Wireless Sensor Network Research Research Articles

Retracted: Application Research of Wireless Sensor Network Based on Computer BIM Technology and ZigBee in Interior Art Design

Retracted: Application Research of Wireless Sensor Network Based on Computer BIM Technology and ZigBee in Interior Art Design

Autonomous configuration establishment method of wireless network on condition monitoring for coupling and decoupling of railway vehicles

AbstractIn recent years, with the development of IoT, research and development of wireless sensor networks for monitoring has been advanced to monitor the condition of various devices in railway vehicles and notify train crews. In the operation of railway vehicles, the composition may be changed at stations by coupling and decoupling, and it is necessary to set up inter‐vehicle wireless network considering them. Therefore, to transmit sensor data in railway vehicles, we propose an autonomous configuration establishment method of wireless network for railway vehicles considering coupling and decoupling.

Privacy-Preserving Distributed Iterative Localization for Wireless Sensor Networks

Effectively determining the accurate locations of sensor nodes while preserving data privacy is an interesting and challenging problem in the research of wireless sensor networks. On the basis of the well-performing distributed iterative localization framework in wireless sensor networks, this paper proposes a dual privacy-preserving scheme based on node-intermittent updates and noises injection. A comprehensive analysis of the localization algorithm in terms of convergence and privacy-preserving performance is presented. It is theoretically demonstrated that the localization algorithm can achieve global accurate localization without leaking the privacy information of sensor nodes. At last, the performance of the privacy-preserving localization algorithm is verified by building an experimental platform containing six robots.

Energy efficiency enhancement in wireless sensor network: ant colony optimization

<p><span>Wireless sensor networks (WSNs) have received significant scholarly attentionwithin the scientific community lately. The use of small and energy efficient devices with restricted computing capabilities has gained traction in various fields of application, including environmental monitoring, target tracing, and medical health observation. Node localization is a fundamental system parameter in numerous applications. Categorizing hybrid solutions as either range-based or range-free poses a challenge in general. In this article, we aim to simplify the classification process by examining range-based and range-free schemes. There are two distinct classifications of schemes, namely fully schemes and hybrid schemes. Furthermore, we conduct a comparative analysis of the predominant energy efficiency measures in WSN networks and deliberate on prospective avenues for research in WSNs deploying ant colony algorithm.</span></p>

A novel model for representing a plane target and finding the worst-case coverage in wireless sensor network based on Clifford algebra

Wireless ad hoc sensor networks have recently emerged as a premier research topic. They have great long-term economic potential and ability to transform our lives and pose many new system building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Most of researches in wireless sensor networks are focused in obtaining better target coverage in order to reduce energy and cost of the network. The problem of planar target analysis is one of the crucial problems that should be considered while studying coverage problem of sensor networks. By combining computational geometry and graph theoretic techniques, specifically the Voronoi diagram and graph search algorithms, this paper introduces a novel sensor network coverage model that deals with plane target problem based on Clifford algebra which is a powerful tool that is coordinate free. Also, the calculations of the node coverage rate for the plane target in the sensor network using Clifford algebra are presented. Then, the maximum clearance path (worst-case coverage) of the sensor network for a plane target is proposed. The optimality and reliability of the proposed algorithm have been proved using simulation. Also, a comparison between the breach weight of the point target and the plane target is provided.

Enhanced Pelican Optimization Algorithm for Cluster Head Selection in Heterogeneous Wireless Sensor Networks.

In the research of heterogeneous wireless sensor networks, clustering is one of the most commonly used energy-saving methods. However, existing clustering methods face challenges when applied to heterogeneous wireless sensor networks, such as energy balance, node heterogeneity, algorithm efficiency, and more. Among these challenges, a well-designed clustering approach can lead to extended node lifetimes. Efficient selection of cluster heads is crucial for achieving optimal clustering. In this paper, we propose an Enhanced Pelican Optimization Algorithm for Cluster Head Selection (EPOA-CHS) to address these issues and enhance cluster head selection for optimal clustering. This method combines the Levy flight process with the traditional POA algorithm, which not only improves the optimization level of the algorithm, but also ensures the selection of the optimal cluster head. The logistic-sine chaotic mapping method is used in the population initialization, and the appropriate cluster head is selected through the new fitness function. Finally, we utilized MATLAB to simulate 100 sensor nodes within a configured area of 100 × 100 m2. These nodes were categorized into four heterogeneous scenarios: m=0,α=0, m=0.1,α=2, m=0.2,α=3, and m=0.3,α=1.5. We conducted verification for four aspects: total residual energy, network survival time, number of surviving nodes, and network throughput, across all protocols. Extensive experimental research ultimately indicates that the EPOA-CHS method outperforms the SEP, DEEC, Z-SEP, and PSO-ECSM protocols in these aspects.

