Enhancing SDN WISE with Slicing Over TSCH

While IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) networks should be equipped to deal with the hard wireless challenges of industrial environments, the sensor networks are often still limited by the characteristics of the used physical (PHY) layer. Therefore, the TSCH community has recently started shifting research efforts to the support of multiple PHY layers, to overcome this limitation. On the one hand, integrating such multi-PHY support implies dealing with the PHY characteristics to fit the resource allocation in the TSCH schedule, and on the other hand, defining policies on how to select the appropriate PHY for each network link. As such, first a heuristic is proposed that is a step towards a distributed PHY and parent selection mechanism for slot bonding multi-PHY TSCH sensor networks. Additionally, a proposal on how this heuristic can be implemented in the IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH) protocol stack and its Routing Protocol for Low-power and Lossy network (RPL) layer is also presented. Slot bonding allows the creation of different-sized bonded slots with a duration adapted to the data rate of each chosen PHY. Afterwards, a TSCH slot bonding implementation is proposed in the latest version of the Contiki-NG Industrial Internet of Things (IIoT) operating system. Subsequently, via extensive simulation results, and by deploying the slot bonding implementation on a real sensor node testbed, it is shown that the computationally efficient parent and PHY selection mechanism approximates the packet delivery ratio (PDR) results of a near-optimal, but computationally complex, centralized scheduler.

Wireless sensor networks (WSNs) are becoming increasingly prevalent in numerous fields. Industrial applications and natural-disaster-detection systems need fast and reliable data transmission, and in several cases, they need to be able to cope with changing traffic conditions. Thus, time-slotted channel hopping (TSCH) offers high reliability and efficient power management at the medium access control (MAC) level; TSCH considers two dimensions, time and frequency when allocating communication resources. However, the scheduler, which decides where in time and frequency these communication resources are allotted, is not part of the standard. Orchestra has been proposed as a scheduler which allocates the communication resources based on information collected through the IPv6 routing protocol for low-power and lossy networks (RPL). Orchestra is a very elegant solution, but does not adapt to high traffic. This research aims to build an Orchestra-based scheduler for applications with unpredictable traffic bursts. The implemented scheduler allocates resources based on traffic congestion measured for the children of the root and RPL subtree size of the same nodes. The performance analysis of the proposed scheduler shows lower latency and higher packet delivery ratio (PDR) compared to Orchestra during bursts, with negligible impact outside them.

Wireless Sensor Nnetworks (WSNs) are becoming increasingly widespread owing to the introduction of the Internet of Things (IoT) and the networks' comparatively low cost and usability. WSNs are usually battery-powered, owing to their low power consumption, which however limits their computational performance. The lifetime of a WSN strongly depends on its communication-related power consumption. Time Slotted Channel Hopping (TSCH) solves the problem of power consumption by featuring both time-division and frequency- division multiplexing in the system's Media Access Control (MAC) layer. In this paper, Pruning-based Coloring Scheduling (PRCOS) is proposed, which is an algorithm for TSCH scheduling that accounts for the power consumption to extend the system's lifetime. Using mathematical analysis, we show that the proposed algorithm decreases the transfer time and energy consumption by factors of 0.43 and 0.57, respectively, compared with existing algorithms.

Autonomous and traffic-aware scheduling for TSCH networks

In the context of industrial applications, ensuring medium access control is a fundamental challenge. Industrial IoT devices are resource-constrained and must guarantee reliable communication while reducing energy consumption. The IEEE 802.15.4e standard proposed time-slotted channel hopping (TSCH) to meet the requirements of the industrial Internet of Things. TSCH relies on time synchronization and channel hopping to improve performance and reduce energy consumption. Despite these characteristics, configuring an efficient schedule under varying traffic conditions and interference scenarios remains a challenging problem. The exploitation of reinforcement learning (RL) techniques offers a promising approach to address this challenge. AI enables TSCH to dynamically adapt its scheduling based on real-time network conditions, making decisions that optimize key performance criteria such as energy efficiency, reliability, and latency. By learning from the environment, reinforcement learning can reconfigure schedules to mitigate interference scenarios and meet traffic demands. In this work, we compare various reinforcement learning (RL) algorithms in the context of the TSCH environment. In particular, we evaluate the deep Q-network (DQN), double deep Q-network (DDQN), and prioritized DQN (PER-DQN). We focus on the convergence speed of these algorithms and their capacity to adapt the schedule. Our results show that the PER-DQN algorithm improves the packet delivery ratio and achieves faster convergence compared to DQN and DDQN, demonstrating its effectiveness for dynamic TSCH scheduling in Industrial IoT environments. These quantifiable improvements highlight the potential of prioritized experience replay to enhance reliability and efficiency under varying network conditions.

