This paper provides an overview of the domain challenges, use cases, objectives, high-level concepts, intended innovations, and expected impact of the DistriMuSe project. The project’s main aim is to enhance human health and safety by improved sensing of human presence, behaviour, intentions and vital signs in a collaborative or common environment by means of multi-sensor systems, distributed processing and machine learning. The use cases address challenges in health monitoring of elderly, sleep and exercise, of drivers and vulnerable road users in traffic and of people interacting with robots in a factory environment. Technical development in the project focuses on unobtrusive monitoring sensors, multi-sensor systems, distribution of computation and intelligence, and domain specific needs for the use cases.

Digital Twin Networks have garnered increasing interest in both industry and academia for managing, monitoring, and controlling networks, irrespective of the underlying technology. However, in networks characterized by low frequency and throughput, the monitoring data is often inadequate to provide sufficient insights into network behavior on its own. In essence, establishing bi-directional communication between the Digital Twin Network and the physical network is crucial for gaining insights into the network and enabling informed reconfiguration based on those insights. This is ideally achieved without relying on out-of-band communication. Therefore, alternative paradigms must be considered. This study investigates the impact of monitoring frequency on the reliability and accuracy of a Digital Twin Network within a Bluetooth Mesh environment. Multiple frequency settings were tested across two experiments to evaluate their effect on network performance. The comparison between real network paths and Digital Twin Network simulations provides insights into its behavior. Results indicate that higher update frequencies generally improve Digital Twin Network performance by enhancing path prediction accuracy. However, this improvement is counterbalanced by a reduction in network reliability at higher frequencies. Furthermore, it was noted that while higher frequencies tend to result in more accurate paths predicted by the Digital Twin Network, they also adversely affect the accuracy of end-to-end latency predictions. These findings highlight the need for a strategic balance between requirements in Digital Twin Network deployment.

Time-Sensitive Networking (TSN) ensures reliable traffic delivery in industrial automation, multimedia, and automotive systems. While effective in wired networks, wireless TSN (WTSN) faces challenges like delays and interference, complicating traffic scheduling. This paper presents a data-driven approach to improve WTSN management by addressing the residual service time (RST) problem, which increases link latency. Tested in a Wi-Fi TSN-based environment, the proposed WTSN digital twin framework preserves TSN traffic guarantees while significantly reducing RST and hence link latency.

The densification of Wi-Fi deployments means that fully distributed random channel access is no longer sufficient for high and predictable performance. Therefore, the upcoming IEEE 802.11bn amendment introduces multi-access point coordination (MAPC) methods. This paper addresses a variant of MAPC called coordinated spatial reuse (C-SR), where devices transmit simultaneously on the same channel, with the power adjusted to minimize interference. The C-SR scheduling problem is selecting which devices transmit concurrently and with what settings. We provide a theoretical upper bound model, optimized for either throughput or fairness, which finds the best possible transmission schedule using mixed-integer linear programming. Then, a practical, probing-based approach is proposed which uses multi-armed bandits (MABs), a type of reinforcement learning, to solve the C-SR scheduling problem. We validate both classical (flat) MAB and hierarchical MAB (H-MAB) schemes with simulations and in a testbed. Using H-MABs for C-SR improves aggregate throughput over legacy IEEE 802.11 (on average by 80% in random scenarios), without reducing the number of transmission opportunities per station. Finally, our framework is lightweight and ready for implementation in Wi-Fi devices.

Time-Sensitive Networking (TSN) plays a crucial role in ensuring determinism and low latency, vital for the demands of industrial applications. Integrating the benefits of wire-less networks, including mobility, presents a significant challenge in such environments. In this study, we propose a novel solution to address this challenge by introducing handover capabilities into wireless Time-Sensitive Networking (W-TSN). Through real-world development and testing, we present an optimized approach for minimizing handover delay and leveraging machine learning to select the optimal handover time and space moment in a two-dimensional environment, with low effect on time-sensitive traffic. Our findings demonstrate that our mechanism reduces handover delay below 10 milliseconds and optimizes the handover moment selection, leading to improvements in critical network parameters such as bandwidth and jitter.

Recent technologies of Wi-Fi are being widely in-corporated in smart factories with an expectation of real-time, flexible, reliable, and quality services. The current Wi-Fi offers a range of physical data rates based on channel quality but is limited to certain applications. With the traditional application and transport layer protocols being designed for wired networks, using them in bottleneck situations of industrial wireless networks poses certain drawbacks and one such drawback is the through-put degradation due to airtime unfairness. Using innovations like in-band network telemetry, application-network interaction, and the programmability of the kernel and intermediate devices, a reactive airtime feedback-based congestion control algorithm, RACC, for wireless networks is introduced in this paper. The designed algorithm reactively adapts the application data transfer rate based on the feedback from the access point and was implemented on commercial off-the-shelf devices. Using this algorithm, the throughput was improved 72% and the airtime unfairness was reduced to as low as 15% as compared to the CUBIC. The designed congestion control algorithm addresses the issue of airtime unfairness and throughput degradation in industrial wireless networks based on real-time network state.

We present a wireless multi-hop network management system that can capture the current network context to gain continuous insights into network performance and provide reconfiguration suggestions. Ongoing IETF standardization efforts refer to the creation of this type of virtual representation as a Digital Twin Network. The management system presented in this paper is based on Bluetooth Mesh networks and combines simulation, graph-based algorithms and theoretical models to gain insights into network performance and provide per-flow reconfiguration suggestions. Through an advanced testbed, we showcase the efficiency of Digital Twin Network-based configurations compared against simple configurations. The demonstration highlights the system’s ease of use and swift implementation with a plug-and-play approach. This study paves the way for the advancement of network management in wireless communication systems and more efficient traffic scheduling for constrained Internet of Things devices. It underscores the potential of autonomous Digital Twin Network configurations to improve network resilience and performance.

