Personal Area Networks Research Articles

Multi-Sensor Based healthcare monitoring system by LoWPAN-based architecture

The development of the Internet of Things (IoT) has recently revived interest in IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). For the enormous IP-based detection technologies in the future IoT, 6LoWPAN mobile compatibility is still in its infancy. A significant 6LoWPAN use of IoT, the hospital's wireless technology, which continuously monitors patients' vital signs, regardless of whether they are moving. To track accurate patient positions, communication between patient nodes and the hospital network needs to be maintained through sensor network. In addition, it must offer automatic switching and improve the power consumption of devices. In this research, a hospital structure based on 6LoWPAN with a Media Access Control (MAC) design for patient data was offered. Our preliminary numerical results indicate a decrease in the expenses associated with transfers on the mobile router, which generally represents a bottleneck in such a network. Biological ECG signals are routed via low pan before transmission via routing algorithms to the gateway network.

Design of slot loaded CPW feed ultra-wideband antenna with WLAN band notch characteristics

The fast development has been noticed during in the last few decades in the area of Ultra-wideband technologies. Throughout this manuscript, a novel ultra wideband (UWB) antenna with single band notched functions with CPW feed line is projected. The single band rejection is presented and analyzed at WLAN frequency. The proposed antenna was initially exhibits the voltage standing wave ratio (VSWR) bandwidth of 10.6 GHz with frequency range of 3.05 to 13.65 GHz. Further to achieve the WLAN band rejection at 5.5 GHz, an arc shaped slot has been presented in the geometry of radiating patch. The size of designed antenna is 27 × 27 mm2. It also shows that the VSWR ≤ 2 for the operating UWB frequency range, except stop band from 5.16 to 6.7 GHz for filtering the WLAN signal. A variety of UWB antenna applications can be found in medical and radar imaging as well as higher data rate Personal Area Networks (PANs). The designed antenna is simulated on the low cost FR4 glass epoxy substrate with dielectric constant 4.4 and thickness 1.6 mm. Performance parameters such as VSWR, radiation pattern and gain of proposed antenna are analyzed by using HFSS V13 simulator.

Energy‐efficient resource allocation model for device‐to‐device communication in 5G wireless personal area networks

SummaryIn general, there are several many devices that can overload the network and reduce performance. Devices can minimize interference and optimize bandwidth usage by using directional antennas and by avoiding overlapping communication ranges. In addition, devices need to carefully manage their use of resources, such as bandwidth and energy. Bandwidth is limited in wireless personal area networks (WPANs), so devices need to carefully select which data to send and receive. In this paper, an intelligent performance analysis of energy‐efficient resource optimization model has been proposed for device‐to‐device (D2D) communication in fifth‐generation (5G) WPAN. The proposed energy‐efficient resource allocation in D2D communication is important because it helps reduce energy consumption and extend the lifespan of devices that are communicating with each other. By allocating resources in an efficient manner, communication between two devices can be optimized for maximum efficiency. This helps reduce the amount of energy needed to power the communication, as well as the amount of energy needed to power the device that is communicating with another device. Additionally, efficient resource allocation helps reduce the overall cost of communication, as the use of fewer resources results in a lower overall cost. The proposed efficient resource allocation helps reduce the environmental impact of communication, as less energy is used for communication. The proposed energy‐efficient resource allocation model (EERAM) has reached 92.97% of energy allocation, 88.72% of power allocation, 87.79% of bandwidth allocation, 87.93% of spectrum allocation, 88.43% of channel allocation, 25.47% of end‐to‐end delay, 94.33% of network data speed, and 90.99% of network throughput.

