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The evolving landscape of cyber threats necessitates continuous advancements in defensive strategies. This paper explores the potential of artificial intelligence (AI) as an emerging tool to enhance cybersecurity. While AI holds widespread applications across information technology, its integration within cybersecurity remains a recent development. We offer a comprehensive review of current AI applications in this domain, focusing particularly on their preventative capabilities against prevalent threats like phishing, social engineering, ransomware, and malware. To illustrate these concepts, the paper presents a case study showcasing a specific AI application in a cybersecurity context. This case study addresses a critical gap in securing communication within resource-constrained Internet of Things (IoT) networks using the IEEE 802.15.4 standard. We discussed the advantages and limitations of employing PN sequence encryption for this purpose. [ABSTRACT FROM AUTHOR]

Summary The majority of wireless sensor network (WSN) systems include multiple data traffic with different service requirements. Small batteries are used to supply energy to the sensor nodes. This research work explores a new optimal hybrid MAC protocol for heterogeneous WSN to carry out efficient routing. The major intention of the designed protocol is the incorporation of features of both IEEE 802.15.4 and Low‐Energy Adaptive Clustering Hierarchy (LEACH) to solve the challenges. The energy‐saving circuit is adopted by predetermining the cluster heads (CHs), whereas the usual nodes are powered by a battery. Thus, it is suggested to extend the lifespan of network operation, where the designed hybrid protocol is intended to transfer the essential activities to the elected cluster heads when reducing the activity of the nodes. Here, a new optimizer known as the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is suggested for selecting the cluster heads and also for promoting the IEEE 802.15.4 protocol. This protocol is assisted to ensure performance regarding self‐healing, scalability, self‐reconfigurability, and energy efficiency. Thus, the performance evaluation is conducted in terms of various performance measures like throughput and energy consumption over the Adaptive Leach Protocol and multi‐channel MAC protocol with IEEE 802.15.4. [ABSTRACT FROM AUTHOR]

This paper addresses the limitations of existing interest forwarding strategies in Named Data Networks (NDN) over Low-power and Lossy Networks (LLNs). While current strategies utilize listening periods to minimize duplicate retransmissions, they suffer from indiscriminately propagating interests across the network, resulting in excessive retransmissions. Conversely, strategies with propagation control often neglect challenges posed by producer mobility. In response, we propose an efficient forwarding strategy that not only mitigates duplicate retransmissions but also governs interest propagation through the integration of probabilities and estimated distances to data producers. Additionally, the strategy adeptly manages producer mobility through judicious flooding control. In contrast to prior studies primarily benchmarking against Blind Flooding (BF) and Deferred Blind Flooding (DBF), our work presents the first comprehensive evaluation of the new forwarding scheme against six established strategies. Through extensive simulations, we demonstrate the superiority of our proposed forwarding solution across key performance metrics, including sent packets, retrieval latency, success rate, and energy consumption in various scenarios. [ABSTRACT FROM AUTHOR]

The backoff algorithm employed by the medium access control (MAC) protocol of the IEEE 802.15.4 standard has a significant impact on the overall performance of the wireless sensor network (WSN). This algorithm helps the MAC protocol resolve the contention among multiple nodes in accessing the wireless medium. The standard binary exponent backoff (BEB) used by the IEEE 802.15.4 MAC protocol relies on an incremental method that doubles the size of the contention window after the occurrence of a collision. In a previous work, we proposed the adaptive backoff algorithm (ABA), which adapts the contention window's size to the value of the probability of collision, thus relating the contention resolution to the size of the WSN in an indirect manner. ABA was studied and tested using contention window sizes of up to 256. However, the latter limit on the contention window size led to degradation in the network performance as the size of the network exceeded 50 nodes. This paper introduces the Improved ABA (I-ABA), an improved version of ABA. In the design of I-ABA we observe the optimal values of the contention window that maximize performance under varying probabilities of collision. Based on that, we use curve fitting techniques to derive a mathematical expression that better describes the adaptive change in the contention window. This forms the basis of I-ABA, which demonstrates scalability and the ability to enhance performance. As a potential area of application for I-ABA, we target wireless body area networks (WBANs) that are large-scale, that is, composed of hundreds of sensor nodes. WBAN is a major application area for the emerging Internet of Things (IoT) paradigm. We evaluate the performance of I-ABA based on simulations. Our results show that, in a large-scale WBAN, I-ABA can achieve superior performance to both ABA and the standard BEB in terms of various performance metrics. [ABSTRACT FROM AUTHOR]