We introduce a comprehensive testing framework built on top of a Bluetooth Mesh Testbed, showcasing a blend of user-friendly design, swift implementation, and adaptability to diverse testing scenarios and technologies. The framework's modular architecture ensures syntactic validation, precise event scheduling, and efficient execution. Its well-defined syntax facilitates easy updates, catering to evolving requirements and maintaining agility. Operating independently across multiple nodes and accommodating various events, whether repetitive or one-time, the framework proves to be a versatile and robust solution for conducting tests. Tools like shared disks and synchronized clocks, provided by the Testbed, further enhance the framework's capability to schedule network flow behavior and gain insights into network performance. Overall, our testing framework presents a valuable tool for researchers and practitioners seeking a seamless and flexible approach to evaluate Bluetooth Mesh networks in a realistic environment.

The concept of broadcasting audio using Bluetooth has been standardized as Auracast. It enables a variety of use cases, both for personal use as well as in public venues. Due to its novelty, available research work about the technology and its performance, is limited. This paper provides a performance evaluation of the listening experience on Bluetooth-based broadcast audio streams, by performing measurements on a testbed that can set up an audio link between a broadcaster and receiver on Bluetooth-capable hardware. The testbed can introduce variable attenuation on the audio link and inject nearby interference from a Bluetooth Low Energy (BLE) connection. The measurements are compared against simulation results from a model that was designed and implemented as part of previous work. A comparable performance between the testbed and model is shown to be achieved for different attenuation settings. Next to this, the work in this paper presents an extension to the model that enables it to provide accurate simulation results for a broadcast audio stream operating in proximity to multiple BLE connections.

With ever-increasing throughput-hungry applications running over WiFi, such as Virtual and eXtended Reality (VR/XR), on the one hand and the need for deterministic communication on the other, network densification is not an option. With dense network deployment interference between overlapping basic service set (OBSS) become the main source of system throughput drop and packet delays, decreasing the benefits of dense network. With the latest WiFi 7 standard being standardized, access point (AP) coordination is one of the key features foreseen to be added. With increased interactions between APs from different OBSS, spatial reuse feature can benefit in determining accurately the levels of interference and modulation and coding scheme (MCS) index to be used for concurrent transmissions. In this paper we show a centralized Coordinated Spatial Reuse (C-SR) algorithm implemented in the network controller that determines the transmit powers of the concurrent AP transmitters based on calculated interference levels in the main receiver. In addition, the algorithm determines the MCS index for each concurrent transmission. In a test-bed measurement setup, we show that the overall system goodput is increased by 20% and 33%, respectively, for the network topology where receivers are positioned in the inner zone between APs. In addition, the communication latency is maintained below certain threshold, compared to cases where C-SR is not activated.

As network management operations increasingly rely on automation and finer control actions, there is a need for precise telemetry systems. In-band Network Telemetry (INT) methods use data packets to carry telemetry and give real-time insights about network performance. Existing solutions often require specialized hardware or offer limited runtime configuration options. This work presents an INT Framework for heterogeneous private networks, targeting industrial and multimedia applications. The framework is designed to be flexible and runtime-reconfigurable, addressing challenges in real-world applications. We provide implementation details of our elements supporting the configurability and the consolidation of raw telemetry into high-level Quality of Service (QoS) metrics. We evaluated the framework in a testbed with wired and wireless devices. The results show the accuracy in monitoring QoS, as well as an analysis of synchronization requirements, showcasing the feasibility of our framework for solutions requiring precise and flexible QoS monitoring.

As industries increasingly rely on advanced networking solutions, Time-Sensitive Networking (TSN) has emerged as an essential tool, ensuring smooth and reliable communication in mission-critical applications. However, while TSN does a lot for industrial systems, there is still a whole world of not-utilized potential in wireless communication. To extend wired TSN with wireless capabilities, imec’s openwifi platform has been extended with TSN features. To speed up the implementation of new Wi-Fi features in the openwifi platform, as well as to test their feasibility in larger-scale network scenarios we implemented the key TSN features of openwifi in the ns-3 simulator. In this paper, we evaluate how the selection of transmission opportunity (TXOP) duration affects network performance in shared time slots, as well as the impact of different shifts between shared time slots. The ns-3 implementation is validated against openwifi as well.

Time-sensitive networking (TSN) is proposed to support deterministic communication for industrial automation use cases. To harvest the wireless communication flexibility, TSN features have been extended to the wireless domain as well. One of the key TSN features is the ability to assign transmission schedules to different traffic flows in the network with the aim of reducing time slot access delay on each network node. In the wireless domain, this becomes even more challenging due to the shared medium, lower reliability, and slower transmission rates compared to wired systems, reducing the available time resources. In this paper we look at utilizing genetic algorithms to support scheduling of traffic flows from different wireless end devices in a shared schedule. Two optimization functions are defined. The first optimization is based on minimizing the overall shared air time between different end nodes, while the second optimization is based on maximizing time slots that can be used without any interference. Both optimizations aim to reduce the collision probability. With these initial results, we identify the best parameters for genetic algorithms and examine the initial population's impact on overall performance. We show that a fully randomized initial population does not achieve the highest fitness value, even after several generations.

Real-time applications are employed in today's pri-vate professional networks to support process handling and improve the efficiency of production. For supporting such applications, communication networks need to support deterministic communication with bounded low latency and high reliability. Time-sensitive networking (TSN) is used for such purposes, recently extended to wireless networks as well. To further improve the network catering to such real-time applications, it is crucial for end devices to expose their requirements to the network. On top of that, new wireless features like OFDMA, implemented in IEEE 802.11ax (Wi-Fi 6), can improve wireless time-sensitive networks (W-TSNs) by improving communication efficiency. This paper looks at reducing the overhead of OFDMA and integrating UL-OFDMA with wireless TSN to support time-sensitive flows. We show that when both features are integrated, it reduces the latency by ~ 16 times compared to Wi-Fi with UL-OFDMA scenario while giving 50 % better air time utilization compared to the wireless TSN scenario.