6LoWPAN MAC layer parameters optimization using evolutionary algorithm based ANN topology in wireless body area networks

Since the IPv6 Wireless Personal Area Network (6LoWPAN) can be utilized for information dissemination, this network gains significant attention in recent years. Proxy mobile IPv6 (PMIPv6) is standard for mobility control based on network at entire IP wireless applications. But, group-based body area networks cannot respond effectively. A new improved group flexibility system decrease the number of control messages contain router requests as well as advertising messages when compared to the group-based PMIPv6 protocol, in order to minimize delay and signaling costs. The IEEE 802.15.4 standard for low-power personal area networks (6LoWPAN) complies through IPv6-compliant MAC and physical layers. If the default parameters, excessive collisions, packet loss, and great latency occur arbitrarily in high traffic by default MAC parameters while using a great number of 6LoWPAN nodes. The implemented Whale optimization algorithm is based on artificial neural network optimization, genetic algorithm or particle swarm optimization to choose and authenticate MAC parameters. This manuscript proposes a novel intelligent method for choosing optimally configured MAC 6LoWPAN layer set parameters. Results of simulations based on the metrics such as Average delay time (ADT), Average signaling cost, Delivery ratio, Energy consumption, Latency, Network Life time (Nlt), Packet Overhead (PO), Packet loss. The performance of the proposed method provides 19.08%, 25.87%, 31.98%, 26.98%, 31.98%, 26.98% and 23.89% lower Latency, 12.67%, 25.98%, 31.98%, 26.98%, 27.98%, 31.97% and 27.85% lower Packet Overhead and 19.78%, 27.96%, 37.98%, 18.09%, 28.97%, 27.98% and 56.04% higher Delivery ratio compared with the existing methods such as 6LoWPAN-NUM-OHCA-FFA, 6LoWPAN-GTCCF-PSO, 6LoWPAN- DODAG-ACO, 6LoWPAN- MAC-GA-PSO, 6LoWPAN-NCG-DTC-NGIPSA and 6LoWPAN-TDMA-GTS-SHJA algorithms respectively.

Blackhole attacks in internet of things networks: a review

The internet of things (IoT) is one of data revolution area and is the following extraordinary mechanical jump after the internet. In terms of IoT, it is expected that electronic gadgets that are used on a regular basis would be connected to the current of the internet. IPv6 over low-power wireless personal area networks (6LoWPAN) is a one of IPv6 header pressure technology, and accordingly, it is vulnerable to attack. The IoT is a combination of devices with restricted resource assets like memory, battery power, and computational capability. To solve this, RPL or routing protocol for low power Lossy network is deploy by utilizing a distance vector scheme. One of denial of service (Dos) attack to RPL network is blackhole attack in which the assailant endeavors to become a parent by drawing in a critical volume of traffic to it and drop all packets. In this paper, we discuss research on numerous attacks and current protection methods, focusing on the blackhole attack. There is also discussion of challenge, open research issues and future perspectives in RPL security. Furthermore, research on blackhole attacks and specific detection technique proposed in the literature is also been presented.

Water Utility Conservation and Management Approach Using IoT

Abstract: The demand for water supply has increased unpredictably worldwide over the past few decades, posing a major challenge. To overcome this challenge, an IoT-based water monitoring and control approach is presented, which supports realtime internet-based data collection. The device comprises a computer system (central hub), an IoT module, a switching unit, and a Zigbee module. The Internet of Things is a network of devices embedded with electronics, software, and sensors that enable them to exchange and analyze data. The centralized hub distributes water individually based on the needs of each household, assisted by IoT integration of communications, control, and information processing across the systems used. This allows water quantity and quality to be sensed at each structure in a particular sector, providing remote access control of the water supply. The centralized hub monitors and shares water among localized tanks or resupplies water from its reservoir according to a rank’s deficit or excess water level. Personal area networks are created in this scenario where a wireless connection is required across the system. UV treatment is deployed to improve the quality of water distributed to every household, and fluoride content level along with hardness checking is done using respective test meters. Overall, the IoT-based water monitoring and control approach design presents an innovative solution to the increasing demand for water supply, enabling efficient distribution and ensuring water quality.