IEEE 802.15.4-based industrial wireless sensor-actuator networks (WSANs) have been widely deployed to connect sensors, actuators, and controllers in industrial facilities. Configuring an industrial WSAN to meet the application-specified quality of service (QoS) requirements is a complex process, which involves theoretical computation, simulation, and field testing, among other tasks. Since industrial wireless networks become increasingly hierarchical, heterogeneous, and complex, many research efforts have been made to apply wireless simulations and advanced machine learning techniques for network configuration. Unfortunately, our study shows that the network configuration model generated by the state-of-the-art method decays quickly over time. To address this issue, we develop a MEta-learning based Runtime Adaptation (MERA) method that efficiently adapts network configuration models for industrial WSANs at runtime. Under MERA, the parameters of the network configuration model are explicitly trained such that a small number of optimization steps with only a few new measurements will produce good generalization performance after the network condition changes. We also develop a data sampling method to reduce the measurements required by MERA at runtime without sacrificing its performance. Experimental results show that MERA achieves higher prediction accuracy with less physical measurements, less computation time, and longer adaptation intervals compared to a state-of-the-art baseline. [ABSTRACT FROM AUTHOR]

Accurate localization of devices within Internet of Things (IoT) networks is driven by the emergence of novel applications that require context awareness to improve operational efficiency, resource management, automation, and safety in industry and smart cities. With the Integrated Localization and Communication (ILAC) functionality, IoT devices can simultaneously exchange data and determine their position in space, resulting in maximized resource utilization with reduced deployment and operational costs. Localization capability in challenging scenarios, including harsh environments with complex geometry and obstacles, can be provided with robust, reliable, and energy-efficient communication protocols able to combat impairments caused by interference and multipath, such as the IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol. This paper presents an enhancement of the TSCH protocol that integrates localization functionality along with communication, improving the protocol's operational capabilities and setting a baseline for monitoring, automation, and interaction within IoT setups in physical environments. A novel approach is proposed to incorporate a hybrid localization by integrating Direction of Arrival (DoA) estimation and Multi-Carrier Phase Difference (MCPD) ranging methods for providing DoA and distance estimates with each transmitted packet. With the proposed enhancement, a single node can determine the location of its neighboring nodes without significantly affecting the reliability of communication and the efficiency of the network. The feasibility and effectiveness of the proposed approach are validated in a real scenario in an office building using low-cost proprietary devices, and the software incorporating the solution is provided. The experimental evaluation results show that a node positioned in the center of the room successfully estimates both the DoA and the distance to each neighboring node. The proposed hybrid localization algorithm demonstrates an accuracy of a few tens of centimeters in a two-dimensional space. [ABSTRACT FROM AUTHOR]

Although wireless devices continuously gain communication capabilities, even state-of-the-art Industrial Internet of Things (IIoT) architectures, such as Internet Protocol version 6 over the Time-Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4 (6TiSCH), continue to use network-wide, fixed link configurations. This presents a missed opportunity to (1) forego the need for rigorous manual setup of new deployments; and (2) provide full coverage of particularly heterogeneous and/or dynamic industrial sites. As such, we devised the Multi-Modal Minimal Scheduling Function (3MSF) for the TSCH link layer, which, combined with previous work on the routing layer, results in a 6TiSCH architecture able to dynamically exploit modern multi-modal hardware on a per-link basis through variable-duration timeslots, simultaneous transmission, and routing metric normalization. This paper describes, in great detail, its design and discusses the rationale behind every choice made. Finally, we evaluate three basic scenarios through simulations, showcasing both the functionality and flexibility of our 6TiSCH implementation. [ABSTRACT FROM AUTHOR]

Today's software-defined networking (SDN) applications have many challenges. Its main applications are focused on networks with nodes with high processing capacity. Applying SDN technology in nodes operating on batteries with limited computing capabilities is challenging. In this context, this paper proposes SDN-enabled algorithms for the remote configuration of the default route to be applied in multi-hop wireless sensor networks (WSNs) with tree-type topology using the IEEE 802.15.4 protocol. The routing algorithm to define the default route of each node is executed in an SDN-enabled WSN controller (SDWSN). The SDWSN controller receives information on the state of the network, executes the Djikstra or Kruskal algorithms, and configures the default route of the nodes remotely. The best route selection is based on the battery level of the nodes and the distance between them. The results show that using network protocols to configure the nodes remotely is unnecessary. [ABSTRACT FROM AUTHOR]