Industrial wireless sensor networks offer a viable alternative to wired solutions where there is a lack of suitable communication infrastructure. Among these networks, time slotted channel hopping (TSCH) emerges as a noteworthy choice due to its capacity for deterministic latency, heightened reliability, and low power consumption. Nonetheless, challenges arise from the energy-intensive joining procedure and inherent idle listening associated with TSCH, impeding the integration of battery-powered end devices. Therefore, this article introduces a novel 6TiSCH low-power node (6LPN) that supports ultralow-power operations. The proposed solution optimizes the energy-intensive joining procedure through reduced advertisement channels, optimal scanning time, and a delayed join, achieving a 90% reduction in energy consumption. Furthermore, idle listening is eliminated by queueing downlink traffic in a 6TiSCH friend node (6FN), ensuring an 87%–94% reduction in power consumption during operational mode while maintaining an average latency of queued frames of 7.62 s. By comparing the impact of the optimizations on three Internet of Things (IoT) hardware platforms, we demonstrate that optimal results are obtained for devices with low RX and idle transceiver current. Finally, our solution maintains full backward compatibility with 6TiSCH and does not introduce additional control traffic.

End-to-end low-latency deterministic communication, next to high-reliability communication, is one of the key features that communication systems are expected to provide for industrial systems. To achieve time-sensitive networking (TSN), a set of standards have already been designed and deployed for wired industrial communication systems, coexisting or replacing other long-living technologies such as Fieldbus, Profibus, or Modbus. Wireless time-sensitive networking (W-TSN) is getting traction with the development of the newest WiFi generation (IEEE 802.11be) as well as advances in cellular networking. One of the challenges in W-TSN is scheduling and isolation of time-critical traffic in the shared wireless medium. In this paper we present a solution, called dynamic traffic classification, to give faster dedicated access to the wireless medium for packets of highly-time-sensitive flows, that can be generated randomly. Dynamic traffic classification utilizes so-called shadow queues implemented in FPGA-based WiFi baseband SDR platform, openwifi, to prioritize channel access of certain packets over others. We show that the channel access latency in the case of dynamic traffic classification does not depend on the scheduling cycle, but on the distribution of dedicated time slots inside the schedule cycle. As such we achieve to decrease the end-to-end latency by 75% in case of longer communication cycles with wider space between communication time slots.

The emergence of Time-Sensitive Networking (TSN) has enabled network determinism to a new level, offering high reliability and bounded latency for critical communications. However, the unpredictable nature of traffic generation also poses new challenges to TSN. While TSN is designed to maintain backward compatibility with the 802.1 standards, many end nodes may not be equipped to understand TSN. This can result in a less deterministic TSN, and suboptimal resource utilization, mainly driven by Residual Service Time (RST). To address these challenges, this study proposes three scheduling mechanisms to reduce RST: q-learning, active time slot update, and polynomial forecasting. Real-world data captured from our wireless-TSN (W-TSN) evaluation kit is used to compare the proposed approaches in terms of one-way latency. The results show that the machine learning approach outperforms the other methods in terms of overall latency. However, it is less effective in identifying the optimal time slot position compared to the other methods.

Deterministic performance and reliable operation are vital for many applications with industrial-grade requirements. Such applications rely on Time-Sensitive Networking (TSN) to enable time-critical deterministic communication. While standardization efforts were focused mainly on TSN features for wired domains, recent advances in wireless technologies (e.g., Wi-Fi 6/7) are extending time-sensitive communication towards wireless networks as well. However, achieving multi-domain LAN/ Wireless LAN (WLAN) end-to-end TSN communication requires addressing challenges on end-to-end time synchronization, multi-domain control plane interoperability, run-time end-to-end scheduling, and fine-grained monitoring. Because state-of-the-art TSN controllers’ scope lays far below these new required capabilities, in this work we present a novel, fully-programmable controller for end-to-end TSN-enabled networks. Our controller is based on a modular architecture to be adaptable to challenges arising when shifting the standard TSN scope towards WLAN domain. We deploy a proof-of-concept in a cloud-wired environment to evaluate its key performance indicators when handling increasing numbers of nodes and simultaneous requests. Further, we run experiments on real TSN-enabled networks comprising Ethernet and Wi-Fi technologies, demonstrating the effectiveness of the controller in performing seamless fine-grained traffic control in both domains.

Industrial communication systems provide deterministic and reliable communication between various industrial components. In the past several decades, different communication technologies (Fieldbus, Real-Time Ethernet (RTE)) were used to achieve such determinism. Recently, Time-Sensitive Networking (TSN) is being utilized in industrial environments to support end-to-end low latency deterministic communication by providing mechanisms for accurate time synchronization, traffic scheduling/shaping, and reliability. With many use cases requiring portability and seamless mobility, such features are being developed for wireless networks as well, expanding the time-sensitive communication to the wireless domain. Wireless TSN’s aim is to provide wired TSN-like features, achieving wired-wireless interoperability and flattening the automation system pyramid. In this paper, we present an integration between the wireless TSN and PROFINET. We show that the safety-related applications can be supported seamlessly, providing deterministic communication and reliability under best-effort traffic load in the wireless network. The solution is evaluated in terms of the achieved end-to-end latency and the probability of failure per hour of the fail-safe communication. It is shown that by using wireless time-sensitive networking with dedicated time slots per traffic flow a safety integrity level up to grade 4 can be achieved.

Time-sensitive networking (TSN) is widely used in industrial environments to support low-latency deterministic communications. Innovation to bring time-sensitive networking to wireless networks is getting traction. Besides enabling real-time and deterministic communications, Wireless Time-Sensitive Networks (W- TSN) should provide flexibility and easy deploy-ment, key characteristic requirements for industrial networks. Nevertheless, current research in this field focuses on adapting wired TSN features to the wireless world, namely accurate time synchronization and traffic scheduling, essential processes for wireless end devices such as automated and impact-less association procedure are not considered until now. This work proposes a W - TSN impactless association procedure that provides time synchronization and traffic scheduling for prospect W - TSN clients during the association phase by utilization of beacons. As such, prospect clients can perform association procedure in a controlled fashion avoiding collisions with other, already-associated, W - TSN clients. The presented procedure is designed, implemented, and tested in a real-world scenario on top of a wireless Software Defined Radio (SDR) platform with the IEEE802.11 standard. The results show high accuracy synchro-nization on client frame transmissions even with challenging scheduling timeslots of 128 μs.