End-to-end communication protocol in IoT-enabled ZigBee network: Investigation and performance analysis

ZigBee is the prominent technology on the Internet of Things that enables smart applications and services. However, this technology forms personal area networks, which will not directly communicate with internet end users. The IoT-enabled Zigbee devices cannot handle the IPv6 packets, which have a maximum packet size of 1280 bytes, and the transmission of IPv6 packets over ZigBee-based IEEE 802.15.4 networks, which will be performed using a gateway. via the ZigBee coordinator. The gateways and the ZigBee coordinator must complete the neighbor discovery process, which increases the coordinator’s complexity. Additional ZigBee devices suffer from header size problems, routing structures, and data forwarding issues. This paper presents an efficient end-to-end communication protocol for IoT-enabled ZigBee devices and with an Internet host using the 6LoWPAN protocol. This 6LoWPAN connects IP-based infrastructures with a collection of Zigbee devices that provide end-to-end communication to route the IPv6 packets into ZigBee-enabled IoT networks. Next, we proposed the RPL-AODV routing protocol, which refers to the capacity to forward or route the data packets from one Zigbee device to the 6LoWPAN Boarder Router (6BR) via several hops. This proposed routing protocol combines the advantages of RPL and AODV routing protocols in ZigBee devices of IoT networks that establish the path from the origin node to the target node on an on-demand basis. Finally, we evaluated the performance of this protocol with various metrics and found improved results compared to existing protocols.

Smart Load-Based Resource Optimization Model to Enhance the Performance of Device-to-Device Communication in 5G-WPAN

In wireless personal area networks (WPANs), devices can communicate with each other without relying on a central router or access point. They can improve performance and efficiency by allowing devices to share resources directly; however, managing resource allocation and optimizing communication between devices can be challenging. This paper proposes an intelligent load-based resource optimization model to enhance the performance of device-to-device communication in 5G-WPAN. Intelligent load-based resource optimization in device-to-device communication is a strategy used to maximize the efficiency and effectiveness of resource usage in device-to-device (D2D) communications. This optimization strategy is based on optimizing the network’s resource load by managing resource utilization and ensuring that the network is not overloaded. It is achieved by monitoring the current load on the network and then adjusting the usage of resources, such as bandwidth and power, to optimize the overall performance. This type of optimization is essential in D2D communication since it can help reduce costs and improve the system’s performance. The proposed model has achieved 86.00% network efficiency, 93.74% throughput, 91.94% reduced latency, and 92.85% scalability.

A novel scheme to improve lifetime and real-time support for IEEE 802.15.4 based wireless personal area networks

IEEE 802.15.4 defines the working of physical and media access layers of a Low-Rate Wireless Personal Area Network (LR-WPAN). A LR-WPAN is a low cost, low power, and low data-rate network that offers reasonable lifetime and reliable data transfer within a limited range. However, it faces several challenges whilst dealing with applications that are having strict timeliness, energy, and bandwidth requirements. This paper proposes an efficient superframe structure for the MAC layer of IEEE 802.15.4 networks that intends to deal with these challenges by varying the functionalities of Guaranteed Time Slot (GTS) bits. Simulations of different GTS allocation techniques show that our enhanced scheme outperforms the original standard as well as previous techniques in terms of energy consumption, average delay, maximum GTS allocation and reliability.

Internet of things-based indoor smart hydroponics farm monitoring system

Internet of things (IoT)-enabled systems are being used to monitor, control, and optimize agricultural systems like hydroponics. Optimization of these systems requires monitoring of various growth factors for plants which will also require multiple sensors. With the number of wireless sensors needed to track the conditions of the hydroponics system, the wireless sensor network will also grow in size and complexity. In this paper, a hybrid IoT-based monitoring system, with both wired and wireless components, with a target indoor farm application is proposed. The system was implemented using controller area network for the wired component, IPv6 over low power wireless personal area network (6LoWPAN) for the wireless component, and Amazon Web Services for the cloud services. Network simulations were performed to compare the network performance of the proposed hybrid system and the purely wireless system. The simulations show that incorporating a wired system results in improvements such as the reduction of packet loss from 12.23% in the purely wireless system to 5.62% in the hybrid system with burst traffic and even down to 0.0% in the hybrid system with continuous traffic.

