Wireless Nodes Research Articles

Energy Efficient Clustering Mechanism for Malicious Sensor Nodes in IOT Based MWSN

A mobile wireless sensor network (MWSN) is a collection of wireless nodes that may be set up anywhere and at any time without the need for a pre-existing network structure. Network performance is challenging factor due to nature of mobility and misbehaving nodes. Data loss and misbehaving in sensor nodes degrades performance of network. Some circumstances some malevolent sensor nodes predisposed to eradicate capability of network. The goal of this study is to use an irregular set approach to distinguish hostile nodes. Broadcasting information in route entry table identifies malicious node. Each sensor node in network preserves entry table and broadcast record regarding nearby nodes. To estimate broadcasting record metrics are premeditated as data deliverance proportion, throughput, delay, packet drop, fault rate. Mobile nodes with diverse velocity are simulated in NS2 environment which contains variable node clusters. Based broadcasting records of mobile nodes with diverse velocity are considered to create information table. Fine and malicious nodes are recognized based on rules derived in table of irregular set tactic. Shortest path without malicious node is elected to broadcast packets in the environment. Proposed tactic consequences reveal irregular set tactic amplifies network capability data deliverance percentage, throughput and dwindled end-to-end delay in mobile sensors.

Real-Time Implementation of a Cognitive Radio Node for Video Transmission with Dynamic Channel Selection

This paper endeavors to exploit the extent to which the radio spectrum can be utilized by almagating and enhancing various methods proposed by previous researchers in the field. Cognitive radio research addresses the challenge of spectrum scarcity and underutilization through cognitive radio technology. The realm of cognitive radio research encompasses diverse aspects of its architecture, ranging from spectrum sensing to higher-level strategies. Notably, the navigation strategy employed by cognitive radios constitutes a pivotal layer in these implementations. Thus, this paper focuses on the real-time implementation of a cognitive radio node in a spectrum of licensed users. Leveraging the capabilities of software-defined radios, GNU Radio, GStreamer and Ubuntu OS computers, this investigation introduces a streamlined channel strategy. This strategy uses both short-term and long-term historical data, along with a buffering mechanism, to facilitate the real-time transmission of a high-definition video signal. The successful implementation of this system yields a promising enhancement of approximately 32% in radio resource utilization. Furthermore, the sensing time of the cognitive radio experiences a significant reduction. This research contributes to the advancement of cognitive radio technology and demonstrates the consolidated strategies' practical implications, underscoring their potential to overcome spectrum-related challenges.

Performance Evaluation of MANETs routing protocols for transmitting video

Transmitting video over Mobile Ad hoc Networks (MANETs) is the most challenge because of the dynamic of its topology and the mobility of its nodes. These networks operate without a fixed physical infrastructure, allows wireless nodes to seamlessly connect or disconnect at any time. Additionally, the nodes in these networks are capable of self-organization. That makes routing process more difficult than traditional networks in addition to needing high bandwidth requirements to complete video transmitting process. This research investigates and assesses the performance of several commonly utilized standard routing protocols in MANETs, including AODV, DSDV, OLSR, and DSR. The evaluation is conducted across a range of wireless node quantities, spanning from 10 to 100, and tested on many performance metrics such as PDR, ETE delay, Packets Delay Variation (jitter), Data Dropped (DD), Throughput, and routing Overhead, the simulation results are analyzed to determine the most suitable routing protocols among them and overcome the video transmitting. Results shows that OLSR routing protocol is better from others tested protocols in almost performance metrics for video transmitting. Standard routing protocols have many resources constraints that may cause a link failure, when using it in multimedia applications it needs more power consumption and more bandwidth. The performance study simulated with ns3 simulator.