RPL—Routing Protocol for Low-Power and Lossy Networks (usually pronounced "ripple")—is the de facto standard for IoT networks. However, it neglects to exploit IoT devices' full capacity to optimize their transmission power, mainly because it is quite challenging to do so in parallel with the routing strategy, given the dynamic nature of wireless links and the typically constrained resources of IoT devices. Adapting the transmission power requires dynamically assessing many parameters, such as the probability of packet collisions, energy consumption, the number of hops, and interference. This paper introduces Adaptive Control of Transmission Power for RPL (ACTOR) for the dynamic optimization of transmission power. ACTOR aims to improve throughput in dense networks by passively exploring different transmission power levels. The classic solutions of bandit theory, including the Upper Confidence Bound (UCB) and Discounted UCB, accelerate the convergence of the exploration and guarantee its optimality. ACTOR is also enhanced via mechanisms to blacklist undesirable transmission power levels and stabilize the topology of parent–child negotiations. The results of the experiments conducted on our 40-node, 12-node testbed demonstrate that ACTOR achieves a higher packet delivery ratio by almost 20%, reduces the transmission power of nodes by up to 10 dBm, and maintains a stable topology with significantly fewer parent switches compared to the standard RPL and the selected benchmarks. These findings are consistent with simulations conducted across 7 different scenarios, where improvements in end-to-end delay, packet delivery, and energy consumption were observed by up to 50%. [ABSTRACT FROM AUTHOR]

As an emerging technology that combines both digital and physical realms, access to information technology has expanded (IoT) the Internet of Things. The Internet of Things, as it becomes more pervasive, will overshadow human life as much as possible. Some of the major challenges associated with the development of this phenomenon have been the issue of security, which is needed in all its layers and even specifically in individual layers. According to the structure and applications of the Internet of Things, as well as the threats and challenges in cyberspace, we first examine security needs and then, by examining some methods of securing the Internet of Things, we propose a method according to the approaches discussed. [ABSTRACT FROM AUTHOR]

This paper introduces a preamble arbitration rule and interference suppression (PARIS) method for ultra-wideband (UWB) in-vehicle networks. Advancements in the automotive technology have led to increased reliance on wire harnesses, resulting in higher costs, electronic integration challenges, and adverse environmental effects. To address these problems, we explored the use of UWB wireless networks, which are characterized by low transmission power and superior signal penetration capabilities. A significant challenge associated with implementing UWB in automotive environments is the increased frame error rate (FER) caused by UWB interference. Our experiments indicate that vehicles equipped with identical UWB networks exhibit an FER of approximately 6% when positioned closely. This level of FER is problematic for automotive applications, where reliable communication is paramount. To mitigate this problem, we developed an PARIS communication algorithm that is robust against interference. As identified in this study, PARIS leverages two key characteristics of UWB. First, it prioritizes the timing of signal reception over radio signal power, enhancing interference suppression by activating the receiver at the optimal moment before the desired frame arrives, thereby minimizing data loss. Second, the algorithm exploits the hierarchical nature of preamble codes in simultaneously received frames, reducing data loss rate to the order of $10^{-5}$ by prioritizing frames from critical communication devices based on the preamble code hierarchy. Implementing the UWB-based PARIS method in wireless vehicle networks can reduce the weight of the wire harnesses by approximately 20%, offering a promising solution to the challenges posed by traditional wiring systems.

The evolving landscape of cyber threats necessitates continuous advancements in defensive strategies. This paper explores the potential of artificial intelligence (AI) as an emerging tool to enhance cybersecurity. While AI holds widespread applications across information technology, its integration within cybersecurity remains a recent development. We offer a comprehensive review of current AI applications in this domain, focusing particularly on their preventative capabilities against prevalent threats like phishing, social engineering, ransomware, and malware. To illustrate these concepts, the paper presents a case study showcasing a specific AI application in a cybersecurity context. This case study addresses a critical gap in securing communication within resource-constrained Internet of Things (IoT) networks using the IEEE 802.15.4 standard. We discussed the advantages and limitations of employing PN sequence encryption for this purpose.