A monopole broadband circularly polarized antenna with coupled disc and folded microstrip stub lines

A broadband circularly polarized (CP) printed monopole antenna which fed by coplanar waveguide (CPW) is proposed in the paper. The structure of the novel antenna includes a quarter circular disc radiating monopole, a coupled circular patch, and a bent L-shaped microstrip stub line. The L-shaped microstrip stub line is used to widen the impedance bandwidth and generate a horizontal component of the electromagnetic wave. The adoption of the asymmetric ground coplanar waveguide structure with the single-feed technology and the coupled circular patch, simultaneously achieve wide impedance bandwidth and wide axial ratio (AR) bandwidth. The structure parameters and the surface current of the designed antenna are analysed. The simulation and the measurement are conducted, showing good characterizations of the designed antenna. The 10-dB impedance bandwidth is 7.57 GHz, the fractional bandwidth from 6.05 to 13.62 GHz is 76.9%, the 3-dB axial ratio bandwidth is 3.01 GHz, and the fractional bandwidth from 6.05 to 9.06 GHz is 39.8%. The antenna can generate right/left hand circularly polarized waves in the direction of ± z axis. The designed antenna has wide applications in the fields of Internet of Things (IoT), broadband dual-CP communication systems and polarization diversity systems, wireless personal area network and other advanced communication systems.

Design of 60 GHz millimeter‐wave SIW antenna for 5G WLAN/WPAN applications

AbstractBroadband millimeter Wave (mmWave) transmission at the 60 GHz band is a great prospect to meet the demanding high data rate requirements of future wireless personal area network (WPAN) and wireless local area network (WLAN) 5G networks. This paper proposes a single layer H‐plane sectoral horn mmWave antenna at 60 GHz using substrate integrated waveguide (SIW) technology for the future high‐speed short range WPAN and WLAN networks. The benefits of the proposed antenna are high gain, low cost, small size, and ease of integration with other planar circuits. The proposed SIW horn is constructed with RT/duroid 5880 substrate, which has a relative permittivity and loss tangent with a thickness of 0.508 mm. The novelty of this work is; a wider bandwidth is achieved by adding striplines at the horn aperture to match the antenna with air and to increase the antenna operating bandwidth. In addition, the antenna gain is improved by adding a dielectric lens with the striplines at the radiating end. During these steps, the antenna parameters are tuned and optimized to achieve the best results as compared to related previous studies. The proposed antenna's performance is analyzed in terms of gain, return loss (S11) and radiation pattern at a frequency of 60 GHz. Simulation results are carried out by using industry standard software, Computer Simulation Technology (CST) microwave studio. The designed antenna achieves a peak gain of 13 dB and impedance bandwidth when , 8.6 GHz (13.688%) for the reflection coefficient of . The results show that the proposed antenna achieves stable tunable 60 GHz frequency performance, which makes it feasible to deploy in WLAN/WPAN operating in mmWave bands.

Design and Implementation of a 6LoWPAN-Based Lightweight Wireless Embedded Internet Platform for IoT Applications

<p>The Internet of Things (IoT) plays an important role in the revolution of the Internet with the rise of Industry 4.0. It is closely related to low-power embedded devices, which have not been entirely IP-enabled until now. The 6LoWPAN (acronym of IPv6 over low-power wireless personal area networks) is an IPv6 protocol for Wireless Embedded Internet. It can help enable even the minimum embedded systems with limited processing capabilities to participate in the IoT. This study investigates a reliable way of future IoT networking by designing and implementing a 6LoWPAN-based lightweight Wireless Embedded Internet platform, named Lowvy (abbreviated from low-power wireless connectivity). Lowvy is characterized by low power consumption, constrained memory, small size, a low-cost IPv6-enabled wireless embedded device, and a constrained application protocol (CoAP). We did different application experiments to test the performance of the platform in terms of received signal strength indicator (RSSI), power consumption, sensor integration, and internet integration application with 6LoWPAN. Comparing Lowvy with other wireless embedded IoT platforms, Lowvy is less expensive and more compact. Moreover, Lowvy has a powerful performance in terms of signal strength for a longer wireless distance transmission of about 25 to 30 meters and has a lower power consumption of 41.60 milliwatts.</p> <p> </p>