A Wi-Fi dynamic routing algorithm based on energy prediction for wildlife monitoring wireless network

The routing protocol of wildlife monitoring Wi-Fi (Wireless Fidelity) networks cannot balance node energy consumption, leading to early node death. Therefore, the research on energy balance in wildlife monitoring Wi-Fi networks is a hot topic. In order to balance the energy consumption of Wi-Fi networks and extend the lifespan of wireless networks, we designed the low energy dynamic routing protocol LEACH-EP (Low Energy Adaptive Clustering Hierarchy- Energy Prediction) based on energy prediction by analyzing the long-range dependent characteristics of the remaining energy time series (RETS) of wireless network nodes. This protocol uses the LSTM (Long Short-Term Memory) model to predict the remaining energy of network nodes, and then dynamically plans routes using future remaining energy. We conducted a networking experiment in the Anzihe Nature Reserve in Chengdu, China, and the Energy Balance Factor index of the wireless network significantly improved. The Mean Absolute Error value of network nodes is less than 60 mW, which is less than 10% of the average daily energy consumption of nodes. Half of the surviving network nodes have achieved an increase to 55.2%, and the network death time has been extended by 38.6%. The experimental results show that the energy prediction routing protocol LEACH-EP can significantly extend the node survival life and balance network energy consumption.

Bandwidth abstraction and service rate instantiation for latency-bounded reliability provisioning in 5th generation wireless networks

The provisioning of the statistical reliability regard to latency is crux for the bursty traffic in the 5th generation (5G) wireless network slicing. Based on martingale theory, a novel analysis framework of the latency-bounded reliability is proposed. For the queuing system with bursty traffic, a Queuing Length Martingale is constructed to reveal the impact of the entanglement between the arrival process and the service process on the latency performance, where these two stochastic processes are sharply heterogeneous. The complex martingale parameters are determined. Relying on the time shift feature of the Queuing Length Martingale, a Latency Martingale is defined, which enables to analyze the latency-bounded unreliability in the martingale domain. Leveraging the stopping time theory, a tight upper bound of the unreliability regard to latency is obtained. A bandwidth abstraction and service rate instantiation scheme is designed for wireless network slicing. Bandwidth abstraction facilitates to decouple the statistical reliability requirements as the desired bandwidth of the wireless node. In the 5G access network, a transmission power allocation problem is formulated with the constraint of abstracted bandwidth. According to the access states and channel characteristics, the demanded transmission power is captured dynamically to instantiate the service rates. Simulation results highlight the effectiveness of the bandwidth abstraction and service rate instantiation scheme.

WIRELESS SENSOR SYNCHRONIZATION METHOD FOR MONITORING SHORT-TERM EVENTS

Topicality. The key part of experimental research is obtaining the most accurate data about the studied object or event. Often, it is necessary to record parameters of processes that are c hallenging to precisely localize in space and time. The process or event under consideration can occur very rapidly, within fractions of a second, making it difficult for the researcher to deploy and configure recording equipment. This necessitates the creation of a network consisting of numerous recording devices to not miss critical events related to the studied process and obtain a sufficient volume of experimental data. Another issue is the synchronization of data obtained from different measurement devices. Spatially distributed recording devices must operate with a high degree of autonomy, leading to discrepancies in timekeeping and the need for synchronization. In processes with sub-millisecond durations, imperfections in timekeeping at each node have a significant impact: undetected and unaccounted discrepancies can lead to distortion or a misunderstanding of the overall picture of the studied process or event, even after acquiring all the necessary data. This is why the development and improvement of methods for synchronizing data recording nodes in distributed wireless sensor networks is important and urgent task. Task statement. One practical application of the proposed solution is the study of injuries caused by the penetration of foreign objects with high kinetic energy into the human body. These studies are conducted using artificial simulators of the human body made from composite materials and ballistic gelatin, with implanted electronic devices for recording changes in physical parameters. Results and conclusions. The article presents a hardware and software method, along with the technical implementation of the process for synchronizing the local clocks of wireless nodes, integrated into a unified information-measurement system located on the simulator. The proposed method allows achieving synchronization accuracy of no more than 12 μs/second using low-cost commercial off-the-shelf components. The practical part of the research discusses microprocessors from the ESP family, which, in general, provide sufficient time synchronization accuracy when using the proposed method, allowing for cost-effective node development within the system. The proposed method can also be applied in other fields, such as measuring vibrations in electrical machines and engines, as well as structural health monitoring.

