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Detection and monitoring of airborne hazards using e-noses has been lifesaving and prevented accidents in real-world scenarios. E-noses generate unique signature patterns for various volatile organic compounds (VOCs) and, by leveraging artificial intelligence, detect the presence of various VOCs, gases, and smokes onsite. Widespread monitoring of airborne hazards across many remote locations is possible by creating a network of gas sensors using Internet connectivity, which consumes significant power. Long-range (LoRa)-based wireless networks do not require Internet connectivity while operating independently. Therefore, we propose a networked intelligent gas sensor system (N-IGSS) which uses a LoRa low-power wide-area networking protocol for real-time airborne pollution hazard detection and monitoring. We developed a gas sensor node by using an array of seven cross-selective tin-oxide-based metal-oxide semiconductor (MOX) gas sensor elements interfaced with a low-power microcontroller and a LoRa module. Experimentally, we exposed the sensor node to six classes i.e., five VOCs plus ambient air and as released by burning samples of tobacco, paints, carpets, alcohol, and incense sticks. Using the proposed two-stage analysis space transformation approach, the captured dataset was first preprocessed using the standardized linear discriminant analysis (SLDA) method. Four different classifiers, namely AdaBoost, XGBoost, Random Forest (RF), and Multi-Layer Perceptron (MLP), were then trained and tested in the SLDA transformation space. The proposed N-IGSS achieved "all correct" identification of 30 unknown test samples with a low mean squared error (MSE) of 1.42 × 10−4 over a distance of 590 m. [ABSTRACT FROM AUTHOR]

Acoustic energy mapping provides the functionality to obtain characteristics of acoustic sources, as: presence, localization, type and trajectory of sound sources. Several beamforming-based techniques can be used for this purpose. However, they rely on the difference of arrival times of the signal at each capture node (or microphone), so it is of major importance to have synchronized multi-channel recordings. A Wireless Acoustic Sensor Network (WASN) can be very practical to install when used for mapping the acoustic energy of a given acoustic environment. However, they are known for having low synchronization between the recordings from each node. The objective of this paper is to characterize the impact of current popular synchronization methodologies as part of the WASN to capture reliable data to be used for acoustic energy mapping. The two evaluated synchronization protocols are: Network Time Protocol (NTP) y Precision Time Protocol (PTP). Additionally, three different audio capture methodologies were proposed for the WASN to capture the acoustic signal: two of them, recording the data locally and one sending the data through a local wireless network. As a real-life evaluation scenario, a WASN was built using nodes conformed by a Raspberry Pi 4B+ with a single MEMS microphone. Experimental results demonstrate that the most reliable methodology is using the PTP synchronization protocol and audio recording locally. [ABSTRACT FROM AUTHOR]

The wireless sensor network is of great interest due to its special features and applications. Due to the computational limitation and power supply of these networks, hierarchical cluster routing is mentioned as a solution to improve the problem of energy consumption and network lifetime. In our study, a fuzzy-based clustering routing protocol was proposed that uses network zoning and node residual energy parameters, node distance to the center of each zone, and node-to-base station angle as fuzzy input for cluster head selection. In the proposed method with the aim of reducing network energy consumption, the responsibility of choosing CHs in each area, determining the area of each node, calculating the distance of each node to the center and calculating the angle of each node was assigned to the BS. The proposed method was carried out with Farahzadi, LEACH, MSCR protocols in terms of network lifetime evaluation criteria, stability period, selection and number of CH and average residual energy in MATLAB environment. The comparison of the results showed that the proposed method has performed better in terms of criteria, so that the network lifetime as one of the important indicators, the proposed method has improved by 50%, 40% and 20%, respectively, compared to LEACH, Farahzadi and MSCR methods. [ABSTRACT FROM AUTHOR]

Underwater acoustic sensor networks (UASNs) are challenged by the dynamic nature of the underwater environment, large propagation delays, and global positioning system (GPS) signal unavailability, which make traditional medium access control (MAC) protocols less effective. These factors limit the channel utilization and performance of UASNs, making it difficult to achieve high data rates and handle congestion. To address these challenges, we propose a reinforcement learning (RL) MAC protocol that supports asynchronous network operation and leverages large propagation delays to improve the network throughput.he protocol is based on framed ALOHA and enables nodes to learn an optimal transmission strategy in a fully distributed manner without requiring detailed information about the external environment. The transmission strategy of sensor nodes is defined as a combination of time-slot and transmission-offset selection. By relying on the concept of learning through interaction with the environment, the proposed protocol enhances network resilience and adaptability. In both static and mobile network scenarios, it has been compared with the state-of-the-art framed ALOHA for the underwater environment (UW-ALOHA-Q), carrier-sensing ALOHA (CS-ALOHA), and delay-aware opportunistic transmission scheduling (DOTS) protocols. The simulation results show that the proposed solution leads to significant channel utilization gains, ranging from 13% to 106% in static network scenarios and from 23% to 126% in mobile network scenarios.oreover, using a more efficient learning strategy, it significantly reduces convergence time compared to UW-ALOHA-Q in larger networks, despite the increased action space. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of fixed-time consensus tracking for a class of nonlinear multi-agent systems subject to unknown disturbances. Firstly, a modified fixed-time disturbance observer is devised to estimate the unknown mismatched disturbance. Secondly, a distributed fixed-time neural network control protocol is designed, in which neural network is employed to approximate the uncertain nonlinear function. Simultaneously, the technique of command filter is applied to fixed-time control, which circumvents the "explosion of complexity" problem. Under the proposed control strategy, all agents are enable to track the desired trajectory in fixed-time, and the consensus tracking error and disturbance estimation error converge to an arbitrarily small neighborhood of the origin, meanwhile, all signals in the closed-loop system remain bounded. Finally, a simulation example is provided to validate the effectiveness of the presented design method. [ABSTRACT FROM AUTHOR]