In this paper SDN-WISE, a software defined networking (SDN) solution for wireless sensor networks, is introduced. Differently from the existing SDN solutions for wireless sensor networks, SDN-WISE is stateful and pursues two objectives: (i) to reduce the amount of information exchanged between sensor nodes and the SDN network controller, and (ii) to make sensor nodes programmable as finite state machines so enabling them to run operations that cannot be supported by stateless solutions. A detailed description of SDN-WISE is provided in this paper. SDN-WISE offers APIs that allow software developers to implement the SDN Controller using the programming language they prefer. This represents a major advantage of SDN-WISE as compared to existing solutions because it increases flexibility and simplicity in network programming. A prototype of SDN-WISE has been implemented and is described in this paper. Such implementation contains the modules that allow a real SDN Controller to manage an OMNeT++ simulated network. Finally, the paper illustrates the results obtained through an experimental testbed which has been developed to evaluate the performance of SDN-WISE in several operating conditions.

The IEEE 802.15.4-2015 TSCH (Time Slotted Channel Hopping) standard provides high-reliability, deterministic delay, and energy efficiency with the channel hopping and the TDMA. The standard does not specify the scheduling method, which is an essential part of the solution. One of the representative studies in TSCH scheduling is Orchestra. It is an autonomous scheduling method with minimal overhead that does not require a negotiation process between nodes. However, with high traffic load, performance of the Orchestra is greatly degraded because of its fixed schedule. If a node has children, continuous collisions occur in the slot of the node. We propose a novel algorithm called SRCA (Slot Reallocation for Collision Avoidance), as a solution for this problem. The SRCA autonomously updates the schedule. When a child requests a slot reallocation, the parent allocates a new slot with a low probability of collision. Another algorithm called SJCA (Slot reJection for Collision Avoidance) is further proposed in this work. It improves the SRCA to operate in an environment with interference where a sending node can disturb a transmission from a hidden node. In the SJCA, a node determines whether a collision due to interference will occur in the slot newly allocated by the parent. If so, it rejects the slot and requests again. We compare the performance of the SRCA and the SJCA against the Orchestra and e-TSCH-Orch through simulations. It is confirmed that the SJCA is robust to interference. In most cases, the SJCA shows better performance of PAR (Packet Acknowledgement Ratio), PLR (Packet Loss Rate), and latency than others. It is also verified that the SJCA provides high-reliability and low latency compared to existing technologies.

IEEE standardized a highly efficient, low power, reliable, deterministic and time–frequency enabled medium access control protocol, IEEE 802.15.4e time slotted channel hopping (TSCH) as an amendment to the medium access control (MAC) protocol defined by the IEEE 802.15.4 standard. Once a communication schedule is built, the IEEE 802.15.4e TSCH is able to execute such a communication schedule. IEEE 802.15.4e TSCH standard lea ves out of scope defining how that communication schedule is built, updated and maintained. In order to fill this gap, we introduce such a scheduling algorithm, called as DIVA. DIVA is specifically designed for IEEE 8092.15.4e TSCH networks. It is a totally distributed scheduling algorithm for divergecast traffic where divergecast means that traffic flows in all directions in contrast to convergecast where traffic flows from leave nodes to root. In order to gain more comprehension about DIVA, we conducted extensive simulations. We also compared DIVA with Berkeley’s Aloha-based algorithm.

The Internet Engineering Task Force 6TiSCH Working Group standardizes the protocol stack for the Industrial Internet of Things, which combines the industrial performance of IEEE802.15.4 time‐slotted channel hopping (TSCH) with the addressability and Internet integration capabilities of Internet Protocol version 6. The 6top Protocol, which is part of 6TiSCH, allows distributed management of the TSCH communication schedule. The Scheduling Function Zero (SF0) is the default algorithm for a node to decide when to add/remove cells to its neighbors. SF0 picks the cells to add randomly; hence, it is possible that 2 nearby pairs of nodes pick the same cell, resulting in a schedule collision. This article introduces cost‐aware cell relocation (CCR), which is a solution to detect and fix such schedule collisions in a distributed manner. CCR monitors the performance of individual cells and uses that information to detect collisions. When such a collision is detected on a cell, neighbor nodes communicate to relocate that cell to a different slot/channel in the TSCH schedule. We implement CCR and run it on a 5‐node network on the Internet of Things Laboratory testbed. The results show that, compared with today's SF0 and for the same traffic requirements, CCR increases the average packet delivery ratio by 2% and reduces the number of cells that need to be scheduled by 27.3%.

Industrial Wireless Sensor Networks (IWSNs) are found in many application domains that require low latency, robustness, and determinism. The IEEE 802.15.4 standard is not able to cope with the requirements of these applications. For this reason, the IEEE 802.15.4e amendment was introduced, which provides novel MAC-layer profiles that are optimized for a broad range of application domains, including process automation. This paper focuses on two of these profiles, i.e., the Deterministic and Synchronous Multi-channel Extension (DSME) and the Time Slotted Channel Hopping (TSCH). The aim of the paper is twofold. First, assessing their behavior in realistic process automation scenarios. Second, comparing their performance in terms of end-to-end delay, reliability and scalability. The ultimate aim of the work is identifying the limits of those protocols, thus paving the way to further work addressing suitable approaches to tackle them.