Improved Security-Based Model for Heterogeneous Wireless Sensor Networks Using the Dispense Incline Drop Algorithm

Numerous real-time applications rely on heterogeneous wireless sensor networks (HWSNs), including the Internet of Vehicles (IoV), Internet of Sensors (IoS), medical applications, and so on. Due to the restricted computational capacity, memory, and connectivity of wireless nodes, it is essential to establish authentication techniques that consume less energy, yet guarantee strong security. It takes a lot of time and energy to construct trust models between sensor devices that can recognize and differentiate between benign and malicious attackers, which, in turn, reduces the detection rate and increases overhead. This article suggests a hybrid forewarn approach based on improved security to attain this degree of safety in HWSN communication called the Improved Security-based hybrid forewarn model (ISBHF) and the Dispense Incline Drop Algorithm. It is recommended to offer a trust score and evaluations for messages and knowledge transfer to improve detection capabilities against attackers targeting essential data transmission. To further minimize packet loss, a reliability secure measure is created, and a weighted averaging strategy is implemented to ensure the robustness and veracity of the secure scores. Furthermore, empirical evidence from measurements and simulations will demonstrate that unsecured paths of communication are key to identifying fraudulent nodes that are causing an outsized fraction of network traffic or data breaches. The suggested protocol is superior to the current approach in terms of efficiency and security, making it ideal for use in HWSN networks by decreasing communication overhead, increasing detection performance, and other parameters such as packet delivery ratio and connectivity ratio.

UAV Seismic Source Traveltime Tomography Technology in Steep Mountainous Areas

Active source seismic exploration is one of the most important high-resolution methods to obtain information about underground structures in tunnel engineering, and the seismic source is the key equipment to acquire high-quality data. In steep mountainous areas with complex geological structures, surface undulation, and drastic changes, the use of traditional seismic sources with high cost can seriously affect the efficiency and accuracy of detection. In this paper, a survey experiment of tunnel engineering is carried out in Lijiang, Yunnan Province, completing a fast, high-quality seismic data acquisition through utilizing the convenient, environmentally friendly, and economical UAV (Unmanned Aerial Vehicle) seismic source as the shot and wireless node instrument as the receiver. The experiment shows that the UAV seismic source can achieve low-cost and environmentally friendly excitation of seismic waves in complex mountainous areas, making a breakthrough in seismic source equipment. We obtain a high-precision velocity model by traveltime tomography, identifying the thickness of the overburden layer in the study area, and providing an important reference for tunnel engineering.

A Proficient Obtrusion Recognition Clustered Mechanism for Malicious Sensor Nodes in a Mobile Wireless Sensor Network

A collection of wireless nodes that may be installed at any location and at any time without requiring an established network structure is called a mobile wireless sensor network. The problem of network performance arises from the mobility of nodes and their misbehaviour. Network performance is negatively impacted by data loss and sensor node misbehaviour. In certain cases, there are malicious sensor nodes that are designed to destroy the network’s capacity. This work aims to identify hostile nodes using an irregular set technique. The route entry table’s broadcasting metadata helps identify rogue nodes. Every sensor node in the network broadcasts information about adjacent nodes and maintains a sentry table. Premeditated data delivery proportion, throughput, delay, packet drop, and fault rate are used to estimate broadcasting record parameters. In the NS2 environment, mobile nodes with varying velocities are simulated. To generate an information table, mobile nodes with varying speeds are examined based on their broadcasting records. On the basis of guidelines taken from the irregular set tactic table, good and bad nodes are distinguished. Packets are disseminated along the shortest path that doesn’t contain any malicious nodes. The results of the proposed technique show that an irregular set tactic increases throughput, network capability, data delivery percentage, and end-to-end delay reduction in mobile sensors.