Wireless Body Area Network (WBAN) is a cutting-edge technology that is being used in healthcare applications to monitor critical events in the human body. WBAN is a collection of in-body and on-body sensors that monitor human physical parameters such as temperature, blood pressure, pulse rate, oxygen level, body motion, and so on. They sense the data and communicate it to the Body Area Network (BAN) Coordinator. Themain challenge for the WBANis energy consumption. These issues can be addressed by implementing an effectiveMediumAccessControl (MAC) protocol that reduces energy consumption and increases network lifetime. The purpose of the study is to minimize the energy consumption and minimize the delay using IEEE 802.15.4 standard. In our proposed work, if any critical events have occurred the proposed work is to classify and prioritize the data. We gave priority to the highly critical data to get the Guarantee Tine Slots (GTS) in IEEE 802.15.4 standard superframe to achieve greater energy efficiency. The proposed MAC provides higher data rates for critical data based on the history and current condition and also provides the best reliable service to high critical data and critical data by predicting node similarity. As an outcome, we proposed aMAC protocol for VariableData Rates (MVDR). When compared to existingMACprotocols, theMVDR performed verywellwith lowenergy intake, less interruption, and an enhanced packet-sharing ratio. [ABSTRACT FROM AUTHOR]

Named-Data Networking (NDN) over Low Power and Lossy Networks (LLNs), employing IEEE 802.15.4 communication technology, is projected to provide native support for mobility and efficient content delivery for the emerging Internet of Things (IoT). While many interest forwarding strategies have been proposed for NDNs over LLNs, most existing studies have relied on software simulations to evaluate their performance due to the lack of analytical modeling tools. This paper introduces the first analytical model for estimating the Interest Satisfaction Ratio (ISR) in NDN over LLNs, which is a crucial metric for assessing the effectiveness of interest forwarding strategies. We develop the analytical model specifically for the broadcast forwarding strategy, which has been extensively studied due to its simplicity and ease of implementation. Simulation results confirm that the proposed model predicts the ISR with reasonable accuracy. The model is then used to elucidate the strong interaction between the CSMA/CA parameters of the IEEE 802.15.4 standard and the achieved ISR. [ABSTRACT FROM AUTHOR]

The backoff algorithm employed by the medium access control (MAC) protocol of the IEEE 802.15.4 standard has a significant impact on the overall performance of the wireless sensor network (WSN). This algorithm helps the MAC protocol resolve the contention among multiple nodes in accessing the wireless medium. The standard binary exponent backoff (BEB) used by the IEEE 802.15.4 MAC protocol relies on an incremental method that doubles the size of the contention window after the occurrence of a collision. In a previous work, we proposed the adaptive backoff algorithm (ABA), which adapts the contention window’s size to the value of the probability of collision, thus relating the contention resolution to the size of the WSN in an indirect manner. ABA was studied and tested using contention window sizes of up to 256. However, the latter limit on the contention window size led to degradation in the network performance as the size of the network exceeded 50 nodes. This paper introduces the Improved ABA (I-ABA), an improved version of ABA. In the design of I-ABA we observe the optimal values of the contention window that maximize performance under varying probabilities of collision. Based on that, we use curve fitting techniques to derive a mathematical expression that better describes the adaptive change in the contention window. This forms the basis of I-ABA, which demonstrates scalability and the ability to enhance performance. As a potential area of application for I-ABA, we target wireless body area networks (WBANs) that are large-scale, that is, composed of hundreds of sensor nodes. WBAN is a major application area for the emerging Internet of Things (IoT) paradigm. We evaluate the performance of I-ABA based on simulations. Our results show that, in a large-scale WBAN, I-ABA can achieve superior performance to both ABA and the standard BEB in terms of various performance metrics.

The advancement of networking, information, and communication technologies has fueled the popularity of Wireless Body Area Networks (WBANs) in both medical (remote patient monitoring) and non-medical sectors. Due to low, medium, and high data traffic requirements, WBAN performance suffers during the synchronization process that generates periodic beacon frames between sensor nodes and the coordinator. It also suffers when sensor nodes implicitly send data to the coordinator during the fixed time slot using the Contention Access Period (CAP). In this study, we propose a solution called Dynamic Next Beacon Interval and Superframe Duration Scheme (DNBISD) to tackle these issues of the IEEE 802.15.4 standard. This standard relies on a Beacon Interval (BI) and CAP for synchronization and data transmission between sensor nodes and the coordinator. However, the standard must adapt to BI and CAP's changing traffic load requirements, resulting in drawbacks such as prolonged packet delays, increased energy consumption, and potential data loss, particularly in real-time patient monitoring applications. In order to overcome these challenges, our DNBISD scheme employs a fuzzy approach to adapt the BI and CAP based on requested synchronization and data considering input parameters like packet received ratio and buffer ratio. The inference system utilizes the Takagi, Sugeno, and Kang (TSK) fuzzy model for rational quantitative analysis. Simulations demonstrate that our proposed scheme significantly enhances data transmission, boosts the average packet delivery ratio and throughput, and reduces the coordinator's average packet loss ratio and energy consumption. Consequently, this improvement allows for more efficient data transfer among numerous nodes within the specified superframe structure.