Bluetooth Mesh (BM) technology is a suitable candidate to realize mesh networks leveraging on a mains-powered backbone. However, the flooding-based technology requires additional management in order to operate efficiently. Consequently, it offers a diverse set of configuration options to control network behavior, including the selection of relays in the backbone that rebroadcast packets further into the network. In the past, Digital Twin technology has been applied to design a Digital Communication Twin (DCT) of a BM network. The DCT (or Digital Twin Network, DTN) can be used to find an optimal network configuration for given application requirements. This includes a relay selection approach that finds a set of relays to assure sufficient path redundancy in the network. However, existing results prove that this approach can be improved in terms of computation time, flexibility and validity of the proposed set of relays. In this paper, we present a reinterpreted version of a genetic algorithm to tackle this issue. The results show it achieves better results on all three improvement targets, compared to the original approach. Furthermore, it showcases the flexibility and adaptability of the DCT whilst adequately improving the relay selection approach.

Precision time protocol (PTP), a state-of-the-art clock synchronization protocol primarily designed for wired networks, has recently gained attention in the wireless community, due to the increased use of the IEEE 802.11 wireless local area networks (WLAN) in real-time distributed systems. However, all the existing WLAN-based PTP designs either incorporate software timestamping (TS) delivering poor clock synchronization accuracy, or hardware (HW) TS providing better synchronization accuracy at the cost of a significant amount of HW overhead. Moreover, the performance of the existing PTP solutions is mostly evaluated in single-hop wireless networks, while the performance across wired and wireless networks is taken for granted. In this article, a new software-defined-radio-based approach to implement PTP is introduced and validated for the IEEE 802.11 WLAN. Instead of using a dedicated HW clock, the solution utilizes the timing synchronization function clock, an existing clock in the IEEE802.11 standard for synchronization between access point and WLAN stations. The performance of the proposed solution is first investigated within a single-hop WLAN and then across wired–wireless networks. Experimental results unveil that 90% of the absolute clock synchronization error falls within 1.4$\mu \mathrm{s}$.

With the ongoing push towards an automated Industry 4.0, data-driven intelligent algorithms are getting more attention. Warehouse operators have traditionally required human labor to identify and register their assets. Autonomous flying drones will help alleviate this task by flying through the warehouse and detecting assets. This can be done based on vision, requiring expensive and energy consuming hardware, limiting drone flight time. In contrast, we propose a solution using radio-frequency identification (RFID) tags and machine learned algorithms to localize assets, which does not require a well-lit environment and can be processed in an energy efficient way. Our machine learning model achieves a 92–93 % accuracy, even when the drone is flying at different heights than the assets. Additionally, the model is easily implementable on off-the-shelf and low-energy consuming embedded hardware. This data-driven solution can easily be retrained for different environments and allows cheap RFID-based horizontal localization of assets in warehouses of the future.

Wireless Sensor Networks (WSNs) operating in unlicensed frequency bands or employing battery-less devices, require a Duty Cycle (DC) limit to ensure fair spectrum access or limit energy consumption. However, in multi-hop networks, it is up to the network protocol to ensure that all devices comply with such DC restrictions. We therefore developed a distributed DC adherence algorithm that limits the DC of all devices without introducing any additional packet overhead. This paper presents a brief description of the algorithm and evaluates its performance through simulation. Our results show that the algorithm can limit the DC of all devices to ensure no devices must switch off. Our algorithm therefore provides a solution for WSNs where nodes must operate below a DC limit.

Many applications use Transmission Control Protocol (TCP) to achieve end-to-end reliable, ordered, and error-free data transfer in the network. The decisions are entirely based on the partial end-to-end information obtained from the acknowledgment packets. With several applications moving towards the wireless domain or wired-wireless domain, there has been advancements in the field of application-network interaction and innovations to obtain real-time network monitoring information on a per-hop basis. This paves a way for extensibility and customization of transport protocols. In this paper, we use detailed real-time in-band network telemetry information to adjust the data transfer at the sender side by modifying the congestion control algorithms in real time. This new technique is tested for different network scenarios and the obtained results indicate that a more network-aware TCP design can greatly increase performance under lossy conditions. The implemented technique illustrates how tighter interactions between higherlayer protocols and the network, in combination with real-time telemetry, can facilitate the way for novel, more adaptive protocol designs.

In-band network telemetry (INT) monitoring is getting traction in the recent years for its ability to offer high-granularity network information on per-hop, per-flow and end-to-end basis. Such detailed network monitoring helps in better network management and accurate network (re)configuration, supporting automated network management and control. However, until now the collected INT information is used as is, without any classification based on its provided information value. In this paper we derive the Age of Information (AoI) mathematical model to calculate the INT hop-time average AoI and the impact of reporting on the INT AoI. Such metric can be used to reduce the network overhead in term of INT reporting by not sending old AoI INT and determining the information accuracy. We also show that the INT hop-time average AoI for a layer three INT implementation for a wireless network depends heavily on the communication latency between each hop and end hop, and that it is bounded by the end-to-end communication latency averaged over the number of hops.

While the Internet of Things continues to grow, the LoRaWAN standard is generating special interest due to its open-source nature, ultralow-power consumption and long-range connectivity. Recent works have explored the challenges of implementing LoRaWAN, with scalability being considered one of the major bottlenecks imposed by its Aloha-based medium access control (MAC) layer. Despite much on-going research on LoRaWAN scheduling aimed at alleviating this concern, experimental approaches are rarely found in the literature. In this work, we describe the steps taken and the technical issues overcome to move from a low-overhead synchronization and scheduling concept to its real-world implementation on top of LoRaWAN Class A. Accordingly, an end-to-end architecture was designed and deployed on top of STM32L0 MCUs, which communicate with a central entity responsible for providing synchronization metrics and allocating transmission slots on demand. The clock drift of devices was measured in a temperature-controlled chamber, which served as a basis to define slot lengths in the network. As a result, an operational end-to-end system was implemented and evaluated for different setup scenarios, with 10-ms accuracy being achieved. Our experimental results show significant improvements in packet delivery ratios with respect to Aloha-based setups, especially under high network loads (up to 29% for SF12), thereby demonstrating the feasibility of the presented approach.