Patterned Coating of Ionic Diode Arrays Toward Flexible Moist‐Electric Generators to Power Wireless Sensor Nodes

AbstractUbiquitous moisture is attractive for developing sustainable mobile power sources. However, how to endow moisture‐electric generators (MEGs) with fine design, mass customization, high power output, and foldability is still a largely unsolved problem. In this work, based on the Patterned Coating method, use is made of modulated carbon nanotube, nano‐Al2O3, and liquid metal inks to design and fabricate MEGs with properties required for their applications. A single MEG of the ionic diode type thus fabricated can generate an open‐circuit voltage (VOC) of 1.03 V and a short‐circuit current density (JSC) of 47.77 µA cm−2. Through large‐area integrated fabrication, an array containing 160 MEGs can generate a VOC of 154.1 V, and an array containing 100 MEGs can produce a short‐circuit current of 1.95 mA. In addition, the excellent wearability of MEG is verified by analyzing its electrical output performance after subjecting it to 800 cycles of bending deformations. The simple and cost‐saving fabrication technology issued from the work opens new perspectives for MEG applications and paves a path to their industrialization. For example, the customizable ionic diode arrays can meet the on‐demand power supply requirements of wireless sensor network nodes in the Internet of Things.

Performance of matrix completion approaches for aquaponics data

Technological innovations in Internet of Things (IoT) have resulted in smart agricultural solutions such as a remotely monitored Aquaponics system and a wireless sensor network (WSN) of such systems (nodes). IoT enables continuous sensing of temperature and pH data at each node of the WSN, which is periodically transmitted to a remote fusion centre. In this regard, the data matrices acquired at the fusion centre often suffer from data vacancies and missing data problems, owing to typical wireless multipath fading environment, sensor malfunctions and node failures. This paper explores the applicability of different matrix completion approaches for missing data reconstruction. Specifically, the performance of baseline predictor, correlation based approaches such as baseline predictor with temporal model, k-nearest neighbors (kNN) and low rank based approaches such as Sparsity Regularized Singular Value Decomposition (SRSVD) and Augmented Lagrangian Sparsity Regularized Matrix Factorization (ALSRMF) have been explored. Reliable temperature and pH data for 19 independent acquisition hours with 60 samples per hour are acquired at the fusion centre via Ultra High Frequency (UHF) transmission at 470 MHz and suitable pre-processing. Simulating different data integrity scenarios, the reconstruction error plots from each of these matrix completion approaches is extracted. A hybrid of kNN and baseline predictor with temporal model rendered a Mean Absolute Percentage Error (MAPE) of 1.75% for temperature and 0.86% for pH, at 0.5 data integrity. Further, with ALSRMF, which exploits the low rank constraint, the error reduced to 1.25% for temperature and 0.7% for pH, thus substantiating a promising approach for Aquaponics system data reconstruction.

A Neural Radiance Field-Based Architecture for Intelligent Multilayered View Synthesis

A mobile ad hoc network is made up of a number of wireless portable nodes that spontaneously come together en route for establish a transitory network with no need for any central management. A mobile ad hoc network (MANET) is made up of a sizable and reasonably dense community of mobile nodes that travel across any terrain and rely solely on wireless interfaces for communication, not on any well before centralized management. Furthermore, routing be supposed to offer a method for instantly delivering data across a network between any two nodes. Finding the best packet routing from across infrastructure is the major issue, though. The proposed protocol's major goal is to identify the least-expensive nominal capacity acquisition that assures the transportation of realistic transport that ensures its durability in the event of any node failure. This study suggests the Optimized Route Selection via Red Imported Fire Ants (RIFA) Strategy as a way to improve on-demand source routing systems. Predicting Route Failure and energy Utilization is used to pick the path during the routing phase. Proposed work assess the results of the comparisons based on performance parameters like as energy usage, packet delivery rate (PDR), and end-to-end (E2E) delay. The outcome demonstrates that the proposed strategy is preferable and increases network lifetime while lowering node energy consumption and typical E2E delay under the majority of network performance measures and factors.