Multiple Gateways (GWs) provide network connectivity to Internet of Things (IoT) sensors in a Wide Area Network (WAN). The End Nodes (ENs) can connect to any GW by discovering and acquiring its periodic beacons. This provides GW diversity, improving coverage area. However, simultaneous periodic beacon transmissions among nearby GWs lead to interference and collisions. In this study, the impact of such intra-network interference is analyzed to determine the maximum number of GWs that can coexist. The paper presents a new collision model that considers the combined effects of the Medium Access Control (MAC) and Physical (PHY) layers. The model takes into account the partial overlap durations and relative power of all colliding events. It also illustrates the relationship between the collisions and the resulting packet loss rates. A performance evaluation is presented using a combination of analytical and simulation methods, with the former validating the simulation results. The system models are developed from experimental data obtained from field measurements. Numerical results are provided with Gaussian Frequency Shift Keying (GFSK) modulation. This paper provides guidance on selecting GFSK modulation parameters for low bit-rate and narrow-bandwidth IoT applications. The analysis and simulation results show that larger beacon intervals and frequency hopping help in reducing beacon loss rates, at the cost of larger beacon acquisition latency. On the flip side, the gateway discovery latency reduces with increasing GW density, thanks to an abundance of beacons. [ABSTRACT FROM AUTHOR]

Accurate localization of devices within Internet of Things (IoT) networks is driven by the emergence of novel applications that require context awareness to improve operational efficiency, resource management, automation, and safety in industry and smart cities. With the Integrated Localization and Communication (ILAC) functionality, IoT devices can simultaneously exchange data and determine their position in space, resulting in maximized resource utilization with reduced deployment and operational costs. Localization capability in challenging scenarios, including harsh environments with complex geometry and obstacles, can be provided with robust, reliable, and energy-efficient communication protocols able to combat impairments caused by interference and multipath, such as the IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol. This paper presents an enhancement of the TSCH protocol that integrates localization functionality along with communication, improving the protocol’s operational capabilities and setting a baseline for monitoring, automation, and interaction within IoT setups in physical environments. A novel approach is proposed to incorporate a hybrid localization by integrating Direction of Arrival (DoA) estimation and Multi-Carrier Phase Difference (MCPD) ranging methods for providing DoA and distance estimates with each transmitted packet. With the proposed enhancement, a single node can determine the location of its neighboring nodes without significantly affecting the reliability of communication and the efficiency of the network. The feasibility and effectiveness of the proposed approach are validated in a real scenario in an office building using low-cost proprietary devices, and the software incorporating the solution is provided. The experimental evaluation results show that a node positioned in the center of the room successfully estimates both the DoA and the distance to each neighboring node. The proposed hybrid localization algorithm demonstrates an accuracy of a few tens of centimeters in a two-dimensional space.

Although wireless devices continuously gain communication capabilities, even state-of-the-art Industrial Internet of Things (IIoT) architectures, such as Internet Protocol version 6 over the Time-Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4 (6TiSCH), continue to use network-wide, fixed link configurations. This presents a missed opportunity to (1) forego the need for rigorous manual setup of new deployments; and (2) provide full coverage of particularly heterogeneous and/or dynamic industrial sites. As such, we devised the Multi-Modal Minimal Scheduling Function (3MSF) for the TSCH link layer, which, combined with previous work on the routing layer, results in a 6TiSCH architecture able to dynamically exploit modern multi-modal hardware on a per-link basis through variable-duration timeslots, simultaneous transmission, and routing metric normalization. This paper describes, in great detail, its design and discusses the rationale behind every choice made. Finally, we evaluate three basic scenarios through simulations, showcasing both the functionality and flexibility of our 6TiSCH implementation.