Computing directed Minimum Spanning Tree ( D M S T ) is a fundamental problem in graph theory. It is applied in a wide spectrum of fields from computer network and communication protocol design to revenue maximization in social networks and syntactic parsing in Natural Language Processing. State-of-the-art solutions are online algorithms that compute  D M S T  for a given graph and a root. For multi-query requirements, the online algorithm is inefficient. To overcome the drawbacks, in this paper, we propose an indexed approach that reuses the computation result to facilitate single and batch queries. We store all the potential edges of  D M S T  in a hierarchical tree in  O (n)  space complexity. Furthermore, we answer the  D M S T  query of any root in  O (n)  time complexity. Experimental results demonstrate that our approach can achieve a speedup of 2–3 orders of magnitude in query processing compared to the state-of-the-art while consuming O(n) index size. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a system of machines, computing devices, electronic equipment, and different sensors. It forms a network, where the transmission of device-related data can be accomplished. The devices in the IoT are connected to each other through wireless links and form ad-hoc networks. In IoT based applications, the lifetime of the communicating nodes is a greater concern. The network lifetime can be maximized by introducing energy efficient data transmission in the network. Therefore, a traffic and delay-aware energy-efficient routing (TADEER) protocol for IoT-based networks are proposed in this work. The proposed technique assigns delay for transmitting data based on the criticality level of data and traffic rate at the forwarding nodes. Fixing delays for data transmission helps to avoid unnecessary transmissions. The route selection process is implemented using an optimization algorithm. A Fuzzy logic (FL) based biogeography-based optimization (BBO) algorithm is presented in this work. Thus, the number of data transmission and energy consumption can be reduced. The performance of the proposed method is evaluated by analyzing transmission delay, network lifetime, and energy consumption. By comparing the simulation results to the existing methods TEAR and ETASA, the simulation results are validated. [ABSTRACT FROM AUTHOR]

Today's Internet is built on decades-old networking protocols that lack scalability, reliability and security. In response, the networking community has developed path-aware Internet architectures that solve these problems while simultaneously empowering end hosts to exert some control on their packets' route through the network. In these architectures, autonomous systems authorize forwarding paths in accordance with their routing policies, and protect these paths using cryptographic authenticators. For each packet, the sending end host selects an authorized path and embeds it and its authenticators in the packet header. This allows routers to efficiently determine how to forward the packet. The central security property of the data plane, i.e., of forwarding, is that packets can only travel along authorized paths. This property, which we call path authorization, protects the routing policies of autonomous systems from malicious senders. The fundamental role of packet forwarding in the Internet's ecosystem and the complexity of the authentication mechanisms employed call for a formal analysis. We develop IsaNet, a parameterized verification framework for data plane protocols in Isabelle/HOL. We first formulate an abstract model without an attacker for which we prove path authorization. We then refine this model by introducing a Dolev–Yao attacker and by protecting authorized paths using (generic) cryptographic validation fields. This model is parametrized by the path authorization mechanism and assumes five simple verification conditions. We propose novel attacker models and different sets of assumptions on the underlying routing protocol. We validate our framework by instantiating it with nine concrete protocol variants and prove that they each satisfy the verification conditions (and hence path authorization). The invariants needed for the security proof are proven in the parametrized model instead of the instance models. Our framework thus supports low-effort security proofs for data plane protocols. In contrast to what could be achieved with state-of-the-art automated protocol verifiers, our results hold for arbitrary network topologies and sets of authorized paths. [ABSTRACT FROM AUTHOR]

Evaluate the differences between clinical visual acuity (VA) as recorded in medical records and electronic Early Treatment Diabetic Retinopathy Study (eETDRS) protocol VA measurements and factors affecting the size of the differences. Retrospective chart review. Study and fellow eyes of participants enrolled in DRCR Retina Network Protocols AC and AE (diabetic macular edema), and W (nonproliferative diabetic retinopathy) with clinical VA recorded within 3 months before the protocol visit. Differences and their association with patient and ocular factors were evaluated using linear mixed models with random effects for correlations within sites and participants. Difference between VA letter scores measured by eETDRS during a study visit versus measured by Snellen during a regular clinical visit (Snellen fraction converted to eETDRS). Data from 1016 eyes (511 participants) across 74 sites were analyzed. The mean VA measurements were 68.6 letters (Snellen equivalent 20/50) at the clinical visit and 76.3 letters (Snellen equivalent 20/32) at the protocol visit, with a mean (standard deviation [SD]) of 26 (21) days between visits. Mean (SD) protocol VA was better than clinical VA by 7.6 (9.6) letters overall, 10.7 (12.6) letters in eyes with clinical VA ≤ 20/50 (n = 376), and 5.8 (6.6) letters in eyes with clinical VA ≥ 20/40 (n = 640). On average, the difference between clinical and protocol VA was 1.3 letters smaller for every 1-line (5 letters) increase in clinical VA (P < 0.001). Mean (SD) differences by clinical correction of refractive error were 3.9 (9.0) letters with refraction, 6.9 (9.2) letters with glasses/contact lenses, 7.9 (11.5) letters with pinhole, and 9.8 (9.3) letters without correction (P = 0.06). On average, clinical Snellen VA is 1 to 2 lines worse than eETDRS protocol refraction and VA testing, which may partly explain why clinical practice does not always replicate clinical trial results. Eyes with lower clinical measurements and eyes tested without clinical refraction tended to have larger differences. Considering the potential discrepancies between clinical and protocol VA measurements, refracting eyes in the clinic may benefit patients when determining treatment plans and study referrals based on vision. Proprietary or commercial disclosure may be found after the references. [ABSTRACT FROM AUTHOR]