Improved 3D localization algorithm for large scale wireless sensor networks

AbstractAs localization represents the main core of various wireless sensor network applications, several localization algorithms have been suggested in wireless sensor network research. In this article, we put forward an iterative bounding box algorithm enhanced by a Kalman filter to refine the unknown node’s estimated position. In fact, several research efforts are currently in progress to extend the 2D positioning algorithm in WSNs to 3D that reflects reality and the most practical applications. Subsequently, we replace a large number of GPS-equipped anchors with a single mobile anchor. In our studies, we consider the type of range-free sensor network exploiting the wireless sensors connectivity. We assess the performance of our algorithm using exhaustive experiments on several isotropic and anisotropic topologies. Our proposed algorithm can fulfill the joint goals of algorithm transparency and accuracy for various scenarios by evaluating parameters such as localization accuracy whilst changing other simulation parameters such as the effect of communication range, mobile anchor node position and sensor node deployment topology. It has been proven by the results of the experiments that the proposed algorithm effectively reduces the location error without requiring more equipment or increasing the communication cost.

Energy and Distance Aware Multi-Objective Firebug Swarm Optimization Based Clustering and Routing in Wireless Sensor Networks

In recent years, Wireless Sensor Networks (WSNs) have received increased international attention due to advancements in the communication, electronics, and information fields. These sensor networks integrate a huge number of sensor nodes to track rapidly changing physical events. The key improvement is that these nodes can be easily positioned in any environment due to their small size. Therefore, maintaining network connectivity is crucial in WSNs. If some nodes become unavailable, the connectivity of the routing path fails, resulting in significant packet loss in the WSN. Therefore, many types of research in WSNs have focused on energy efficiency, where energy consumption is minimized to improve the network lifetime. Here, Energy and Distance-aware Multi-Objective Firebug Swarm Optimization (ED-MOFSO) is projected to achieve an energy efficient process. Furthermore, ED-MOFSO minimizes delays to enhance performance measures. From the overall simulation, it shows that ED-MOFSO achieves improved metrics, including residual energy (14.29 J), delay (11.1 ms), packet delivery ratio (0.994), routing overhead (0.10), and throughput (1.233 Mbps) when compared to conventional Elephant Herding Optimization (EHO) greedy and Ant Colony Optimization Integrated Glow-worm Swarm Optimization (ACI-GSO).

A review of routing algorithms for underwater wireless sensor networks

With the rise of the upsurge of exploiting marine resources and the rapid development of the research of terrestrial wireless sensor networks, the research of underwater wireless sensor networks (UWSNs,) has become a new research hotspot. In UWSNs, routing protocol plays a very important role as one of the important components. This paper introduces several classical routing algorithms from the following categories: location, sector, reinforcement learning, and intelligent optimization algorithms. Finally, the paper also summarizes and prospects the research direction of underwater wireless sensor network routing algorithms.

Enhancing Network Lifetime of WSNs through the Implementation of a Modified Ant Colony Optimization Algorithm

Energy efficient routing has been the mainstay of research in wireless sensor networks. With rising utility of WSNs in a broad range of applications, a significant volume of research contributions are targeted towards obtaining an energy efficient routing with a good quality of service (QoS) metric. In recent times, the utility of evolutionary algorithm for such multi-objective problems has been on the rising trend as evolutionary models closely mimic the real time scenario of any problem optimization. In this research work, a modified ant colony optimization (M-ACO) has been proposed and implemented for optimization in terms of energy conservation and thereby to extend the network lifetime of the network

Enhanced model for improving QOS in wireless sensor networks for healthcare monitoring application

Wireless Sensor Network (WSN) is made up of numerous sensor nodes that are dispersed at random and form themselves into a cooperative network. WSN fulfils the three basic tasks of communication, computation, and sensing. WSN research and analysis have grown into a significant exploratory field of healthcare monitoring, particularly because of the difficulties they can address. Current technologies on healthcare system focus on the wearable and implantable Wireless Body Area Networks (WBANs), which are a subclass of WSNs. A medical sensor implanted in or attached to the body using a wireless media forms the basis of a WBAN. This technology allows the collection of physical information about the human body. The WBAN network is made up of different node coordinators that gather data from the devices (e.g. Heartbeat sensor) and transmit it to the closest access point (AP) of the healthcare system. Maintaining the Quality of Service (QoS) parameters such as delay, throughput, energy consumption in the real or active environment caused by different activity of human motion are the main issues faced by body area networks. In this research, we combine Time Division Multiple Access (TDMA) with Carrier Sense Multiple Access (CSMA/CA)to propose a Combined Enhanced Multiplexing Algorithm (CEMA). With the implementation of this strategy, performance of the MAC protocol in congested networks can be enhanced. An improvement in the performance of the MAC protocol in WBAN was observed considering multi-channel transmission by integrating two algorithms.

