The growing use of mobile nodes in manufacturing environments is increasing the Quality of Service (QoS) requirements of the communications infrastructures that support them, as is the case with Industrial Wireless Sensor Networks (IWSN). Managing networks using Software Defined Networks (SDN) addresses the challenge of handling multiple sources in a satisfactory manner. The global vision of the topology that the SDN controller has allows a logical segmentation of the network, through the allocation of dedicated resources for each information flow, thus ensuring independent service levels and complete isolation. Mobile nodes produce constant changes in topology, which lead to instability for routing protocols. Traditional routing solutions with protocols such as Routing Protocol for Low-Power and Lossy Networks (RPL) require additional time to make the parent node change. This paper proposes Mobile Multicast Forwarding with Software Defined Network (MMF-SDN), an approach using Software Defined Networking solution for WIreless SEnsor Network (SDN WISE) protocol that exploits the advantages of SDN and Time Slotted Channel Hopping (TSCH) synchronism. The mobile nodes are managed as multicast sources, through a cumulative allocation of resources from the controller. This allows reception states to be synchronized at the parent nodes to provide network stability, avoiding subsequent recalculations in the routing protocol. Parent node changes are transparent and immediate. This proposal improves on other SDN based solutions, reducing energy consumption in reception by up to 50%, 70% end-to-end delay and improving scalability with a 30% reduction in slotframe occupancy.

IWSNs (Industrial Wireless Sensor Networks) have become the next step in the evolution of WSN (Wireless Sensor Networks) due to the nature and demands of modern industry. With this type of network, flexible and scalable architectures can be created that simultaneously support traffic sources with different characteristics. Due to the great diversity of application scenarios, there is a need to implement additional capabilities that can guarantee an adequate level of reliability and that can adapt to the dynamic behavior of the applications in use. The use of SDNs (Software Defined Networks) extends the possibilities of control over the network and enables its deployment at an industrial level. The signaling traffic exchanged between nodes and controller is heavy and must occupy the same channel as the data traffic. This difficulty can be overcome with the segmentation of the traffic into flows, and correct scheduling at the MAC (Medium Access Control) level, known as slices. This article proposes the integration in the SDN controller of a traffic manager, a routing process in charge of assigning different routes according to the different flows, as well as the introduction of the Time Slotted Channel Hopping (TSCH) Scheduler. In addition, the TSCH (Time Slotted Channel Hopping) is incorporated in the SDN-WISE framework (Software Defined Networking solution for Wireless Sensor Networks), and this protocol has been modified to send the TSCH schedule. These elements are jointly responsible for scheduling and segmenting the traffic that will be sent to the nodes through a single packet from the controller and its performance has been evaluated through simulation and a testbed. The results obtained show how flexibility, adaptability, and determinism increase thanks to the joint use of the routing process and the TSCH Scheduler, which makes it possible to create a slicing by flows, which have different quality of service requirements. This in turn helps guarantee their QoS characteristics, increase the PDR (Packet Delivery Ratio) for the flow with the highest priority, maintain the DMR (Deadline Miss Ratio), and increase the network lifetime.

The advent of Industry 4.0 brought about digitalisation and the integration of advanced technologies into industrial processes, with wireless networks emerging as a key enabler in the interconnection of smart devices, cyber–physical systems, and data analytics platforms. With the development of Industry 5.0 and its emphasis on human–machine collaboration, Wi-Fi has positioned itself as a viable alternative for industrial wireless connectivity, supporting seamless communication between robots, automation systems, and human operators. However, its adoption in critical applications remains limited due to persistent concerns over latency, reliability, and interference in shared-spectrum environments. This study evaluates the practical performance of Wi-Fi standards from 802.11n (Wi-Fi 4) to 802.11be (Wi-Fi 7) across three representative environments: residential, laboratory, and industrial. Six configurations were tested under consistent conditions, covering various frequency bands, channel widths, and traffic types. Results prove that Wi-Fi 6/6E delivers the best overall performance, particularly in low-interference 6 GHz scenarios. Wi-Fi 5 performs well in medium-range settings but is more sensitive to congestion, while Wi-Fi 4 consistently underperforms. Early Wi-Fi 7 hardware does not yet surpass Wi-Fi 6/6E consistently, reflecting its ongoing development. Despite these variations, the progression observed across generations clearly demonstrates incremental gains in throughput stability and latency control. While these improvements already provide tangible benefits for many industrial communication scenarios, the most significant leap in industrial applicability is expected to come from the effective implementation of high-efficiency mechanisms. These include OFDMA, TWT, scheduled uplink access, and enhanced QoS features. These capabilities, already embedded in the Wi-Fi 6 and 7 standards, represent the necessary foundation to move beyond conventional best-effort connectivity and toward supporting critical, latency-sensitive industrial applications.