In order to solve the problem that there are a large number of unknown protocols on the network, which affect the network management and network security in varying degrees, an unknown binary protocol identification method is proposed. On the premise that the center cluster of unknown protocols is obtained by the clustering algorithm, the unknown protocols for network traffic are identified by combining one-class of classification with one-dimensional CNN classification technology. At first, a class of classification algorithm is used to select the unknown protocols, and then, the labeled protocol data obtained by clustering are used to train the one-dimensional CNN model, and the classified binary protocol packets are directly used as the input of the one-dimensional convolution neural network. After the classification of the CNN model, the unknown protocols are finally identified. The experimental results show that the proposed classification and recognition method is better than the traditional CNN and SVM algorithms, and the maximum frequency pooling is better than the traditional pooling method. [ABSTRACT FROM AUTHOR]

Currently, the proportion of unknown traffic in networks continues to increase. This poses great challenges to the management and security of cyberspace. The unknown traffic refers to network traffic generated by previously unknown protocols in a preconstructed traffic identification system. Measures to address this challenge can be developed by grouping the mixed unknown traffic into multiple clusters, where, ideally, each cluster contains just one traffic class. In this paper, we propose a novel scheme for clustering unknown traffic, named dual-path autoencoder-based clustering, to discover protocol-based traffic classes. The dual-path autoencoder model refers to the combination of convolutional autoencoder and deep autoencoder, which realizes the extraction and aggregation of payload features and statistical features. Then, the fusion feature is clustered by the correlation-adjusted clustering module, and the unknown traffic flows are divided into multiple high-purity clusters. To evaluate our scheme, experiments are conducted on two public network traffic datasets and one campus network dataset. Using seven common application layer protocols to simulate unknown traffic, the evaluation results show that our scheme can achieve above 98% on each dataset when the preset number of clusters is 60. This establishes the effectiveness of the proposed scheme for clustering unknown network protocols. [ABSTRACT FROM AUTHOR]

Next-generation Internet-of-Things applications pose challenges for sixth-generation (6G) mobile networks, involving large bandwidth, increased network capabilities, and remarkably low latency. The possibility of using ultra-dense connectivity to address the existing problem was previously well-acknowledged. Therefore, placing base stations (BSs) is economically challenging. Drone-based stations can efficiently address Next-generation Internet-of-Things requirements while accelerating growth and expansion. Due to their versatility, they can also manage brief network development or offer on-demand connectivity in emergency scenarios. On the other hand, identifying a drone stations are a complex procedure due to the limited energy supply and rapid signal quality degradation in air-to-ground links. The proposed method uses a two-layer optimizer based on a pre-trained VGG-19 model to overcome these issues. The non-orthogonal multiple access protocol improves network performance. Initially, it uses a powerful two-layer optimizer that employs a population of micro-swarms. Next, it automatically develops a lightweight deep model with a few VGG-19 convolutional filters. Finally, non-orthogonal multiple access is used to schedule radio and power resources to devices, which improves network performance. We specifically examine how three scenarios execute when various Cuckoo Search, Grey Wolf Optimization, and Particle Swarm Optimization techniques are used. To measure the various methodologies, we also run non-parametric statistical tests, such as the Friedman and Wilcoxon tests. The proposed method also evaluates the accuracy level for network performance of DBSs using number of Devices. The proposed method achieves better performance of 98.44% compared with other methods. [ABSTRACT FROM AUTHOR]

Summary: Recently, much of the wireless personal area network (WPAN) research concerns network protocols, scheduling, and security challenges but the major issue of resource utilization has been very rarely investigated. The design of resource sharing in a network gets more attention when the number of users increases. While optimizing performance, resource utilization plays a critical role. In this paper, the numerical performance of a wireless resource utilization algorithm for a bi‐partite scatternet is presented. This algorithm is focused to enhance the bandwidth allocation and power utilization of wireless scatternets. Every node can communicate with a single neighbor at a time with minimum resources. Finally, the performances of the RUBI algorithm are shown. This algorithm is compared with the existing algorithms such as the load adaptive scheduling algorithm and pseudorandom coordinated scheduling scheme in terms of various parametric metrics like reliability, throughput, collision probability, transmission probability, and signal‐to‐noise ratio (SINR). The proposed L‐RUBI achieves 93.4% of reliability, 93.6% of transmission probability, 91.4% of throughput, 76.8% of collision performance, and 72.2% SINR. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a global network of interconnected computing, sensing, and networking devices that can exchange data and information via various network protocols. It can connect numerous smart devices thanks to recent advances in wired, wireless, and hybrid technologies. Lightweight IoT protocols can compensate for IoT devices with restricted hardware characteristics in terms of storage, Central Processing Unit (CPU), energy, etc. Hence, it is critical to identify the optimal communication protocol for system architects. This necessitates an evaluation of next-generation networks with improved characteristics for connectivity. This paper highlights significant wireless and wired IoT technologies and their applications, offering a new categorization for conventional IoT network protocols. It provides an in-depth analysis of IoT communication protocols with detailed technical information about their stacks, limitations, and applications. The study further compares industrial IoT-compliant devices and software simulation tools. Finally, the study provides a summary of the current challenges, along with a broad overview of the future directions to tackle the challenges, in the next IoT generation. This study aims to provide a comprehensive primer on IoT concepts, protocols, and future insights that academics and professionals can use in various contexts. [ABSTRACT FROM AUTHOR]