Summary: With the development of 5G technology, the Internet of Things (IoT) system is becoming more and more widely used in various fields. However, the reliability issue still hinders the wide applications. For instance, the transmission reliability of the IoT system will be significantly affected by the status of end devices, wireless channel quality, and the environment. Moreover, according to the Automatic Repeat‐reQuest (ARQ) retransmission mechanism in the 802.15.4 protocol, if the IoT end devices pursue a conservative power model causing low signal transmission power, it is likely that the signal power will lose too much during the transmission process. This will result in the increase of the network packet loss rate and the power consumption during the data retransmission. To solve this problem, this paper proposes a reasonable transmission power allocation algorithm to ensure the transmission reliability, considering the ARQ retransmission mechanism. The algorithm intends to find the optimal transmission power of each IoT end device, so as to minimize the total energy consumption. The simulation results demonstrate that the power allocation algorithm improves the reliability of the IoT system, compared with other algorithms. [ABSTRACT FROM AUTHOR]

The paper discusses the operation of wireless sensor networks consisting of nodes based on the IEEE 802.15.4 ZigBee transceiver operating in the presence of Rayleigh or Nakagami-m fading, additive white Gaussian noise (AWGN) and interference. Analytical expressions for bit error rate (BER) for the IEEE 802.15.4 network were obtained when Rayleigh and Nakagami-m fading were processed with a selection-combining (SC) and maximum-ratio-combining (MRC) combiner and when AWGN and interference were present. Analytical results are presented graphically in the form of BER change, depending on the signal-to-noise ratio (SNR) for different values of network parameters: fading parameter (m), number of branches of MRC combiner (L), modulation parameter (M), and spreading sequence lengths (Lc). Graphical results are presented for the system when there are no combiners and when the SC and MRC combiners are included. Numerical results were confirmed by Monte Carlo simulation. Analysis of the SC and MRC combiner application impact on the performance improvement of the IEEE 802.15.4 network and the received signal was performed. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) have been utilized as communication infrastructure for smart grid applications. The primary requirement of WSNs for smart grid applications is to transmit delay-critical data from smart grid assets ether at the maximum rate or by reducing collision rates. Additionally, WSNs should utilize the limited resources of the network to provide the required long-term QoS. The achievement of these objectives requires a remarkable design of WSN protocols to satisfy the requirements of smart grid applications. In this study, a multi-channel cluster tree protocol is proposed to prevent collisions and increase network performance. In the proposed scheme, the cluster head serves to broadcast a beacon frame containing information on the allocated channels and time slots. This enables the new node to determine its channel and timeslot. A performance analysis reveals that the proposed scheme can achieve a low end-to-end delay and low collision rates compared with the well-known IEEE 802.15.4 MAC protocols widely used in the literature to provide QoS to smart-grid applications. [ABSTRACT FROM AUTHOR]

The increasing demand for Internet of Things (IoT) applications has resulted in vast amounts of data, requiring the utilization of big data analytics. The integration of big data analytics in IoT-based smart cities can greatly benefit from the development of wireless communication protocols, among which the Thread protocol has emerged as a promising option. Thread is IEEE 802.15.4 based and has advanced capabilities like mesh networking, IPv6 support, and multiple gateways providing no single point of failure. This paper presents the design and evaluation of a low-cost mesh network using Raspberry Pi, nRF52840 dongle, and OpenThread 1.2 (i.e., an open-source software implementation of the Thread protocol stack). The research elaborates on the hardware and software solutions used, as well as the network topologies adopted. To evaluate the performance of the developed system, extensive real-time tests are performed, considering parameters, such as jitter, packet loss, and round trip time. These tests effectively demonstrate the effectiveness of the Thread network. Furthermore, the impact of varying payload size and bitrate on the network is analyzed to understand its influence. The behavior of the multi-hop network is also examined under link failure scenarios, providing insights into the network's robustness. Our findings provide valuable insights for researchers interested in designing low-cost and efficient mesh networks for various IoT applications, including home automation, building/campus monitoring systems, distributed industrial IoT applications, and smart city infrastructure. [ABSTRACT FROM AUTHOR]