QSec-RPL: Detection of version number attacks in RPL based mobile IoT using Q-Learning

Internet of Things (IoT) has revolutionized the networking by connecting the real world entities to the Internet. IoT connects the communication devices and has an incredible impact on perspective analytics on the massive volume of data produced every day. An attacker may exploit vulnerabilities of IoT entities and compromise users’ security and privacy. Development of solutions to address security and privacy issues of IoT is in premature stage and considered as challenge. This challenge becomes more critical when the devices in the network are resource-constrained in terms of energy, processing and memory. The IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN) has emerged in recent years as an adaptation layer to carry IPv6 packets over IEEE 802.15.4. Many IoT applications use Routing Protocol for Low Power and Lossy Networks (RPL) as a network layer protocol developed for routing in 6LoWPAN. Security is challenging in resource constrained environment where encryption may not be a viable solution. Version number attack is one of the most common network layer attacks against RPL based 6LoWPAN. The RPL specification does not address the integrity of the version number and therefore leaves version number mechanism as a weak point in terms of security. This paper investigates the impact of version number attack in RPL networks while considering mobility of the sensor nodes. We propose a solution that utilizes Q-Learning strategy to detect the malicious nodes that are performing version number attack. The proposed approach detects malicious nodes with reasonable accuracy while imposing significantly less overhead on the nodes of low power and lossy networks. There are other approaches too like Message Authentication Codes (MAC) based on symmetric keys but these techniques have memory and communication overhead. So we propose different approach Q-Learning to detect the attacker nodes.

L‐RUBI: An efficient load‐based resource utilization algorithm for bi‐partite scatternet in wireless personal area networks

SummaryRecently, 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.

Accurate Phase Detection for ZigBee Using Artificial Neural Network

The IEEE802.15.4 standard has been widely used in modern industry due to its several benefits for stability, scalability, and enhancement of wireless mesh networking. This standard uses a physical layer of binary phase-shift keying (BPSK) modulation and can be operated with two frequency bands, 868 and 915 MHz. The frequency noise could interfere with the BPSK signal, which causes distortion to the signal before its arrival at receiver. Therefore, filtering the BPSK signal from noise is essential to ensure carrying the signal from the sender to the receiver with less error. Therefore, removing signal noise in the BPSK signal is necessary to mitigate its negative sequences and increase its capability in industrial wireless sensor networks. Moreover, researchers have reported a positive impact of utilizing the Kalmen filter in detecting the modulated signal at the receiver side in different communication systems, including ZigBee. Meanwhile, artificial neural network (ANN) and machine learning (ML) models outperformed results for predicting signals for detection and classification purposes. This paper develops a neural network predictive detection method to enhance the performance of BPSK modulation. First, a simulation-based model is used to generate the modulated signal of BPSK in the IEEE802.15.4 wireless personal area network (WPAN) standard. Then, Gaussian noise was injected into the BPSK simulation model. To reduce the noise of BPSK phase signals, a recurrent neural networks (RNN) model is implemented and integrated at the receiver side to estimate the BPSK’s phase signal. We evaluated our predictive-detection RNN model using mean square error (MSE), correlation coefficient, recall, and F1-score metrics. The result shows that our predictive-detection method is superior to the existing model due to the low MSE and correlation coefficient (R-value) metric for different signal-to-noise (SNR) values. In addition, our RNN-based model scored 98.71% and 96.34% based on recall and F1-score, respectively.

