Search Results (62)

The rapid expansion of Internet-of-Things (IoT) applications necessitates a thorough understanding of network configurations to address unique challenges across various use cases. This paper presents an in-depth analysis of three IoT network topologies: linear chain, structured tree, and dynamic transition networks, each designed to meet the specific requirements of industrial automation, home automation, and environmental monitoring. Key performance metrics, including round-trip time (RTT), server processing time (SPT), and power consumption, are evaluated through both simulation and hardware experiments. Additionally, this study introduces an enhanced UDP protocol featuring an acknowledgment mechanism and a power consumption evaluation, aiming to improve data transmission reliability over the standard UDP protocol. Packet loss is specifically measured in hardware experiments to compare the performance of standard and enhanced UDP protocols. The findings show that the enhanced UDP significantly reduces packet loss compared to the standard UDP, enhancing data delivery reliability across dynamic and structured networks, though it comes at the cost of slightly higher power consumption due to additional processing. For network topology performance, the linear chain topology provides stable processing but higher RTT, making it suitable for applications such as tunnel monitoring; the structured tree topology offers low energy consumption and fast communication, ideal for home automation; and the dynamic transition network, suited for industrial Automated Guided Vehicles (AGVs), encounters challenges with adaptive routing. These insights guide the optimization of communication protocols and network configurations for more efficient and reliable IoT deployments. Full article

The wide-ranging applications of the Internet of Things (IoT) show that it has the potential to revolutionise industry, improve daily life, and overcome global challenges. This study aims to evaluate the performance scalability of mature industrial wireless sensor networks (IWSNs). A new classification approach for IoT in the industrial sector is proposed based on multiple factors and we introduce the integration of 6LoWPAN (IPv6 over low-power wireless personal area networks), message queuing telemetry transport for sensor networks (MQTT-SN), and ContikiMAC protocols for sensor nodes in an industrial IoT system to improve energy-efficient connectivity. The Contiki COOJA WSN simulator was applied to model and simulate the performance of the protocols in two static and moving scenarios and evaluate the proposed novelty detection system (NDS) for network intrusions in order to identify certain events in real time for realistic dataset analysis. The simulation results show that our method is an essential measure in determining the number of transmissions required to achieve a certain reliability target in an IWSNs. Despite the growing demand for low-power operation, deterministic communication, and end-to-end reliability, our methodology of an innovative sensor design using selective surface activation induced by laser (SSAIL) technology was developed and deployed in the FTMC premises to demonstrate its long-term functionality and reliability. The proposed framework was experimentally validated and tested through simulations to demonstrate the applicability and suitability of the proposed approach. The energy efficiency in the optimised WSN was increased by 50%, battery life was extended by 350%, duplicated packets were reduced by 80%, data collisions were reduced by 80%, and it was shown that the proposed methodology and tools could be used effectively in the development of telemetry node networks in new industrial projects in order to detect events and breaches in IoT networks accurately. The energy consumption of the developed sensor nodes was measured. Overall, this study performed a comprehensive assessment of the challenges of industrial processes, such as the reliability and stability of telemetry channels, the energy efficiency of autonomous nodes, and the minimisation of duplicate information transmission in IWSNs. Full article

Key aspects of communities of the Internet of Things (IoT) smart objects presenting social aspects are represented by trust and reputation relationships between the objects. Several trustworthiness models have been presented in the literature in the context of multi-smart object community that could be adopted in the IoT scenario; however, most of these approaches represent the different dimensions of trust using scalar measures, then integrating these measures in a global trustworthiness value. In this paper, we discuss the limitation of this approach in the IoT context, highlighting the necessity of modeling complex trust relationships that cannot be captured by a vector-based model, and we propose a new trust model in which the trust perceived by an object with respect to another object is modeled by a directed, weighted graph whose vertices are trust dimensions and whose arcs represent relationships between trust dimensions. By using this new model, we provide the IoT community with the possibility of representing also situations in which an object does not know a trust dimension, e.g., reliability, but it is able to derive it from another one, e.g., honesty. The introduced model can represent any trust structure of the type illustrated above, in which several trust dimensions are mutually dependent. Full article