An adaptive congestion and energy aware multipath routing scheme for mobile ad-hoc networks through stable link prediction

Advancement in mobile ad-hoc network (MANET's) has offered solutions to wide range of real-time applications. MANET's consist of group of battery operated wireless mobile nodes that forms a dynamic topology and functions autonomously without infrastructure. Mobile nodes are limited to resource, bandwidth, energy and memory. Due to mobile nature of the nodes, mobility and resource limitations are the two major factors that affect MANET's performance. Frequent topology changes and mobility affects the link stability between two nodes, frequent link interruption results in network congestion, lead to packet drop and increase retransmission delays. During multihop data transmissions, the wireless channel is shared among neighbour nodes. Determining the channel status and predicting the quality of link is still a challenging issue. Existing MANET's routing scheme considers optimal hop count as a metric for data transmission and selects the shortest path. Due to nodes movement, frequent link failure occurs, resulting in packet loss and retransmission of packet, which restablished path avoids packets loss, and alternate paths can be discovered within time such that congestion is controlled and delay is minimised. Therefore, it is required to design routing scheme for MANET's that can adapt to network changes and conditions to support quality of service (QoS). In this paper, we propose an Adaptive Congestion and Energy Aware Multipath Routing Scheme (ACEAMR) to provision QoS requirements in MANET's. ACEAMR discovers stable, energy aware, and congestion free paths towards destination. The congestion level at node is determined by computing queue utilization through adaptive feedback mechanism. ACEAMR integrates stable link prediction (SLP) to estimate the link quality and channel availability for reliable data transmission. Energy aware nodes are computed using fitness function of nodes having sufficient energy to extend network lifetime. Simulation results show that proposed ACEAMR achieves 30 % of higher throughput, 25 % more in packet delivery ratio, 27 % less delay and 28 % energy efficient compared to LLECP-AOMDV, OLEADM and AOMDV schemes.

Underwater Wireless Sensor Network-Based Delaunay Triangulation (UWSN-DT) Algorithm for Sonar Map Fusion

Abstract Robust and fast image recognition and matching is an important task in the underwater domain. The primary focus of this work is on extracting subsea features with sonar sensor for further Autonomous Underwater Vehicle navigation, such as the robotic localization and landmark mapping applications. With the assistance of high-resolution underwater features in the Side Scan Sonar (SSS) images, an efficient feature detector and descriptor, Speeded Up Robust Feature, is employed to seabed sonar image fusion task. In order to solve the nonlinear intensity difference problem in SSS images, the main novelty of this work is the proposed Underwater Wireless Sensor Network-based Delaunay Triangulation (UWSN-DT) algorithm for improving the performances of sonar map fusion accuracy with low computational complexity, in which the wireless nodes are considered as underwater feature points, since nodes could provide sufficiently useful information for the underwater map fusion, such as the location. In the simulated experiments, it shows that the presented UWSN-DT approach works efficiently and robustly, especially for the subsea environments where there are few distinguishable feature points.

Low-cost Wireless Lamp Socket and Power Plug for Smart Homes and Its Comparison with Available Commercial Competitors

Smart home manufacturers widely produce Wireless Lamp Socket and Power Plug devices, which offer various features ranging from basic on/off control to more complex functionalities such as monitoring energy consumption, power losses, and harmonics. However, these devices tend to be expensive, as indicated by market surveys. To address this issue, the current study aimed to develop low-cost wireless control nodes for smart homes that operate using relays. The two nodes consisted of lamp socket and power plug built with lowcost electronic components, including a Wi-Fi built-in Microcontroller ESP8266 (Wemos D1 mini model) as the backbone to create ESP-Mesh wireless network and to provide control ports for high/low logic, a relay module, an AC-to-DC converter module, and terminals (E27 screw for lamp socket node and C-type plug for the power plug node). This paper primarily focuses on the hardware aspects. In order to evaluate the effectiveness of the nodes, the following tests are conducted: (1) product demonstration to assess the product functions, (2) power measurement in idle and active conditions, (3) ESP-Mesh connection testing, and (4) RSSI measurement. Functional testing is done using a smartphone with the UPISmartHome version 2.0 Android application, which successfully controlled the nodes wirelessly. In idle conditions, power plug and lamp socket nodes consume 426.36 mWatt and 418.275 mWatt of power, respectively. Further, in active conditions, power plug and lamp socket nodes consume 435.704 mWatt and 440.583 mWatt of power, respectively. RSSI testing results show that both nodes can be controlled within an optimal range of 60 meters (with reference to RSSI below –85 dBm) without the Internet, utilizing the ESP-Mesh feature of ESP8266. This range is deemed reasonable for smart homes of 21, 36, or 45 square meters. Both nodes could be controlled under the ESP-Mesh network that gets build. We also present the comparison with other products of competitors in this paper.