In recent years, extensive research has been conducted on the Internet of Things (IoT). Wireless Smart Ubiquitous Network (Wi-SUN) has gained considerable attention as a wireless communication standard for IoT. Wi-SUN Field Area Network (Wi-SUN FAN) is a technical specification of Wi-SUN that can be implemented in both indoor and outdoor IoT communication infrastructure with multi-hop routing. Although Wi-SUN FAN version 1.0 (Wi-SUN FAN 1.0) has been standardized by IEEE 2857–2021, there have been no studies or reviews conducted on the transmission performance of Wi-SUN FAN 1.0 regarding transmission success rate and delay time using computer simulations and experimental evaluation environments involving actual devices. In this study, the specifications of the Wi-SUN FAN are reviewed, and the fundamental transmission performance, such as average transmission success rate and average delay time, is measured using computer simulation as reference data. An experimental evaluation environment involving actual devices is developed to validate the characteristics evaluated by computer simulation. The characteristics determined by the computer simulation and experimental evaluation environment are in good agreement. Using the validated simulator, we evaluate the transmission performance in the wireless IoT environment with one border router and 100 routers randomly arranged in a flat square field with 4,000 m on a side. The average transmission success rate is approximately 1 at 1.00 × 10−1 s−1 or less. Consequently, Wi-SUN FAN 1.0 can communicate with a higher transmission success rate even when transmitting frequent IoT-data, which is once every ten seconds.

Wireless smart utility network (Wi-SUN) is one of the wireless communication technologies that realize the Internet of things (IoT). The existing Wi-SUN adopts frequency shift keying compliant with IEEE 802.15.4 for smart utility networks, also known as SUN-FSK, as its physical layer. However, owing to the increased demand for Wi-SUN applications, higher-performance communication methods even in severe fading environments with mobility are required. Orthogonal frequency-division multiplexing compliant with IEEE 802.15.4 is expected to be the most promising candidate for this. Studies on receiving methods have been conducted to accommodate high environment mobility. However, the maximum moving speed of the device is 200 km/h if diversity reception is adopted. In this study, we proposed two channel estimation methods to obtain accurate channel state information (CSI), particularly in a frequency selective fading environment with high mobility using the coherent and linear method. Further, we also proposed a Viterbi decoder with a likelihood ratio adjusted for CSI. Using the proposed channel estimation method and decoder, the required packet error rate of 10% is achieved at a maximum moving speed of 216 km/h by computer simulation. If a two-branch maximum ratio combining antenna diversity is used, the PER is achieved at 720 km/h.

The objective of IEEE 802.15.4 standard is to establish the foundation for a low-rate wireless personal area network that focuses on ubiquitous communication between devices while maintaining a reasonable data rate. Its popularity has increased significantly as a result of its implementation at low power and cheap cost, and the need to improve its performance has become a necessity. The most persistent issues are throughput, packet delivery ratio (PDR), packet loss ratio (PLR), and packet delay (PD). The advances in wireless technology place a strong emphasis on overcoming these problems. To accomplish stated goals, GFCO: A genetic fuzzy-logic approach to optimize channel of IEEE 802.15.4 LR-WPAN is proposed. It employs the $Fuzzy Logic Controller$ (FLC), and the $Genetic Algorithm$ (GA), by doing so, GA optimally modifies the FLC. For this, five algorithms are presented, Algorithm-1: GFCO for LR-WPAN, Algorithm-2: $GA_{1}$ for GFCO, Algorithm-3: $FLC_{1}$ for GFCO, Algorithm-4: $GA_{2}$ for GFCO, and Algorithm-5: $FLC_{2}$ for GFCO. The suggested GFCO approach is assessed for $Random Exponential Backoff$ (REB) algorithm, which was chosen as a fundamental algorithm, along with the $Survivability~Aware~Channel~Allocation$ (SACA) algorithm, taken as a benchmark study. Two scenarios are implemented in NS-3.20 in conjunction with fuzzylite in a hospital environment. First scenario is implemented in randomly deployed 10 sensors on a person’s body ( $2\times 2\,\,m^{2}$ area), whereas second scenario is implemented in $20\times 20\,\,m^{2}$ area of a ward in hospital having 10 to 50 persons. The simulated outcomes of both scenarios were recorded for REB, SACA, and GFCO. Simulated testing demonstrated that the proposed GFCO greatly enhanced performance of throughput 15.11%, SR 3.11%, PLR 3.11%, and PD 5.52% on average for scenario-I, whereas throughput 12.06%, SR 9.0%, PLR 9.0%, and PD 2.23% on average for scenario-II, as compared to SACA. Following that, these results are used to calculate the throughput, PDR, PLR, and PD and to draw a graphical representation. The proposed GFCO technique significantly improved efficiency, according to the results of the simulated testing.