Video communication gained wide popularity since it offers a more real-time mode of face-to-face interaction. This paper mainly aims to enhance the video transmission quality of multimedia applications via communication network security improvement and an adaptive resource allocation strategy. The main aim of the resource allocation strategy is to achieve efficient usage of spectrum resources since video communication utilizes the orthogonal subcarriers for data transmission and the need for conversion of non-flat channels to flat. An optimized Hybrid Deep Random Neural Network (HDRaNN) architecture is used to overcome the adaptive spectrum resource allocation problem in the single-frequency network transmission by taking into account the different time–frequency resources and regions for overlapping areas and the same time–frequency for non-overlapping areas. The Sheep Flock Optimization algorithm is used to minimize the network error rate of the HDRaNN architecture by optimizing the weights and biases. The basic purpose of communication network security in this paper is to ensure that data communicated over a network connection are safe and secure. The network security protocol offers protection from unauthorized data retrieval and attempts to obtain data. The protocols utilized for secure communication in the proposed technique are Secure Hypertext Transfer Protocol, Secure Socket Layer, Simple Network Management Protocol, and Secure File Transfer Protocol. This protocol also assures that unauthorized users, devices, or services do not have access to your network data and works on all network mediums and data types. The extensive experiments conducted using the proposed methodology show improvements in the video transmission quality in terms of high diversity gain, security, increased throughput, and minimized bit error rate. [ABSTRACT FROM AUTHOR]

Blockchain is increasingly gaining interest in both the academic and professional worlds. The implementation of this decentralised and distributed network has started taking place, firstly in the financial world and in recent years reaching to other industries. Nevertheless, not all blockchain networks are the same, and choosing the right consensus algorithm is important for companies willing to invest in this technology. Companies eager to implement blockchain should understand the underlying architecture when selecting a particular network. Through an in-depth analysis, this paper aims to explore and compare from a technical perspective the three biggest permissionless blockchain networks by market capitalisation: Bitcoin, Ethereum and Ripple. Our research shows that Bitcoin gains a competitive advantage as a widely adopted means of payment, Ethereum excels in adopting a robust and flexible smart contract functionality whilst Ripple is most suitable for cross-border payments due to its scalability and fast processing speed. Based on the comprehensive analysis of the networks and their consensus protocols, this paper is designed to set the ground for further studies on the emerging applications of blockchain in numerous sectors. [ABSTRACT FROM AUTHOR]

The advancement of the Internet of Things (IoT) has tremendously influenced many fields of human life. The Internet of Medical Things, Internet of Flying Things, Internet of Floating Things and Internet of Autonomous Things are recent evolution of IoT. The protocols used in all forms of IoT are critical during the execution demanding formal verification methods to ensure correctness. However, the most challenging part of formal verification is abstracting the system under test, making many systems unverified. Formal protocol verification is essential for detecting specification and design flaws that go undetected and corrected during the testing phase. This paper proposes novel methods for abstracting communication patterns for IoT protocols. Message broadcasts, periodic message advertisements, topology encoding, and topology change are examples of communication patterns. An attempt is made to model these patterns using pi-calculus and PROMELA. Finally, the trickle, a wireless sensor network dissemination protocol, has been modelled using pi-calculus and PROMELA. The Spin model checker verifies design flaws, such as deadlocks and non-progress cycles. The verification results ensure that there are no deadlocks or non-progress loops. The protocol is statically verified for message transmission semantics. The analysis revealed that the protocol could only guarantee message transmission for lossy connections if an alternative route covers all other nodes. The empirical results and theorem show that the abstraction mechanism can be directly utilised for automated and theoretical verification. Researchers can use the abstraction framework described in this paper to create validation models for static and automated verification of existing and new IoT protocols. [ABSTRACT FROM AUTHOR]

The 802.11ah standard is a new energy-efficient, wireless networking protocol which allows thousands of indoor and outdoor devices to be connected to the same access point. The Centralized Authentication Control (CAC) method, described in the standard, enables up to 8000 stations to be authenticated and associated with the same access point. A baseline implementation of the CAC method has been reported; however, it suffers from a few limitations. In this paper, an efficient methodology is proposed to minimize the CAC method's association time. The proposed methodology allows the association of a large number of stations by predicting the size of the network followed by selecting the best step size that will enable fast association between the access point and the stations of the network. The methodology consists of three stages. The first stage provides a baseline implementation of the 802.11ah standard, while the second stage eliminates the effect of too large or too small step sizes. The third stage finds the optimal step size and step repeat for each network size and predicts network size based on queue size. The performance of the proposed methodology is evaluated and compared in terms of total association time, number of total trials and percentage of ineffective trials. The methodology outperforms the baseline implementation by achieving a 30% reduction in the total association time, 30% reduction in the total number of trials and 45% reduction in the total number of ineffective trials. [ABSTRACT FROM AUTHOR]

