather-independent systems and the implementation of precise monitoring and control of plant growth and environmental conditions. Hydroponic cultivation techniques have emerged as transformative solutions with the potential to reduce water consumption for cultivation and offer a sheltered environment for crops, protecting them from the unpredictable impacts of climate change. However, a significant challenge lies in the frequent need for human intervention to ensure the efficiency and effectiveness of these systems. This paper introduces a novel system with a modular architecture, offering the ability to incorporate new functionalities without necessitating a complete system redesign. The autonomous hydroponic greenhouse, designed and implemented in this study, maintains stable environmental parameters to create an ideal environment for cultivating tomato plants. Actuators, receiving commands from a cloud application situated at the network’s edge, automatically regulate environmental conditions. Decision-making within this application is facilitated by a PID control algorithm, ensuring precision in control commands transmitted through the MQTT protocol and the NGSI-LD message format. The system transitioned from a single virtual machine in the public cloud to edge computing, specifically on a Raspberry Pi 3, to address latency concerns. In this study, we analyzed various delay aspects and network latency to better understand their significance in delays. This transition resulted in a significant reduction in communication latency and a reduction in total service delay, enhancing the system’s real-time responsiveness. The utilization of LoRa communication technology connects IoT devices to a gateway, typically located at the main farm building, addressing the challenge of limited Internet connectivity in remote greenhouse locations. Monitoring data are made accessible to end-users through a smartphone app, offering real-time insights into the greenhouse environment. Furthermore, end-users have the capability to modify system parameters manually and remotely when necessary. This approach not only provides a robust solution to climate-induced challenges but also enhances the efficiency and intelligence of agricultural practices. The transition to digitization poses a significant challenge for farmers. Our proposed system not only represents a step forward toward sustainable and precise agriculture but also serves as a practical demonstrator, providing farmers with a key tool during this crucial digital transition. The demonstrator enables farmers to optimize crop growth and resource management, concretely showcasing the benefits of smart and precise agriculture.