Industry 4.0 digitization requirements have led to widespread adoption of industrial wireless sensor networks (IWSNs) in manufacturing environments. These require strict control of the traffic flowing over the network to ensure the quality of service. Software-defined networks (SDNs) can address this challenge, as their centralized operation allows routing and media access control (MAC) protocols to be optimized. In addition, in many cases a massive deployment of metering devices is necessary, therefore the network must be scalable, to allow an increase in the number and density of nodes in the network. This implies an increase in the control traffic required by SDNs, generating a significant reduction in the throughput available for data. This is because the length of the timeslot limits the throughput of the network in protocols that uses time division, such as the Time Slotted Channel Hopping (TSCH), conditioning the number of nodes that the network can have and its data sending rate. In this paper, we propose to exploit the integration and reconfiguration capabilities of SDN to extend the number of nodes in the network through the use of multi-radio sinks called virtual sinks, orchestrated from the SDN controller, and extending their use to multiple SD-IWSNs to take full advantage of the radio spectrum. To optimize bandwidth usage, the SDN controller will allocate network slices, allowing nodes to send data with a high frequency using dedicated channels. The results obtained show that the use of multi-radio sinks provides for increasing the maximum number of nodes that can be deployed while preserving the quality of service (QoS) requirements. A linear increase in nodes at least 0.7 times for each radio interface is obtained compared to an SD-IWSN with a traditional sink. In addition, the use of virtual sinks increases the packet frequency of the network by a factor equal to the number of radio interfaces. Moreover, the total number of nodes is improved through the coexistence of multiple SD-IWSNs, where up to 13.7 times more nodes can be scheduled using all the available spectrum orchestrated from the same SDN controller.

Industrial Wireless Sensor Networks (IWSN) are becoming increasingly popular in production environments due to their ease of deployment, low cost and energy efficiency. However, the complexity and accuracy demanded by these environments requires that IWSN implement quality of service mechanisms that allow them to operate with high determinism. For this reason, the IEEE 802.15.4e standard incorporates the Time Slotted Channel Hopping (TSCH) protocol which reduces interference and increases the reliability of transmissions. This standard does not specify how time resources are allocated in TSCH scheduling, leading to multiple scheduling solutions. Schedulers can be classified as autonomous, distributed and centralised. The first two have prevailed over the centralised ones because they do not require high signalling, along with the advantages of ease of deployment and high performance. However, the increased QoS requirements and the diversity of traffic flows that circulate through the network in today’s Industry 4.0 environment require strict, dynamic control to guarantee parameters such as delay, packet loss and deadline, independently for each flow. That cannot always be achieved with distributed or autonomous schedulers. For this reason, it is necessary to use centralised protocols with a disruptive approach, such as Software Defined Networks (SDN). In these, not only is the control of the MAC layer centralised, but all the decisions of the nodes that make up the network are configured by the controller based on a global vision of the topology and resources, which allows optimal decisions to be made. In this work, a comparative analysis is made through simulation and a testbed of the different schedulers to demonstrate the benefits of a fully centralized approach such as SDN. The results obtained show that with SDN it is possible to simplify the management of multiple flows, without the problems of centralised schedulers. SDN maintains the Packet Delivery Ratio (PDR) levels of other distributed solutions, but in addition, it achieves greater determinism with bounded end-to-end delays and Deadline Satisfaction Ratio (DSR) at the cost of increased power consumption.

Wireless networks are increasingly considered for industrial and time-critical applications, where flexible deployment must be reconciled with predictable communication behaviour. IEEE 802.11ax introduces mechanisms such as Orthogonal Frequency Division Multiple Access (OFDMA), Trigger-based Uplink Access (TUA), and Target Wake Time (TWT) as part of ongoing efforts to support bounded latency and deterministic transmissions in Wi-Fi networks. However, the practical behaviour of these mechanisms depends not only on the standard, but also on what commercial devices expose, how access points implement scheduling decisions, and how trigger-based access, RU assignment, and timing control can be configured in real deployments. This paper therefore focuses on the practical implementation and experimental assessment of OFDMA-based deterministic operation using Wi-Fi 6 commercial off-the-shelf (COTS) hardware. The proposed configuration combines driver-level enabling of high-efficiency mechanisms with controlled testbed measurements and complementary simulations, allowing OFDMA operation to be compared against conventional single-user OFDM under realistic traffic and interference conditions. The results show that coordinated OFDMA operation on COTS devices improves temporal stability, reducing jitter by up to 23% and latency by approximately 44% with respect to single-user OFDM operation. The experiments also reveal practical effects that are central to deterministic-oriented Wi-Fi: simultaneous RU-based transmissions reduce contention-driven variability, TWT-based activity windows improve temporal alignment, and RU subdivision introduces a throughput trade-off that must be considered when dimensioning industrial traffic. Overall, the study provides empirical evidence that Wi-Fi 6 can support deterministic-oriented industrial communication when OFDMA, trigger-based access, and timing mechanisms are jointly configured, while also highlighting the implementation constraints that remain when moving from standard capabilities to COTS device behaviour.