A Low‐Power WLAN CMOS LNA for Wireless Sensor Network Wake‐Up Receiver Applications

Wireless communication integration is related to many challenges such as reliability, quality of service, communication range, and energy consumption. As the overall performance of wireless sensor networks (WSN) will be improved if the capacity of each sensor node is optimized, several techniques are used to fine‐tune the various circuits of each node. In recent works, the wake‐up receiver nodes have been introduced to minimize latencies without increasing energy consumption. To overcome the sensitivity of wake‐up receiver limitations, a design of a low‐noise amplifier (LNA) with several design specifications is required. This article discusses the relevance of the wake‐up receiver in WSN applications and provides a brief study of this component. An LNA design for WSN wake‐up receiver applications is presented. The challenging task of the LNA design is to provide equitable trade‐off performances such as noise figure, gain, power consumption, impedance matching, and linearity. The LNA circuit is designed for wireless personal area network (WLAN) standards utilizing RF‐TSMC CMOS 0.18 μm. Two innovative techniques are applied to the LNA topology to improve its performance: forward body biasing is used to reduce power consumption by 11.43 mW, and substrate resistance is added to reduce noise by 1.8 dB. The developed LNA achieves a noise figure of 1.6 dB and a power gain of 21.7 dB at 5.2 GHz. At 0.6 V, the designed LNA dissipates 0.87 mW.

Energy aware Load Balanced Clustering using Golden Eagle Optimization in MS based LR-WPAN

Escalation in the real world applications using Internet of Things (IoT) now demands low cost and minimum power consuming devices having sensing, communicating, and computing capabilities. Low-rate Wireless Personal Area Network (LR-WPAN) is an emerging solution which can provide these capabilities with low data rate and less complexity. The longevity and connectivity of the network is a critical issue during the data collection in LR-WPAN. An Energy aware Load Balanced Clustering (ELBC) approach is proposed in this paper that enhances the network life time by minimizing the energy consumption. Clustering is done using the Golden Eagle Optimization (GEO) and by taking connectivity, Average energy of cluster, balancing factor and cohesion as parameters for optimal cluster head selection. Mobile Sink based data collection strategy using Gravitational Search Algorithm (GSA) is used to collect data from clusters. The simulation is done in network simulator-3 and the result shows that, the performance of ELBC-GEO is better in terms of network lifetime, average energy of nodes, and data collection delay.

Localization for V2X communication with noisy distance measurement

Mobile sensor network localization is a growing research topic after IEEE 802.15.4 specified the procedure of low-rate wireless personal area networks (LR-WPANs), which further helps localize vehicles in the automobile industry. This paper presents a new localization scheme based on flying anchors deployed in vehicular infrastructure. The mobile anchor nodes follow a random C-shaped trajectory. A global positioning system (GPS) is attached to each anchor node, transmitting beacons with ID and location to all other vehicles in a network. Distance calculation is facilitated through link quality induction, employing the centroid method to compute localization error. Mobile anchor localization, particularly when employing a C-shaped trajectory commonly adopted by various topologies, consistently yields optimal positioning outcomes. However, this approach can be susceptible to the impact of noisy measurements, potentially reducing overall localization performance. To overcome this problem, we proposed a framework based on extended Kalman filtering (EKF), which is used to refine the coordinates of the vehicles. To compute the lower bounding of the vehicular node, an analytical framework is also proposed to enhance the localization error accuracy. Simulation results show that the EKF framework provides better positioning accuracy compared to the existing C-shaped solution, irrespective of noise statistics, topology selection, and anchor node density. With the help of the Extended Kalman Filter (EKF) framework, we achieved a comprehensive localization error of 0.99 m, accompanied by a standard deviation of 0.47.

Fragmentation Attacks and Countermeasures on 6LoWPAN Internet of Things Networks: Survey and Simulation

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.