Most of the existing sender-based message logging protocols cannot commonly handle simultaneous failures because, if both the sender and the receiver(s) of each message fail together, the receiver(s) cannot obtain the recovery information of the message. This unfortunate situation may happen due to their asymmetric logging behavior. This paper presents a novel sender-based message logging protocol for broadcast network based distributed systems to overcome the critical constraint of the previous ones with the following three features. First, when more than one process crashes at the same time, the protocol enables the system to ensure the always no rollback property by symmetrically replicating the recovery information at each process or group member connected on a network. Second, it can make the first feature persist even if the general form of communication for the system is a combination of point-to-point and group ones. Third, the communication overhead resulting from the replication can be highly lessened by making full use of the capability of the standard broadcast network in both communication modes. Experimental outcomes verify that, no matter which communication patterns are applied, it can reduce about 4.23∼9.96% of the total application execution time against the latest enabling the traditional ones to cope with simultaneous failures. [ABSTRACT FROM AUTHOR]

Introduction: Patent ductus arteriosus (PDA) is one of the most common congenital heart diseases. Once the PDA is diagnosed, it needs to be dealt with in time. At present, main methods include pharmacological treatment, surgical closure, and interventional closure for treatment of PDA. However, the effect of different interventions in PDA management is still controversial. Thus, our study aims to assess the effectiveness of different interventions together and estimate the sequence of these therapies for PDA children. Meanwhile, it is necessary to conduct a Bayesian network meta-analysis to compare the safety of different interventions comprehensively. Methods and analysis: To the best of our knowledge, this is the first Bayesian network meta-analysis comparing the efficacy and safety of different interventions for the treatment of PDA. PubMed, Embase, Cochrane Library, Web of Science, gray literature, and trial registry databases were searched from inception to December 2022. We will extract and report data according to methodological guidelines for Bayesian network meta-analysis by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). Primary PDA closure, overall PDA closure, technical success, surgical success rate, mortality during hospital stay, operation time, intensive care unit stay, intraoperative radiation dose, radiation exposure time, total postoperative complication rate, and postoperative major complication rate will be defined as the outcomes. The quality of all random studies will be assessed using ROB, and quality of evidence for all outcomes will be judged by using the Grading of Recommendations Assessment, Development and Evaluation (GRADE). Ethics and dissemination: The results will be disseminated through peer-reviewed publication. Since no private and confidential patient data will be contained in the reporting, there are no ethical considerations associated with this protocol. Systematic review registration: INPLASY2020110067. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) approach relies on the use of the Internet Protocol (IP) as a pervasive network protocol. IP acts as a "glue" for interconnecting end devices (on the field side) and end users, leveraging on very diverse lower-level and upper-level protocols. The need for scalability would suggest the adoption of IPv6, but the large overhead and payloads do not match with the constraints dictated by common wireless solutions. For this reason, compression strategies have been proposed to avoid redundant information in the IPv6 header and to provide fragmentation and reassembly of long messages. For example, the Static Context Header Compression (SCHC) protocol has been recently referenced by the LoRa Alliance as a standard IPv6 compression scheme for LoRaWAN-based applications. In this way, IoT end points can seamlessly share an end-to-end IP link. However, implementation details are out of the specifications' scope. For this reason, formal test procedures for comparing solutions from different providers are important. In this paper, a test method for assessing architectural delays of real-world deployments of SCHC-over-LoRaWAN implementations is presented. The original proposal includes a mapping phase, for identifying information flows, and a subsequent evaluation phase, in which flows are timestamped and time-related metrics are computed. The proposed strategy has been tested in different use cases involving LoRaWAN backends deployed all around the world. The feasibility of the proposed approach has been tested by measuring the end-to-end latency of IPv6 data in sample use cases, obtaining a delay of less than 1 s. However, the main result is the demonstration that the suggested methodology permits a comparison of the behavior of IPv6 with SCHC-over-LoRaWAN, allowing the optimization of choices and parameters during deployment and commissioning of both infrastructure components and software. [ABSTRACT FROM AUTHOR]

There is a large number of connected devices in the Internet of Things (IoT) networks that are typically several orders of magnitude bigger than enterprise networks and campus networks. The exponential increase in the number of interconnected smart devices is expected to exceed 60 billion smart objects shortly. The requirements needed for IoT networks are scalability, low power consumption, and simplified routing and security protocols. IoT networks are also heterogeneous, composing different types of networks together. Legacy network protocols like IPv4 has deemed to be inefficient for IoT networks. As the number of IPv4 addresses is almost consumed with regular network devices, we propose the use of IPv6 addressing for IoT-connected devices as IPv4 cannot accommodate the scalability requirement of IoT. IPv6 provides extended address space and enhanced mobility which are very essential for IoT networks. In this research, we apply IPv6 to IoT networks to avoid the scalability bottleneck of the IPv4 subnet. IPv6 accommodates a large number of connected devices and solves issues resulting from the heterogeneous nature and access methods of IoT devices. However, IPv6 is a large protocol that does not suit itself well in the IoT world. The Maximum Transmission Unit (MTU) permitted for IEEE 802.15.4 MAC data frames with their encapsulated IPv6 packet is limited to 127 bytes. We need 40 bytes for the uncompressed IPv6 header and 8 bytes are needed for the uncompressed UDP header. As a result, there are either 54 bytes left for the payload when security is not considered or 33 bytes when security is considered. We investigate throughput improvement for IoT networks by applying adaptation to IPv6 through header compression with UDP header compression. We also apply fragmentation for MAC frames that exceed the 127 bytes MTU limit. Simulation results showed that IPv6 compression with or without fragmentation serves toward adapting IPv6 packets to IoT networks. In the case of applying fragmentation, the technique of fragment forwarding greatly enhances the performance. Network traffic within the same network can be compressed to 2 bytes. On leaving the 802.15.4 network, the header increases to 12 bytes if the network prefix is known or to 20 bytes if the network prefix is unknown. Two evaluation metrics, namely, Compression Gain and Packet Delivery Ratio were applied to our proposed implementation method to prove the validity and the efficiency of our proposal. [ABSTRACT FROM AUTHOR]