The burgeoning complexity and heterogeneity of IoT networks, coupled with their rapid growth, constant evolution, and new players, present significant challenges in terms of connectivity, interoperability, management, and usability. These networks, composed of a diverse array of devices, technologies and the like, demand innovative solutions to bridge the gaps between different IoT technologies and communication protocols. This article presents a simple, yet efficacious communication Relay to address one of these critical gaps. This Relay uses NB-IoT to ease the integration of 6LoWPAN-based IoT devices (IPv6) into the public legacy Internet (IPv4). This device translates 6LoWPAN, IPv6 CoAP messages into Internet-standard REST requests, so that appropriate handling of devices’ data be achieved in several stages. Thus, the Relay establishes two branches of communications: (i) the local network where the 6LoWPAN gateway is placed, and (ii) the public NB-IoT network. User interaction and data analysis are achieved by virtue of Home Assistant, where former 6LoWPAN devices are now discovered and shown as proper Home Assistant entities thanks to the Relay’s ease of integration into the open-source platform. This novel approach not only ensures efficient data and network management, but it also meets the urgent necessity for advanced solutions in enhancing actual IoT interconnectivity and monitoring. The unprecedented pace at which IoT devices, players and different networks have been proliferating in recent times is not compatible with countless manufacturer-dependent platforms, applications, and proprietary protocols that the IoT field has been leading with so far, almost from its beginnings. Full article

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%. Full article

The rapid proliferation of Internet of Things (IoT) devices has raised significant concerns regarding the trustworthiness of IoT devices, which is becoming a crucial aspect of our daily lives. In this paper, we deal with this important aspect by taking into account Meshtastic, a dynamic mesh networking protocol that offers robustness and adaptability, important characteristics for the dynamic and heterogeneous IoT environment. LoRaWAN (Low-Range Wide Area Network), a low-power, long-range wireless communication standard, introduces energy efficiency and extends the reach of IoT networks, enabling secure communication over extended distances. To improve the trustworthiness of IoT devices, we present an integrated approach that leverages the strengths of Meshstastic’s dynamic mesh networking capabilities and LoRa’s low-power, long-range communication, along with the integration of a reputation model specifically designed for IoT. We evaluated the performance of the proposed solution through several simulations and real-world experiments. The results show that the devices’ measured values of trust reflect the real behaviour of the devices. These findings underscore the viability and applicability of the Meshtastic protocol utilising LoRa technology as a pivotal step towards establishing resilient and trustworthy IoT infrastructures in the face of evolving security challenges. Full article

The Internet of Things (IoT) facilitates the integration of diverse devices, leading to the formation of networks such as Low-power Wireless Personal Area Networks (LoWPANs). These networks have inherent constraints that make header and payload compression an attractive solution to optimise communication. In this work, we evaluate the performance of Generic Header Compression (6LoWPAN-GHC), defined in RFC 7400, for IEEE 802.15.4-based networks running the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). Through simulation and real-device experiments, we study the impact of 6LoWPAN-GHC on energy consumption and delays and investigate for which scenarios 6LoWPAN-GHC is beneficial. We show that all RPL control packets are compressible by 6LoWPAN-GHC, which reduces their transmission delay and as such their vulnerability to interference. However, for the devices under study transmitting at 250 kbit/s, the energy gain obtained from sending a compressed packet is outweighed by the energy needed to compress it. The use of 6LoWPAN-GHC causes an energy increase of between 2% and 26%, depending on the RPL packet type. When the range is more important than the bandwidth and a sub-GHz band is used at 10 kbit/s, an energy gain of 11% to 29% can be obtained, depending on the type of RPL control packet. Full article

Indoor agriculture is emerging as a promising approach for increasing the efficiency and sustainability of agri-food production processes. It is currently evolving from a small-scale horticultural practice to a large-scale industry as a response to the increasing demand. This led to the appearance of plant factories where agri-food production is automated and continuous and the plant environment is fully controlled. While plant factories improve the productivity and sustainability of the process, they suffer from high energy consumption and the difficulty of providing the ideal environment for plants. As a small step to address these limitations, in this article we propose to use internet of things (IoT) technologies and automatic control algorithms to construct an energy-efficient remote control architecture for grow lights monitoring in indoor farming. The proposed architecture consists of using a master–slave device configuration in which the slave devices are used to control the local light conditions in growth chambers while the master device is used to monitor the plant factory through wireless communication with the slave devices. The devices all together make a 6LoWPAN network in which the RPL protocol is used to manage data transfer. This allows for the precise and centralized control of the growth conditions and the real-time monitoring of plants. The proposed control architecture can be associated with a decision support system to improve yields and quality at low costs. The developed method is evaluated in emulation software (Contiki-NG v4.7),its scalability to the case of large-scale production facilities is tested, and the obtained results are presented and discussed. The proposed approach is promising in dealing with control, cost, and scalability issues and can contribute to making smart indoor agriculture more effective and sustainable. Full article