Abstract Internet of Things (IoT) technologies, when adequately integrated, cater for logistics optimisation and operations' environmental impact monitoring, both key aspects for today's EU ports management. This article presents Obelisk, a scalable and multi‐tenant cloud‐based IoT integration platform used in the EU H2020 PortForward project. The landscape of IoT protocols being particularly fragmented, the first role of Obelisk is to provide uniform access to data originating from a myriad of devices and protocols. Interoperability is achieved through adapters that provide flexibility and evolvability in protocol and format mapping. Additionally, due to ports operating in a hub model with various interacting actors, a second role of Obelisk is to secure access to data. This is achieved through encryption and isolation for data transport and processing, respectively, while user access control is ensured through authentication and authorisation standards. Finally, as ports IoTisation will further evolve, a third need for Obelisk is to scale with the data volumes it must ingest and process. Platform scalability is achieved by means of a reactive micro‐services based design. Those three essential characteristics are detailed in this article with a specific focus on how to achieve IoT data platform scalability. By means of an air quality monitoring use‐case deployed in the city of Antwerp, the scalability of the platform is evaluated. The evaluation shows that the proposed reactive micro‐service based design allows for horizontal scaling of the platform as well as for logarithmic time complexity of its service time.

Most industrial applications demand determinism in terms of latency, reliability, and throughput. This goes hand in hand with the increased complexity of real-time network programability possibilities. To ensure network performance low-overhead, high-granularity, and timely network verification techniques need to be deployed. The first cornerstone of network verification ability is to enable end-to-end network monitoring, including end devices too. To achieve this, this article shows a novel and low overhead in-band network telemetry and monitoring technique for wireless networks focusing on IEEE 802.11 networks. A design of in-band network telemetry enabled node architecture is proposed and its proof of concept implementation is realized. The PoC realization is used to monitor a real-life SDN-based wireless network, enabling on-the-fly (re)configuration capabilities based on monitoring data. In addition, the proposed monitoring technique is validated in terms of monitoring accuracy, monitoring overhead, and network (re)configuration accuracy. It is shown that the proposed in-band monitoring technique has 6 times lower overhead than other active monitoring techniques on a single-hop link. Besides this, it is demonstrated that (re)configuration decisions taken based on monitored data fulfill targeted application requirements, validating the suitability of the proposed monitoring technique.

Sensors of governments, companies and citizens have been adding a lot of data in recent years to the global datasphere. Yet the vast majority of this data does not belong to its rightful owner causing privacy issues and keeping potential of the data untapped. Local authorities mainly use this data to improve monitoring of the city and to perform their daily tasks more efficiently and - often due to a lack of resources - not to develop new, innovative applications. In addition, sensor data from consumer products often does not belong to the users and remains trapped within walls of platforms. These factors cause an imbalance in online data possession and generated data remaining largely unused. However, by connecting technologies that are available today, sensor data can end up with the rightful owner. Additionally, the data can be linked and shared, which might distribute the opportunities better, so anyone can build novel applications or gain insight. If local authorities adopt the same approach, they can become more transparent and create more awareness into what is happening in their citizens' living environment. Also, innovative solutions, build on the basis of this data, can respond to the (local) needs of people. This opinion article tries to shed light on the possibilities and challenges of an open Web of Things.

The fifth generation of mobile networks (5G) and the Software- Defined Radio Access Networks (SD- RAN) architecture envision to support lower latency, enhanced reliability, massive connectivity, and improved energy efficiency. In this context, low latency is considered crucial and Ultra-Reliable Low Latency Communication (URLLC) as one of the key enablers. Currently, IEEE 802.11 networks cannot be programmed fine-grained enough nor manage multiple networks at runtime. Besides, in such scenarios, the coarse-grained level of monitoring information has been hindering troubleshooting and management. In this paper, we present an SDN-based framework where fine-grained End-to-End (E2E) network statistics can be gathered using Inband Network Telemetry (INT) and used for network control and management. With such fine-grained network information, we show how our system can enhance the Quality of Service (QoS) delivery through slice orchestration in IEEE 802.11 Radio Access Networks (RANs).

For continuous, persistent and problem-free operation of Industrial Wireless Sensor Networks (IWSN), it is critical to have visibility and awareness into what is happening on the network at any one time. Especially, for the use cases with strong needs for deterministic and real-time network services with latency and reliability guarantees, it is vital to monitor network devices continuously to guarantee their functioning, detect and isolate relevant problems and verify if all system requirements are being met simultaneously. In this context, this article investigates a light-weight telemetry solution for IWSNs, which enables the collection of accurate and continuous flowbased telemetry information, while adding no overhead on the monitored packets. The proposed monitoring solution adopts the recent Alternate Marking Performance Monitoring (AMPM) concept and mainly targets measuring end-to-end and hopby-hop reliability and delay performance in critical application flows. Besides, the technical capabilities and characteristics of the proposed solution are evaluated via a real-life implementation and practical experiments, validating its suitability for IWSNs.

As the Internet of Things (IoT) continues to expand, the need to combine communication technologies to cope with the limitations of one another and to support more diverse requirements will proceed to increase. Consequently, we started to see IoT devices being equipped with multiple radio technologies to connect to different networks over time. However, the detection of the available radio technologies in an energy-efficient way for devices with limited battery capacity and processing power has not yet been investigated. As this is not a straightforward task, a novel approach in such heterogeneous networks is required. This article analyzes different low-power wide-area network technologies and how they can be integrated in such a heterogeneous system. Our contributions are threefold. First, an optimal protocol stack for a constrained device with access to multiple communication technologies is put forward to hide the underlying complexity for the application layer. Next, the architecture to hide the complexity of a heterogeneous network is presented. Finally, it is demonstrated how devices with limited processing power and battery capacity can have access to higher bandwidth networks combined with longer range networks and on top are able to save energy compared to their homogeneous counterparts, by measuring the impact of the novel vertical handover algorithm.