Wireless body area networks are communication networks between the sensors and hubs in-body, on-body and out-body. IEEE 802.15.6 protocol has been developed for such networks. In this study, modulation techniques proposed in IEEE 802.15.6 ultra-broadband physical layer were compared with orthogonal frequency division multiplexing based dual carrier modulation techniques in wireless body area networks channels. The dual carrier modulation is defined with 16-quadrature amplitude modulation constellation diagrams. In order to have reliable communication, dual carrier modulation with lower level modulations such as quadrature amplitude modulation and binary phase shift keying constellation diagrams has been presented in this study. IEEE 802.15.6 ultra-broadband physical layer has been simulated and compared with the dual carrier modulation and types discussed on the same wireless body area networks channels and according to the timing parameters proposed in the protocol. Performance results have been given as bit error rate—signal to noise ratio graphs. At low data rates, it was observed that the performances were high, while the dual carrier modulation performances were even higher. Due to the high dispersion of wireless body area networks channels, the performances of both protocol modulations and dual carrier modulations are quite low in wireless body area networks channels at high data rates. Therefore, at high data rates, a suitable channel equalizer or high number of subcarriers should be used for modulations with orthogonal frequency division multiplexing because of the high tap number of wireless body area network channel. By using dual carrier modulation with higher subcarrier, better performance results are achieved with trade off hardware complexity. [ABSTRACT FROM AUTHOR]

This research aims to validate the functionality of an industrial network in proprietary protocols such as CIP, DeviceNet, DH-485 and open protocols such as Ethernet/IP between Allen Bradley equipment. This industrial network allows monitoring and controlling through an HMI Panel View Plus 1000 screen connected in Ethernet/IP to all devices connected to the network, such as ControlLogix L61, CompacLogix L32E and MicroLogix 1100 controllers. In addition, in the same network the computer, where the programming of each controller and the design of the HMI is performed, is connected. In the graphical interface, each protocol has a window that shows the parameters that can be monitored and controlled. With the CIP protocol, there are two ControlLogix L61 controllers, one is a producer and the other a consumer. DeviceNet communication has been incorporated with the CompacLogix L32E controller, with a scanner module for DeviceNet, which allows controlling two motors, one for each device, in addition, DH485 communication, where there is a MicroLogix 1100 controller, the View 600 Panel accesses test programs of the PLC MicroLogix 1100 and the SLC 5/05 through different display screens. From the research a functional industrial network capable of communicating and linking different Allen Bradley equipment in different protocols, demonstrating the reliability of the use of networks in an industry to communicate actuators and controllers, has been obtained. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a network of smart objects connected via the Internet, where each object is identified by a unique, accessible, and programmable address, while Blockchain is a technology for storing and transmitting information based on a decentralized system such that the centralized validation of transactions is replaced by a consensus mechanism. The integration of these two technologies requires consensus protocols to overcome the major challenges encountered in IoT systems, including issues related to security, storage capacity limits, computing power, etc. Therefore, different consensus algorithms have been implemented. For this purpose, this paper presents a research study on the criteria that would render a Blockchain consensus algorithm suitable for IoT networks, namely, computing power, latency, storage capacity, and security. [ABSTRACT FROM AUTHOR]

Named Data Networking (NDN) is an implementation of Information-Centric Networking (ICN) that has emerged as a promising candidate for the Future Internet Architecture (FIA). In contrast to traditional networking protocols, NDN's focus is on content, rather than the source of the content. NDN enables name-based routing and location-independent data retrieval, which gives NDN the ability to support the highly dynamic nature of mobile networks. Among other important features, NDN integrates security mechanisms and prioritizes protecting content over communication channels through cryptographic signatures. However, the data verification process that NDN employs may cause significant delays, especially in mobile networks and vehicular networks. This aspect makes it unsuitable for time-critical and sensitive applications such as the sharing of safety messages. Therefore, in this work, we propose NDN-BDA, a blockchain-based decentralized mechanism that provides a faster and more efficient data authenticity mechanism for NDN-based vehicular networks. [ABSTRACT FROM AUTHOR]

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The Wireless Sensor Network (WSN) is a network of Sensor Nodes (SN) which adopt radio signals for communication amongst themselves. There is an increase in the prominence of WSN adaptability to emerging applications like the Internet of Things (IoT) and Cyber-Physical Systems (CPS). Data security, detection of faults, management of energy, collection and distribution of data, network protocol, network coverage, mobility of nodes, and network heterogeneity are some of the issues confronted by WSNs. There is not much published information on issues related to node mobility and management of energy at the time of aggregation of data. Towards the goal of boosting the mobility-based WSNs' network performance and energy, data aggregation protocols such as the presently-used Mobility Low-Energy Adaptive Clustering Hierarchy (LEACH-M) and Energy Efficient Heterogeneous Clustered (EEHC) scheme have been examined in this work. A novel Artificial Bee Colony (ABC) algorithm is proposed in this work for effective election of CHs and multipath routing in WSNs so as to enable effective data transfer to the Base Station (BS) with least energy utilization. There is avoidance of the local optima problem at the time of solution space search in this proposed technique. Experimentations have been conducted on a large WSN network that has issues with mobility of nodes. [ABSTRACT FROM AUTHOR]