Novel communication system for buried water pipe monitoring using acoustic signal propagation along the pipe

PurposeWireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.Design/methodology/approachAn acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.FindingsWith predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.Research limitations/implicationsAlthough an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.Originality/valueThis paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.

Maximal Weighted Coverage Deployment of UAV-Enabled Rechargeable Visual Sensor Networks

Due to the generation and transmission of video data, the high energy consumption rates of wireless nodes result in short lifetime of a visual sensor network, which has been commonly deployed in 3D space. In many applications, lots of targets need to be covered, but the budgets of both deployment and maintenance are limited. Therefore, how to maximize total weighted target coverage while prolonging network lifetime is of great significance. This work investigates the maximum weighted target coverage deployment of a rechargeable visual sensor network charged by an unmanned aerial vehicle (UAV) in 3D space, which should ensure network permanence and satisfy the budgets of both deployment and maintenance. In this problem, since UAV has a limited energy capacity, it is allowed to return to the depot for energy replenishment more than once in each charging period of wireless nodes so as to increase target coverage. After formulating this problem as a mixed integer nonlinear program, this work proposes a greedy heuristic and a particle swarm optimizer to approximately solve this NP-hard problem. Extensive simulation results reveal that the latter can deliver a better solution despite consuming more time than the former.

End to end delay distribution analysis and interference aware high throughput for Wireless Mesh Networks

The wireless mesh network is an innovative and efficient wireless communication approach with immense potential to transform future wireless networks. This cutting-edge wireless technology provides a wide range of wireless services for personal, local, campus, and metropolitan environments. The wireless mesh network consists of a cluster of mobile wireless nodes that can dynamically and instantaneously create random and temporary network topologies, forming a wireless ad-hoc network. Ad hoc wireless networks are particularly advantageous due to their cost-effectiveness and ease of deployment. In order to further optimize the performance of ad-hoc networks, different routing algorithms such as Ad-hoc On-Demand Distance Vector Routing (AODV), Dynamic Source Routing Algorithm (DSR) and Destination Sequenced Distance Vector (DSDV) have been thoroughly researched via simulation.

Wireless Node Localization Based on Wild Goats Algorithm for Industrial Internet of Things

Wireless Node Localization Based on Wild Goats Algorithm for Industrial Internet of Things

Managing Energy Consumption of Devices with Multiconnectivity by Deep Learning and Software-Defined Networking.

Multiconnectivity allows user equipment/devices to connect to multiple radio access technologies simultaneously, including 5G, 4G (LTE), and WiFi. It is a necessity in meeting the increasing demand for mobile network services for the 5G and beyond wireless networks, while ensuring that mobile operators can still reap the benefits of their present investments. Multipath TCP (MPTCP) has been introduced to allow uninterrupted reliable data transmission over multiconnectivity links. However, energy consumption is a significant issue for multihomed wireless devices since most of them are battery-powered. This paper employs software-defined networking (SDN) and deep neural networks (DNNs) to manage the energy consumption of devices with multiconnectivity running MPTCP. The proposed method involves two lightweight algorithms implemented on an SDN controller, using a real hardware testbed of dual-homed wireless nodes connected to WiFi and cellular networks. The first algorithm determines whether a node should connect to a specific network or both networks. The second algorithm improves the selection made by the first by using a DNN trained on different scenarios, such as various network sizes and MPTCP congestion control algorithms. The results of our extensive experimentation show that this approach effectively reduces energy consumption while providing better network throughput performance compared to using single-path TCP or MPTCP Cubic or BALIA for all nodes.