Media transmission in the context of constrained IoT devices is of critical importance to support several solutions that enable interaction with the physical environment. This includes solutions that range from scenarios of occupancy estimation in building automation to traditional audio and image processing in remote sensing. Many modern access side IoT networks follow Event Driven Architecture (EDA) topologies that rely on brokers to forward messages between endpoints. The Message Queuing Telemetry Transport (MQTT) is one such protocol that can be used to encapsulate well known Real Time Protocol (RTP) audio and media packets. Unfortunately, MQTT relies on TCP transport that is not well suited in IoT constrained environments. This paper introduces a scheme that leverages some of the MQTT features to enable the reliable transmission of media in the context of Lossy Low Power Networks (LLNs). Specifically, this scheme is presented, analyzed, optimized and compared against other state-of-the-art mechanisms.

Time slotted channel hopping (TSCH) is an enhanced access mechanism for IEEE 802.15.4 that improves many aspects of the original protocol, like determinism and power consumption. Besides preventing collisions, time slotting allows motes to stay asleep for most of the time. In addition, channel hopping achieves more stable communication, in terms of packet losses and transmission latency, in spite of wireless spectrum variations. In this article, the specific effects of the latter mechanism are investigated from both qualitative and quantitative points of view. In particular, a thorough experimental campaign was carried out on real devices, deployed in a real environment and performing realistic data exchanges, when they are exposed to different interference conditions, to assess the benefits it brings over the case when transmissions are performed on a fixed-channel (FC). Experimental results confirm that, when the transmission frequency is kept repeatedly changing, communication quality is sensibly less affected by colocated Wi-Fi infrastructures, which makes the network behavior more predictable, and hence, intrinsically more dependable.

The Industrial Internet of Things (IIoT) requires wireless connectivity that meets the strict industrial requirements on metrics such as reliability and latency. Promising approaches include Time Slotted Channel Hopping (TSCH) media access, where nodes operate according to a schedule. Autonomously built schedules typically rely on shared resources, where reliability and latency may suffer depending on traffic scenarios and topologies. We have earlier proposed the Layered scheduler, which belongs to a new category of autonomous schedulers: Flow-based scheduling. Layered allocates resources to traffic flows, and as opposed to typical autonomous schedulers, dedicated resources are guaranteed to be scheduled at every hop from source to destination in a convergecast scenario. In addition, Layered minimizes the number of channels required through the novel employment of autonomous spatial reuse. We extend earlier theoretical analysis and simulations by evaluating Layered using the FIT IoT-LAB testbed and compare it to Orchestra and 6TiSCH Minimal scheduler. The experiments demonstrate the feasibility of spatial reuse and that Layered retains performance independent of network topology and traffic intensity - a desirable feature in industrial scenarios. The performance comes at the expense of energy consumption, which in the worst case is 75 % higher compared to Orchestra and Minimal. We also present lessons learned, such as the impact of TSCH configuration on RPL convergence, the benefits of black-listing on performance, and how co-located TSCH networks could be divided by channel offsets as opposed to physical channels. Lastly, we discuss flow-based scheduling in general, its properties, and future research areas.

Abstract It is well known that a wireless body area network (WBAN) is a special proposed wireless sensor network (WSN) that can assist in monitoring physiological signals for the evaluation and planning of patient treatment. One of the most challenging issues for WBANs is communication reliability, with acceptable communication efficiency and packet loss. To obtain such network characteristics, collision-free data transmission in networks of wireless sensor nodes is an interesting research problem. In this paper, the experiments of dynamic capabilities in several WBAN scenarios are focused, where the novelty and major contribution of our tests is that the effects of packet inter-arrival times, packet sizes, and the number of nodes deployed in the network, including human movements, indoor and outdoor environments, and transmitter and receiver positions, are all taken into consideration and evaluated. This is achieved by implementing the WBAN using IEEE 802.15.4 low-power sensor nodes. Experimental results illustrate the significant factors that impact the communication reliability of WBANs as measured by the packet delivery ratio (PDR). The experimental results show that the diverse environment testbed can affect network performance for WBAN data transmission. Our findings also show that the best network reliability needs to be set at more than 15 ms in packet interval time to achieve over 90% PDR for every test scenario. More details of the experimental results related to WBAN reliability obtained from all test cases are also discussed and summarized in the paper. To the best of our knowledge, our findings can be useful for users and researchers to consider the optimal point for WBAN setting and configuration to achieve the communication reliability requirements and also to deploy and develop a more reliable WBAN system.