Information-Centric Networking (ICN) essentially supports multipath transmission. However, current multipath schemes in ICN either necessitate major network infrastructure updates or necessitate specific network settings for terminal devices. To solve these problems, we propose MPTS-ICN, a multipath transmission system for ICN that realizes end-to-end multipath transmission. Taking the ICN architecture based on the standalone name resolution approach as a basis, MPTS-ICN is easier to implement and deploy than other ICN multipath schemes. Moreover, we have extended the original network layer protocol to support multipath data transmission in ICN. To set up concurrent transmission multipath efficiently, we propose a heuristic algorithm for the selection of multipath service nodes. Extensive experimental comparisons with existing data transmission methods show that in bandwidth-constrained scenarios, MPTS-ICN outperforms the best-route method by 83.6% and the ECMP method by 79.7% in average flow completion time. [ABSTRACT FROM AUTHOR]

Currently, the internet of things (IoT) is a technology entering various areas of society, such as transportation, agriculture, homes, smart buildings, power grids, etc. The internet of things has a wide variety of devices connected to the network, which can saturate the central links to cloud computing servers. IoT applications that are sensitive to response time are affected by the distance that data is sent to be processed for actions and results. This work aims to create a prototype application focused on emergency vehicles through a fog computing infrastructure. This technology makes it possible to reduce response times and send only the necessary data to cloud computing. The emergency vehicle contains a wireless device that sends periodic alert messages, known as an in-vehicle beacon. Beacon messages can be used to enable green traffic lights toward the destination. The prototype contains fog computing nodes interconnected as close to the vehicle as using the low-power whole area network protocol called a long-range wide area network. In the same way, fog computing nodes run a graphical user interface (GUI) application to manage the nodes. In addition, a comparison is made between fog computing and cloud computing, considering the response time of these technologies. [ABSTRACT FROM AUTHOR]

The most significant increase of current task is in the desire for operational flexibility and agility in large-scale underwater network application scenarios in recent years. In order to address the challenging problems in Underwater Wireless Sensor Networks (UWSNs), we propose a large-scale UWSN based on the cellular network architecture called Underwater Cellular (uw-Cellular) network. It is designed especially for application scenarios where a large number of both fixed and mobile network nodes exist in a wide area to monitor the underwater environment. We also design protocols in each network layer in order to ensure reasonable channel sharing, data forwarding path selection and data reliability. The purpose of the simulation study we implement is to evaluate the performance of the CLA routing strategy compared to the VBF and the MFLOOD protocols in the uw-Cellular network. We also deploy a twenty-node uw-Cellular network in the real-world environment as the field case study. The experimental results showed that the Data Rate between any nodes could reach above 500 bps, and the network Average Throughput was no less than 550 bps under various load situations. [ABSTRACT FROM AUTHOR]

Underwater Internet-of-Things (UIoT) is an extension of Internet-of-Things technology in underwater. The underwater acoustic network with WiFi architecture (UW-WiFi), as a specific deployment of UIoT, has been proved to be a promising technique for wide-ranging marine applications. However, due to the unique features of underwater acoustic channel, such as long and variable propagation delay, low available bandwidth and high bit error rate, conventional medium access control (MAC) protocols designed for terrestrial WiFi networks need an overhaul to work efficiently for UW-WiFi networks. In consideration of the aforementioned channel features, different demands of nodes to occupy channel resources and the reliability of data transmission, a time sequence-based dynamic on-demand assignment (SDDA) MAC protocol for UW-WiFi networks is proposed in this paper. In SDDA, the collision-free scheduling is integrated with the reservation mechanism, aiming to address the issue of various access requirements of diverse task nodes on channel resources in the UW-WiFi network system. The designed protocol employs propagation delays and the amount of data to be sent by terminal nodes to achieve non-conflict transmissions of control packets and on-demand scheduling of data packets. Additionally, the scheme does not require extra overhead for time synchronization. Comparison simulations demonstrate that SDDA provides considerable benefits in terms of channel utilization, end-to-end delay and packet delivery ratio. At last, the SDDA protocol is implemented and a UW-WiFi network system is set up in the marine environment. The ocean field experiment results agree well with the simulated ones and also verify that the proposed protocol achieve conflict-free on-demand scheduling, fairness among terminal nodes at different ranges and the practicability in actual environments. [ABSTRACT FROM AUTHOR]

Recently, vehicular ad hoc networks (VANETs) finds applicability in different domains such as security, rescue operations, intelligent transportation systems (ITS), etc. VANET has unique features like high mobility, limited mobility patterns, adequate topologymodifications, and wireless communication. Despite the benefits of VANET, scalability is a challenging issue which could be addressed by the use of cluster-based routing techniques. It enables the vehicles to perform intercluster communication via chosen CHs and optimal routes. The main drawback of VANET network is the network unsteadiness that results in minimum lifetime. In order to avoid reduced network lifetime in VANET, this paper presents an enhanced metaheuristics based clustering with multihop routing technique for lifetime maximization (EMCMHR-LM) in VANET. The presented EMCMHR-LM model involves the procedure of arranging clusters, cluster head (CH) selection, and route selection appropriate for VANETs. The presentedEMCMHR-LMmodel uses slime mold optimization based clustering (SMO-C) technique to group the vehicles into clusters. Besides, an enhanced wild horse optimization based multihop routing (EWHO-MHR) protocol by the optimization of network parameters. The presented EMCMHR-LMmodel is simulated usingNetwork Simulator (NS3) tool and the simulation outcomes reported the enhanced performance of the proposed EMCMHR-LM technique over the other models. [ABSTRACT FROM AUTHOR]