With the emergence of the Internet of Things (IoT) and Industry 4.0 concepts, industrial applications are going through a tremendous change that is imposing increasingly diverse and demanding network dynamics and requirements with a wider and more fine-grained scale. Therefore, there is a growing need for more flexible and reconfigurable industrial networking solutions complemented with powerful monitoring and management functionalities. In this sense, this paper presents a novel efficient network monitoring and telemetry solution for Industrial Wireless Sensor Networks mainly focusing on the 6TiSCH Network stack, a complete protocol stack for ultra-reliable ultra-low-power wireless mesh networks. The proposed monitoring solution creates a flexible and powerful in-band network telemetry design with minimized resource consumption and communication overhead while supporting a wide range of monitoring operations and strategies for dealing with various network scenarios and use cases. Besides, the technical capabilities and characteristics of the proposed solution are evaluated via a real-life implementation, practical and theoretical analysis. These experiments demonstrate that in-band telemetry can provide ultra-efficient network monitoring operations without any effect on the network behavior and performance, validating its suitability for Industrial Wireless Sensor Networks.

Wireless netWorks are becoming more complex while applications on top are becoming more demanding. To maintain network performance in terms of latency, throughput and reliability, continuous verification of the performance, possibly followed by on-the-fly network (re)configuration is needed. To achieve this, the way wireless network monitoring is being done needs to be reconsidered and should evolve towards more timely, low overhead and fine-grained monitoring. This paper shows hoiv in-band network telemetry (INT) monitoring can achieve these objectives. An INT-enabled node architecture is designed as well as novel INT options. By means of an implementation on WiFi Linux devices, the concept is validated by tracking the behavior of a real network.

Fingerprinting indoor localization provides high positioning accuracy with low cost and easy deployment. Considering the unsatisfying precision of received signal strength (RSS)-based fingerprinting, hybrid metrics including angle-of-arrival (AoA) and time-of-flight (ToF), are incorporated to the RSS fingerprinting system. To evaluate the positioning performance of hybrid metrics, the closed-form Cramér-Rao lower bound (CRLB) is derived in this paper. The existence conditions of CRLBs, as well as the relationship of the CRLBs between single and hybrid metrics is revealed. Numerical results based on an office building scenario show that hybrid metrics greatly improve the positioning performance and the robustness to measured standard deviations compared to the single metric's case. Furthermore, hybrid schemes of the AoA/RSS/ToF metrics are also investigated, and simulations reveal that the scheme of AoA/ToF-supporting access points (AP) enhanced with single RSS-supporting APs achieves the best positioning accuracy among all hybrid schemes.

Indoor Positioning Systems (IPS) using ultra-wideband (UWB) are used in several application domains to optimize production processes and save expensive man hour costs. To deploy such a system, most solutions rely on an existing backbone network that is used for communication between the anchors and the Real Time Localization System (RTLS), which calculates the location. Our solution aims to be easy to install by using an IoT-standardized and low-power sub-GHz radio as backbone communication medium. Furthermore, using this low-power radio allows us to decrease the overall energy consumption of the anchors. In the demo we showcase that our solution does not require any wired connections and is a factor five more energy efficient than existing implementations.

Bluetooth Low Energy (BLE) is a popular technology within the Internet of Things. It allows low-power, star networks to be set up between a BLE gateway and multiple, power-constrained BLE devices. However, these networks tend to be static, not supporting BLE devices that can freely move around in an environment of multiple interconnected BLE gateways and perform handovers whenever necessary. This work proposes two alternative network architectures for mobile BLE peripherals. One leverages on IPv6 over BLE, whereas the other combines default BLE mechanisms with an additional custom controller. On top, we study in detail the handover mechanism that must be present in both architectures and compare the performance of both a passive and active handover approach. The passive handover approach can be set up without any extra implementation, but an active handover approach offers more proactive handover decisions and can provide a much lower handover latency. All proposed solutions have been implemented and validated on real hardware, showing the feasibility of having future infrastructures with support for mobile BLE devices.

Narrowband Internet of Things (NB-IoT) is gaining prominence as a key Low Power Wide Area Network (LPWAN) technology for IoT applications. Since it operates on licensed frequency spectrum it can provide guarantees to applications demanding Quality of Service (QoS). NB-IoT has emerged as a competitive rival for other LPWAN technologies such as LoRa and Sigfox, which work in the unlicensed frequency spectrum and are vulnerable to interference. Therefore, NB-IoT is the trivial fit for industries and other business companies that demand guaranteed services. In this paper the different features of the NB-IoT technology have been studied on the commercial Orange network in Belgium using the ublox SARA-N210 module [1] as the user equipment (UE). We focused on the device and network performance in terms of setup times, signal quality, throughput, latency, and reliability and studied the network dynamicity on signal strength. These observations are then compared with the theoretical defined limits of NB-IoT.

Recently, LoRaWAN has attracted much attention for the realization of many Internet of Things applications because it offers low-power, long-distance, and low-cost wireless communication. Recent works have shown that the LoRaWAN specification for class A devices comes with scalability limitations due to the ALOHA-like nature of the MAC layer. In this paper, we propose a synchronization and scheduling mechanism for LoRaWAN networks consisting of class A devices. The mechanism runs on top of the LoRaWAN MAC layer. A central network synchronization and scheduling entity will schedule uplink and downlink transmissions. In order to reduce the synchronization packet length, all time slots that are being assigned to an end node are encoded in a probabilistic space-efficient data structure. An end node will check if a time slot is part of the received data structure in order to determine when to transmit. Time slots are assigned based on the traffic needs of the end nodes. We show that in case of a nonsaturated multichannel LoRaWAN network with synchronization being done in a separate channel, the packet delivery ratio (PDR) is easily 7% (for SF7) to 30% (for SF12) higher than in an unsynchronized LoRaWAN network. For saturated networks, the differences in PDR become more profound as nodes are only scheduled as long as they can be accommodated given the remaining capacity of the network. The synchronization process will use less than 3-mAh extra battery capacity per end node during a one year period, for synchronization periods longer than three days. This is less than the battery capacity used to transmit packets that are going to be lost in an unsynchronized network due to collisions.