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.

The demand for reliable and energy-efficient low-power wireless network protocols is growing up steadily with the flourish of the emerging Internet of Things (IoT) applications. The Time Slotted Channel Hopping (TSCH), part of the IEEE 802.15.4 standard, represents the latest generation of low-power and highly reliable MAC protocols. It orchestrates the medium access according to a time-frequency communication schedule. Several scheduling algorithms have been introduced for TSCH. In contrast to centralized and distributed scheduling approaches, autonomous scheduling does not occur any signaling overhead and appears as a promising approach. In this study, we review autonomous TSCH scheduling algorithms, including static and recently proposed adaptive algorithms. Then, we investigate, on a real-world testbed, the performance of representative static autonomous scheduling schemes for TSCH protocol. Experimental results show that they suffer from high number of queued packets and buffers overflow, which increase the network delay and decreases the delivery ratio. Finally, we qualitatively compare and discuss the performance of recent adaptive autonomous TSCH scheduling algorithms, showing that research on adaptive autonomous TSCH scheduling still has open issues.

Wireless industrial sensor networks are wireless sensor networks which have been adapted to industrial applications. Most techniques for wireless sensor networks can be applied to wireless industrial sensor networks. However, for industrial applications of wireless industrial sensor networks, new requirements such as real-time, reliable delivery need to be considered. In this paper, we propose EARQ, which is a novel routing protocol for wireless industrial sensor networks. It provides real-time, reliable delivery of a packet, while considering energy awareness. In EARQ, a node estimates the energy cost, delay and reliability of a path to the sink node, based only on information from neighboring nodes. Then, it calculates the probability of selecting a path, using the estimates. When packet forwarding is required, it randomly selects the next node. A path with lower energy cost is likely to be selected, because the probability is inversely proportional to the energy cost to the sink node. To achieve real-time delivery, only paths that may deliver a packet in time are selected. To achieve reliability, it may send a redundant packet via an alternate path, but only if it is a source of a packet. Experimental results show that EARQ is suitable for industrial applications, due to its capability for energy efficient, real-time, reliable communications.

Emerging Industry 4.0 applications require ever-increasing amounts of data and new sources of information to more accurately characterize the different processes of a production line. Industrial Internet of Things (IIoT) technologies, and in particular Wireless Sensor Networks (WSNs), allow a large amount of data to be digitized at a low energy cost, thanks to their easy scalability and the creation of meshed networks to cover larger areas. In industry, data acquisition systems must meet certain reliability and robustness requirements, since other systems such as predictive maintenance or the digital twin, which represents a virtual mapping of the system with which to interact without the need to alter the actual installation, may depend on it. Thanks to the IEEE 802.15.4e standard and the use of Time-Slotted Channel Hopping (TSCH) as the medium access mechanism and IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) as the routing protocol, it is possible to deploy WSNs with high reliability, autonomy, and minimal need for re-configuration. One of the drawbacks of this communication architecture is the low efficiency of its deployment process, during which it may take a long time to synchronize and connect all the devices in a network. This paper proposes an analytical model to characterize the process for the creation of downstream routes in RPL, whose transmission of multi-hop messages can present complications in scenarios with a multitude of interfering nodes and resource allocation based on minimal IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH). This type of multi-hop message exchange has a different behaviour than the multicast control messages exchanged during the synchronization phase and the formation of upstream routes, since the number of interfering nodes changes in each retransmission.

Cognition is of paramount importance in modern communication systems for this brings the potential for adaptiveness and self-fine-tuning for dynamic reconfigurability. To achieve this feat, two primary tasks are to identify the influential configurable parameters and availability of comprehensive datasets representative of the real-world scenarios rather than simulated ones. For this article, an extensive dataset covering diverse settings of wireless sensor networks (WSNs) driven internet of things (IoT) is collected. It covers broad variations of 10 pre-configured communication parameters as well as some runtime information. In addition to legacy parameters (e.g., transmission power, and packet size, etc.), we also used two different medium access control protocols (i.e., carrier sense multiple access (CSMA) and time-slotted channel hopping (TSCH)), and routing metrics (i.e., objective function 0 (OF0), minimum rank with hysteresis (MRH), MRH with expected transmission count (ETX2)). Important quality of service (QoS) metrics like packet delivery ratio, throughput, and energy consumption against all combinations of the communication parameters are measured and recorded. A thorough statistical analysis is carried out to identify the correlations among the communication parameters and QoS metrics. The results lay the foundation for the design of a data-driven framework for predictive QoS control in the IoT.