Low-power wide-area (LPWA) technologies have gained popularity in accordance with the explosive growth of the Internet of Things (IoT). Among others, LoRa is considered as the leading standard that can meet the needs of modern wireless networking, mainly offering energy efficiency and broad coverage as well as a massive amount of device support. In addition to the ALOHA protocol, which is the default channel access mechanism used by the standard, a number of alternatives have been proposed in the literature in an effort to ameliorate the overall network performance. Furthermore, with moving nodes gaining ground more and more in the IoT realm and the research being at a relatively premature stage, it is imperative to create innovative algorithms that support highly dense networks with fast moving nodes. Motivated by these reasons, this work proposes a novel medium access protocol that takes advantage of the increased capabilities of modern wake up radio (WuR) technology in order to achieve low latency and mitigate the risk of lost packets in IoT networks with moving nodes based on the LoRa technology. A number of simulation scenarios have been devised and the findings suggest that the proposed protocol achieves the set goals and improves existing solutions. [ABSTRACT FROM AUTHOR]

The congestion problem can occur in a cooperative network because of the non-responsiveness of intermediate nodes or heavy traffic. Existing DSR cannot optimize the communication route in a such high congestion situation. In this paper, a new CPEDSR protocol is presented for handling energy and congestion-critical situations in the mobile network. The main objective of the proposed protocol is to identify the suspected attacked and congested nodes and perform communication over safe and reliable nodes.In this improved protocol, a congestion ratio-based probabilistic measure is employed for computing the congestion-resistance (CR) for each node. The weight is evaluated based on connectivity count (CC), residual energy (RE), average participation (AP), and average failure (AF) ratios. After computing the individual parameter, the overall CR is estimated to label the congestion-safe nodes. The weight rules are implied on CR for deciding the participation eligibility of the node. With each communication session, a more effective and accurate decision for node participation is taken. It is an experience adaptive protocol that acquires some weightage of the previous status for making decisions about the current node. This participation degree of neighbor nodes is processed by the DSR protocol to identify the next effective hop. The simulation is performed in congested and DDOS-infected networks. The comparative analysis is done against the existing and improved reactive protocols. The proposed protocol is validated on four network scenarios with a varied number of nodes and in attacked, non-attacked, and heavy traffic situations. The proposed CPEDSR protocol is validated against DSR, AODV, SAODV, PSAODV, PDS-AODV, and RSKNSN protocols. The average loss rate of AODV, DSR, SAODV, PSAODV, PDS-AODV, RSKNSN, and the proposed CPEDSR protocols for all scenarios is 15.07, 18.99, 10.62, 7.09, 8.30, 9.27, and 6.08%. The average number of dead nodes for all scenarios is 20.75 for AODV, 22.75 for DSR, 19.75 for SAODV, 18.5 for PSAODV, 18.25 for PDS-AODV, 16.75 for RSKNSN, and 14 for CPEDSR. It shows that the proposed protocol improved the network life and reduced communication loss during transmission. [ABSTRACT FROM AUTHOR]

This paper proposes a MAC protocol for ad hoc networks using In-band Full-duplex (IBFD) wireless communications, which are named as AdHoc-FDMAC. To utilize IBFD communications in ad hoc networks, this protocol modifies a number of control frames in the IEEE 802.11 Distributed Coordination Function (DCF) MAC standard. Here, the detailed time sequences for all types of IBFD communications are shown for the data transmission and routing. In this paper, the probability and throughput equations for IBFD communications in different situations have been derived. The performance of the proposed AdHoc-FDMAC has been analysed in terms of probability, throughput, and routing time. The Maximum throughput of AdHoc-FDMAC has been found to be 48.34 Mbps, and it is compared with a recently published ad hoc MAC as well as with the conventional HD MAC. The AdHoc-FDMAC outperforms the recently published ad hoc MAC and conventional HD MAC by 16.80% and 66.50% throughput gain, respectively. AdHoc-FDMAC incorporates the existing Ad hoc On-demand Distance Vector (AODV) routing protocol, but this AODV routing is utilized here using IBFD communications. This paper also compares the routing time of the IBFD-based AODV with the conventional AODV. The result shows that the IBFD-based AODV requires 33.33% less routing time than that of the conventional AODV for 3-hop distance between the transmitter and receiver. This paper suggests that the AdHoc-FDMAC protocol provides much more throughput in ad hoc networks by utilizing IBFD communications. [ABSTRACT FROM AUTHOR]

It is well known that the Sixth Generation (6G) communication system integrating multiple access networks promotes the internet of everything world-widely. However, due to the differentiated underlying network protocols, it is difficult to find a general authentication solution to support various authentication methods in different access networks. Blockchain is a new technology that supports network heterogeneity, which provides a potential solution for differentiated authentication. In this paper, we propose a blockchain-based differentiated authentication mechanism for 6G Heterogeneous Networks (HetNets), which can efficiently authenticate user identities through scheduling different authentication methods. Particularly, we analyze the authentication architecture of 6G HetNets and put forward a blockchain-based differentiated authentication framework. Besides, to improve the scalability of user authentication, it is the first time to use various blockchain authentication contracts to represent different authentication methods. Meanwhile, a differentiated authentication management contract is proposed to uniformly manage different authentication contracts to realize differentiated identity authentication. Based on the evaluation of the prototype system, the proposed mechanism can dynamically provide differentiated authentication services (e.g. EAP-MD5, 5G-AKA) with low additional time (milliseconds levels) cost. [ABSTRACT FROM AUTHOR]