A number of industrial wireless technologies have emerged over the last decade, promising to replace the need for wires in a variety of use cases. Except for customized time division multiple access (TDMA)-based wireless technologies that can achieve ultralow latency over a very limited area, wireless communication generally has reliability and latency issues when it comes to industrial applications. Closed loop communication requires high reliability (over 99%), limited jitter and latency, which poses a challenge especially over a wide area measuring in hundreds of meters. Extended coverage is promised with the advent of sub-GHz technologies, one of them being IEEE 802.11ah which is the only one that offers sufficient data rate for frequent bidirectional communication. Thus, we evaluated IEEE 802.11ah for low-latency time-critical control loops. We propose the network setup for adjusting the network dynamics to that of control loops, enabling limited jitter and high reliability. We explore the scalability of IEEE 802.11ah network hosting both control loops and monitoring sensors that periodically transmit measurements. Assigning the control loop end-nodes to dedicated restricted access window (RAW) slot results in over 99.99% successful deliveries. Furthermore, interpacket delay is concentrated around the cycle-time in the following or preceding beacon interval in case the beacon interval is at least half the value of the shortest cycle-time. Adjusting the beacon interval to the fastest control loop in the network ensures latency requirements at the cost of maximum achievable throughput and energy consumption.

We develop and benchmark four RSS localisation algorithms where different a priori knowledge is required. The selection of the best algorithm depends on the availability of additional information on path loss exponent and/or transmit power. We compare our algorithms with centroid localization and show that the algorithms provide better results for shadowing on the values not exceeding 6dB. We perform experiments and simulations with Bluetooth Low Energy and LoRaWAN technologies and select the best technology and algorithm for localisation in large open industrial environments.

Modern connected devices are equipped with the ability to connect to the Internet using a variety of different wireless network technologies. Current network management solutions fail to provide a fine-grained, coordinated, and transparent answer to this heterogeneity, while the lower layers of the OSI stack simply ignore it by providing full separation of layers. To address this, we propose the ORCHESTRA framework to manage the different devices in heterogeneous wireless networks and introduce capabilities such as packet-level dynamic and intelligent handovers (both interand intra-technology), load balancing, replication, and scheduling. The framework is the first of its kind in providing a fine-grained packet-level control across different technologies by introducing a fully transparent virtual medium access control layer and an software-defined networking-like controller with global intelligence. Furthermore, we present a novel optimization problem formulation that can be solved to optimally configure the network. We provide a thorough evaluation through simulations and a prototype implementation. We show that our framework enables, in a real-life setting, transparent and realtime inter-technology handovers and that coordinated load balancing can double the network-wide throughput across different scenarios.

Local area networks (LANs) are employed by a plethora of heterogeneous consumer devices, equipped with the ability to connect to the Internet using a variety of different wireless network technologies. Existing solutions and the lower layers of the OSI stack are unfit to cope with this heterogeneity. For instance, dynamical inter-technology switching is user-of application-based. We propose the ORCHESTRA framework to manage the different devices in heterogeneous wireless local area networks (WLANs) and introduce capabilities such as packet-level dynamic and intelligent handovers (both inter- and intratechnology), load balancing, replication, and scheduling. The framework consists of a controller that is capable of communicating with both existing Software-Defined Networking (SDN) and Network Function Virtualization (NFV) controllers and with devices containing a newly introduced virtual Medium Access Control (MAC) layer. We show that the virtual MAC enables transparent and real-time inter-technology handovers and that our solution scales up to two thousands of clients.

LoRa is a long range, low power, low bit rate, single hop wireless communication technology. It is intended to be used for Internet of Things (IoT) networks, where devices are battery powered and limited bandwidth is needed. In combination with its scalability and the low end device price, LoRa is a candidate technology for low bandwidth industrial applications with a high number of communication devices spread across large areas. The use case for this paper is taken from the flower industry, where a large number of trolleys need to communicate with a server during their movement across the auction floor area. Once trolleys are outside of the auction floor they can use the public LoRaWAN network to communicate with the server, without switching communication technology. The LoRaWAN network consists of multiple end nodes and a single gateway per cell, acting as a transparent bridge between the end nodes and the network server. The measurements show that with a single LoRa gateway we can cover an indoor area of around 34000m2 only with spreading factor 7, while for spreading factor 12 the total covered area will be even higher. Also, the area outside the factory is covered when switching to spreading factor 12. We also show that the number of nodes (trolleys) that can be served by a gateway in such a case can be as high as 6000.

Due to the fast emergence of location-based services and the absence of a widely adopted localization technology for indoor environments, Indoor Localization Systems have become a central topic of research in the last decade. Although there is a significant amount of research targeting indoor localization technologies and their performance, most of these efforts only focus on theory, system design or evaluation in non-industrial environments, usually offices or healthcare spaces. In this work, a detailed performance evaluation of two commercially available accurate localization technologies, based on Bluetooth Low Energy (LE) and Ultra-wideband (UWB), in an industrial environment is presented to create an experimental understanding of their behaviour in similar conditions and to investigate their potential to be used in industrial applications with concrete localization requirements. For this purpose, these localization technologies are examined with respect to various performance criteria in several scenarios in a real industrial site.

IEEE 802.11ah is a new Wi-Fi standard operating on unlicensed sub-GHz frequencies. It aims to provide long-range connectivity to Internet of Things (IoT) devices. The IEEE 802.11ah restricted access window (RAW) mechanism promises to increase throughput and energy efficiency in dense deployments by dividing stations into different RAW groups and allowing only one group to access the channel at a time. In this demo, we demonstrate the ability of the RAW mechanism to support a large number of densely deployed IoT stations with heterogeneous traffic requirements. Differentiated Quality of Service (QoS) is offered to a small set of high-throughput wireless cameras that coexist with thousands of best-effort sensor monitoring stations. The results are visualized in near real-time using our own developed IEEE 802.11ah visualizer running on top of the ns-3 event-based network simulator.