The Internet of Things (IoT) has the potential to revolutionize agriculture by providing real-time data on crop and livestock conditions. This study aims to evaluate the performance scalability of wireless sensor networks (WSNs) in agriculture, specifically in two scenarios: monitoring olive tree farms and stables for horse training. The study proposes a new classification approach of IoT in agriculture based on several factors and introduces performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The study utilizes COOJA, a realistic WSN simulator, to model and simulate the performance of the 6LowPAN and Routing protocol for low-power and lossy networks (RPL) in the two farming scenarios. The simulation settings for both fixed and mobile nodes are shared, with the main difference being node mobility. The study characterizes different aspects of the performance requirements in the two farming scenarios by comparing the average power consumption, radio duty cycle, and sensor network graph connectivity degrees. A new approach is proposed to model and simulate moving animals within the COOJA simulator, adopting the random waypoint model (RWP) to represent horse movements. The results show the advantages of using the RPL protocol for routing in mobile and fixed sensor networks, which supports dynamic topologies and improves the overall network performance. The proposed framework is experimentally validated and tested through simulation, demonstrating the suitability of the proposed framework for both fixed and mobile scenarios, providing efficient communication performance and low latency. The results have several practical implications for precision agriculture by providing an efficient monitoring and management solution for agricultural and livestock farms. Overall, this study provides a comprehensive evaluation of the performance scalability of WSNs in the agriculture sector, offering a new classification approach and performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The results demonstrate the suitability of the proposed framework for precision agriculture, providing efficient communication performance and low latency. Full article

The Internet of Things (IoT) has become increasingly popular, and opened new possibilities for applications in various domains. However, the IoT also poses security challenges due to the limited resources of the devices and its dynamic network topology. Routing attacks on 6LoWPAN-based IoT devices can be particularly challenging to detect because of its unique characteristics of the network. In recent years, several techniques have been proposed for detecting routing attacks, including anomaly detection. These techniques leverage different features of network traffic to identify and classify routing attacks. This paper focuses on routing attacks that target the Routing Protocol for Low-Power and Lossy Networks (RPL), which are widely used in 6LoWPAN-based IoT systems. The attacks discussed in this paper can be categorized as either inherited from Wireless Sensor Networks or exploiting vulnerabilities unique to RPL (known as RPL-specific attacks). The paper describes various RPL attacks, including Flood Attacks, Data-DoS/DDoS Attacks, Wormhole Attacks, RPL Rank Attacks, Blackhole Attacks, Version Attacks, and Sinkhole Attacks. In this paper, a novel Hybrid Intrusion Detection System (HIDS) that combines a decision tree classifier and a one-class Support Vector Machine classifier is proposed to detect routing attacks. The HIDS draws on the strengths of both a Signature Intrusion Detection System (SIDS) and an Anomaly-based Intrusion Detection System (AIDS) to identify routing attacks with a high degree of accuracy and a low false alarm rate. The routing dataset, which features genuine IoT network traffic and various kinds of routing attacks, was used to test the proposed HIDS. According to the findings, the hybrid IDS proposed in this study outperforms SIDS and AIDS approaches, with higher detection rates and lower false positive rates. Full article

Coronavirus disease 2019 (COVID-19) has caused severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across the globe, impacting effective diagnosis and treatment for any chronic illnesses and long-term health implications. In this worldwide crisis, the pandemic shows its daily extension (i.e., active cases) and genome variants (i.e., Alpha) within the virus class and diversifies the association with treatment outcomes and drug resistance. As a consequence, healthcare-related data including instances of sore throat, fever, fatigue, cough, and shortness of breath are given due consideration to assess the conditional state of patients. To gain unique insights, wearable sensors can be implanted in a patient’s body that periodically generates an analysis report of the vital organs to a medical center. However, it is still challenging to analyze risks and predict their related countermeasures. Therefore, this paper presents an intelligent Edge-IoT framework (IE-IoT) to detect potential threats (i.e., behavioral and environmental) in the early stage of the disease. The prime objective of this framework is to apply a new pre-trained deep learning model enabled by self-supervised transfer learning to build an ensemble-based hybrid learning model and to offer an effective analysis of prediction accuracy. To construct proper clinical symptoms, treatment, and diagnosis, an effective analysis such as STL observes the impact of the learning models such as ANN, CNN, and RNN. The experimental analysis proves that the ANN model considers the most effective features and attains a better accuracy ($~98.3\%$) than other learning models. Also, the proposed IE-IoT can utilize the communication technologies of IoT such as BLE, Zigbee, and 6LoWPAN to examine the factor of power consumption. Above all, the real-time analysis reveals that the proposed IE-IoT with 6LoWPAN consumes less power and response time than the other state-of-the-art approaches to infer the suspected victims at an early stage of development of the disease. Full article