As LoRaWAN networks are actively being deployed in the field, it is important to comprehend the limitations of this low power wide area network technology. Previous work has raised questions in terms of the scalability and capacity of LoRaWAN networks as the number of end devices grows to hundreds or thousands per gateway. Some works have modeled LoRaWAN networks as pure ALOHA networks, which fails to capture important characteristics such as the capture effect and the effects of interference. Other works provide a more comprehensive model by relying on empirical and stochastic techniques. This paper uses a different approach where a LoRa error model is constructed from extensive complex baseband bit error rate simulations and used as an interference model. The error model is combined with the LoRaWAN MAC protocol in an ns-3 module that enables to study multichannel, multispreading factor, multi-gateway, bi-directional LoRaWAN networks with thousands of end devices. Using the LoRaWAN ns-3 module, a scalability analysis of LoRaWAN shows the detrimental impact downstream traffic has on the delivery ratio of confirmed upstream traffic. The analysis shows that increasing gateway density can ameliorate but not eliminate this effect, as stringent duty cycle requirements for gateways continue to limit downstream opportunities.

Wireless network deployments in industry often grow organically with new technologies added over time, among which many use the non-licensed spectrum to avoid licensing costs. As a result, technologies competing for the same spectrum end up deployed in the same area, causing coexistence problems to manifest themselves at a later stage. To avoid unexpected performance degradation, there is a need to evaluate the impact of additional wireless technologies on an existing network before the actual deployment. This paper proposes to simplify the impact assessment by emulating the signals of the potential wireless network with a single software-defined radio. To evaluate the emulator's performance, the impact of Bluetooth on Wi-Fi technology is considered as the reference scenario. A series of real-life experiments with configurable traffic load and network scale are conducted to estimate the impact of Bluetooth network on a Wi-Fi link, and the corresponding measurements are repeated with the emulated Bluetooth signals. To the best of the authors' knowledge, we are the first to propose such a solution, and it is shown that the use of our emulator gives a reliable indication of the expected impact at the location of the Wi-Fi link. As such, this paper provides an important step toward a simple, cost efficient, and reliable solution, to assess the impact of a wireless network prior to its deployment.

Wireless communication is an enabling technology for industrial automation. For mobile industrial devices operating in large areas, the performance of the wireless handover process is crucial. For the welfare of industrial processes short time communication outage must be ensured, especially for time-critical traffic. This paper assesses the handover performance for three industrial real-life use cases with different requirements. It covers handover performance under heavy interference, its impact on time-critical traffic and on broadcast traffic latency, followed by lessons learned and opportunities for further research.

As open standards for the Internet of Things gain traction, the current Intranet of Things will evolve to a truly open Internet of Things, where constrained devices are first class citizens of the public Internet. However, the large amount of control over constrained networks offered by today's vertically integrated platforms, becomes even more important in an open IoT considering its promise of direct end-to-end interactions with constrained devices. In this paper a set of challenges is identified for controlling interactions with constrained networks that arise due to their constrained nature and their integration with the public Internet. Furthermore, a number of solutions are presented for overcoming these challenges by means of an intercepting intermediary at the edge of the constrained network.

The Constrained Application Protocol (CoAP) is a new Internet protocol that is currently being standardized. CoAP allows access to the drastically increasing number of smart objects and their sensing resources from virtually anywhere. It is a light-weight protocol designed to cope with the restrictions imposed by the limited resources (CPU, memory, power,...) of many smart objects. Depending on the application, information from individual objects might not be sufficient, reliable, or useful. An application may need to aggregate and/or compare data from a group of objects in order to obtain accurate results. Although multicast may be used to transmit the same request to several objects, multicast communication with smart objects has some disadvantages. Programming individual requests is another solution but lacks flexibility and opportunities for reusability. In this paper we propose a novel CoAP-based approach for communication with a group of resources across multiple smart objects. This approach organizes the group of resources that should be accessed into a new CoAP resource, called an entity, and nicely integrates several important aspects of entity management: creation, validation, usage and manipulation. In order to demonstrate the feasibility of this approach we present an implementation and experimental validation.

As embedded networks are evolving to open systems, it's becoming possible to create new applications on top of these existing embedded systems. However, developing new applications can be difficult due to the large diversity of protocols that exist today. In this paper, the authors demonstrate how employing the CoAP protocol can enable rapid application development by re-using well-known principles from the Web development world. Furthermore, we also demonstrate how a number of extensions to CoAP help to lower the barrier for developing applications even further.

In this paper we discuss the impact of proactive routing in comparison with a reactive routing approach in an environment where multiple communication technologies are used simultaneously. Therefore the Virtual Private Ad Hoc Networking platform will be introduced and used. A simulation environment is created and used to illustrate the outcomes with a simple scenario. Although many papers have been published comparing proactive and reactive routing protocols, this paper focusses on the impact on the VPAN platform with its two-level hierarchical architecture and nodes joining and leaving clusters.

In this paper we introduce the Virtual Private Ad Hoc Networking platform as an integrated solution for emergency communication and applications. This platform creates a virtual logical self-organizing network on top of existing network technologies reducing complexity and facilitating immediate availability. The architecture and its features will be explained in detail and matched against the specific communication needs of emergency applications.

An ad hoc network is an autonomous system of heterogeneous, mobile nodes that communicate with each other over wireless links. Routing protocols for these networks are inherently based on broadcasting control information and are therefore very bandwidth consuming. In order to limit the amount of routing information that has to be stored and maintained by the individual nodes, the technique of clustering is used. The network is partitioned into nonoverlapping sub networks, referred to as clusters, and one cluster node, the clusterhead, will take a leading role in the dissemination of control information. In this paper we approach the problem of finding an optimal partition that explicitly takes into account the heterogeneity of the network, as an integer linear programming (ILP) problem. In a second phase we have developed a new heuristic that approximates our ILP solution that is used in our clustering algorithm. It is shown that this heuristic tends to be more stable than existing clustering techniques that are solely based on ID number and/or connectivity and that do not take into account the heterogeneity of the network.