The Internet of things is a popular concept in the current digital revolution. Nowadays, devices worldwide can be connected to the Internet, enhancing their communication, capabilities, and intelligence. Low-Power Wireless Personal Area Network (6LoWPAN) was specifically designed to build wireless networks for IoT resource-constrained devices. However, 6LoWPAN is susceptible to several security attacks. The fragmentation mechanism, in particular, is vulnerable to various attacks due to the lack of fragment authentication and verification procedures in the adaptation layer. This article provides a survey of fragmentation attacks and available countermeasures. Furthermore, the buffer reservation attack, one of the most harmful fragmentation attacks that may cause DoS, is studied and simulated in detail. A countermeasure for this attack is also implemented based on a reputation-scoring scheme. Experiments showed the harmful effects of the buffer reservation attack and the effectiveness of the implemented reputation-scoring countermeasure. Full article

Today, the role of smart machines in our lives is valuable. With the advancement of digital technologies, such as the internet of things (IoT), many embedded systems have been developed for various applications. In homes, all daily activities and even security depend on machines. Therefore, implementing IoT-based smart homes has become a prominent research field. Also, since we are in the era of endless growth of the IoT and its applications, the topic of home automation systems is becoming more popular due to its countless advantages. In general, most home automation systems focus on one function: the ability to control home appliances remotely. In the world of information technology, the creation of rules and standards should always be done in the early stages of development because, after the work is done, incompatibilities between devices are created, which is a severe challenge and limits the use of technology. Therefore, the research on IoT technology has led to the formation of various protocols; this article gives an overview of seven essential protocols. Also, in this review article, energy consumption management, and privacy and security issues are discussed, and smart homes are introduced as critical requirements for the evolution of smart cities. Full article

The Internet of Things (IoT) has become one of the most attractive domains nowadays. It works by creating a special network between physical devices such as vehicles, home equipment, and other items. In recent days, the common technologies of communication such as Wi-Fi and 2G/3G/4G cellular networks are insufficient for IoT networks because they are designed to serve appliances with immense processing capabilities such as laptops and PCs. Moreover, most of these technologies are centralized and use an existing infrastructure. Currently, new communication technologies such as Z-Wave, 6LowPAN, and Thread are dedicated to the IoT and have been developed to meet its requirements. These technologies can handle many factors such as range, data requirements, security, power demands, and battery life. Nevertheless, the security issues in IoT systems have major concerns and issues because vulnerabilities in such systems may result in fatal catastrophes. In this paper, an enhanced IoT security framework for authentication and authorization is proposed and implemented to protect the IoT protocols from different types of attacks such as man-in-the-middle attacks, reply attacks, and brute force attacks. The proposed framework combines an enhanced token authentication that has identity verification capabilities and a new sender verification mechanism on the IoT device side based on time stamps, which in turn can mitigate the need for local identity verification methods in IoT devices. The proposed IoT security framework was tested using security analysis with different types of attacks compared with previous related frameworks. The analysis shows the high capability of the proposed framework to protect IoT networks against many types of attacks compared with the currently available security frameworks. Finally, the proposed framework was developed using Windows applications to simulate the framework phases, check its validity through the real network, and calculate the payload time added. Full article

Wireless Sensor Networks (WSNs) are the core of the Internet of Things (IoT) technology, as they will be used in various applications in the near future. The issue of security and power consumption is still one of the most important challenges facing this type of network. 6LoWPAN protocol was developed to meet these challenges in networks with limited power and resources. The 6LoWPAN uses a hierarchical topology and the traditional method of encryption and key management, keeping power consumption levels high. Therefore, in this paper, a technique has been developed that helps in balancing security and energy consumption by exploiting the Trust technique between low-cost WSN nodes called Trust-Cluster Head (Trust-CH). Trust between nodes is built by monitoring the behavior of packet transmission, the number of repetitions and the level of security. The Trust-CH model provides a dynamic multi-level encryption system that depends on the level of Trust between WSN nodes. It also proposes a dynamic clustering system based on the absolute-trust level in the mobile node environment to minimize power consumption. Along with a set of performance metrics (i.e., power consumption and network lifetime), the Cooja simulator was used to evaluate the Trust-CH model. The results were compared to a static symmetric encryption model together with various models from previous studies. It has been proven that the proposed model increases the network lifetime by 40% compared to previous studies, as well as saves as much as 28% power consumption in the case of using a static encryption model. While maintaining the proposed model’s resistance to many malicious attacks on the network. Full article