DV-Hop-based localization algorithm using optimum anchor nodes subsets for wireless sensor network

Node localization has become a crucial technology in wireless sensor network (WSN) research field. Although the widely used DV-Hop localization algorithm is simple and easy to implement, its positioning accuracy still needs to be further enhanced. To improve the DV-Hop algorithm accuracy, a DV-Hop-based scheme using optimum anchor nodes subsets (OANS DV-Hop) is put forward in this article. For OANS DV-Hop algorithm, first of all, each anchor node localizes itself by using other anchor nodes, and employs binary particle swarm optimization (BPSO) algorithm to generate an optimum subset composed of other anchor nodes except itself. Then the anchor node applies OANS to recalculate its average hop size and broadcasts the new hop size and OANS to the nearest unknown nodes. The unknown node localizes itself by using OANS instead of all anchor nodes. Finally, a fitness function is designed based on OANS, and the continuous particle swarm optimization (PSO) algorithm is applied to further increase the localization accuracy. Simulation results demonstrate that OANS DV-Hop algorithm owns higher localization accuracy compared with the primal DV-Hop and other improved DV-Hop algorithms in various network environments.

A Dynamic Multi-Mobile Agent Itinerary Planning Approach in Wireless Sensor Networks via Intuitionistic Fuzzy Set.

In recent research developments, the application of mobile agents (MAs) has attracted extensive research in wireless sensor networks (WSNs) due to the unique benefits it offers, such as energy conservation, network bandwidth saving, and flexibility of open usage for various WSN applications. The majority of the proposed research ideas on dynamic itinerary planning agent-based algorithms are efficient when dealing with node failure as a result of energy depletion. However, they generate inefficient groups for MAs itineraries, which introduces a delay in broadcasting data return back to the sink node, and they do not consider the expanding size of the MAs during moving towards a sequence of related nodes. In order to rectify these research issues, we propose a new Graph-based Dynamic Multi-Mobile Agent Itinerary Planning approach (GDMIP). GDMIP works with “Directed Acyclic Graph” (DAG) techniques and distributes sensor nodes into various and efficient group-based shortest-identified routes, which cover all nodes in the network using intuitionistic fuzzy sets. MAs are restricted from moving in the predefined path and routes and are responsible for collecting data from the assigned groups. The experimental results of our proposed work show the effectiveness and expediency compared to the published approaches. Therefore, our proposed algorithm is more energy efficient and effective for task delay (time).

Augmentation in performance and security of WSNs for IoT applications using feature selection and classification techniques

Energy consumption, secure connection of Sensor Nodes (SNs), and their performance analysis play a major role in Wireless Sensor Networks (WSNs) research. Increased case use of various Internet of Things (IoT) applications has led to the development of complicated networks. To address the threats and security issues faced in complicated WSNs, a novel combined feature selection method known as the Fast Correlation-based Feature Selection (FCBFS) with XG-Boost has been proposed for the NSL-KDD intrusion detection benchmark dataset. It helps in the selection of the best features in a cluster-based WSN before the classification step. Five popular machine learning-based classifiers, namely decision tree, random forest, Naïve Bayes, extra tree, and XG-Boost, are used for the development of a robust intrusion detection system in WSN and its IoT applications. The effectiveness and robustness of the developed ensemble methods have been checked using classification accuracy, precision, recall, and F-score. XG-Boost classifier along with the FCBFS process has performed best with a classic accuracy, precision, recall, and F-score up to 99.84%, 99.83%, 99.84%, and 99.82% on multiple runs. Upon comparison with the existing state-of-the-art work in this field, the proposed work has outperformed. Results show that, in contrast to the previous filter approaches, our proposed process can successfully minimize the number of features while maintaining a high classification precision and recognition rate. It further tends to lower the overall energy required by sensor nodes during attack detection, hence extending the network lifetime and usefulness to a sufficient time frame.

Performance Analysis and Evaluation of a Multi-Hop Routing Protocol for Wireless Multimedia Sensor Networks

Researchers in wireless multimedia sensor networks (WMSNs) are constantly interested in designing and developing energy-efficient routing protocols. Numerous clustering routing protocols have been developed in recent years to overcome the limitation of consuming less energy and prolong the lifetime of sensor nodes in homogeneous and heterogeneous WMSNs. Existing approaches depend on single-hope communication, in which sensor nodes consume more energy and die faster. Inter-communication nodes can play an important role in reducing energy by transmitting data in a multi-hope fashion to the sink. An energy-efficient multi-path clustering with load balancing routing protocol for wireless multimedia sensor networks (EEMCL) is proposed in this study. In this protocol, the main cluster heads (MCHs) are preselected in each network cluster and filled with more energy than normal sensor nodes. The two secondary cluster heads (SCHs) with the highest energy nodes will be selected by the main cluster head algorithm. Moreover, inter-cluster multi-hop routing with the help of MCHs can enhance the network lifetime when the sink is located at the corner of the sensing field. The simulation results verify that the proposed multi-hop technique provides better performance than existing LEACH, LEACH-C, SEEN, and IEE-LEACH routing protocols in scenario 1 and when compared with CPMA in scenario 2. The last node dead (LND) for the proposed protocol is at round 5721, 2225 for LEACH, 2300 for LEACH-C, 2900 for SEEN, and 3160 for IEE−LEACH in scenario 1, while in scenario 2, the LND for the proposed protocol is at round 3820 and 435 for the CPMA routing protocol.

Integration of Wireless Sensor Networks in Environmental Monitoring Cyber Infrastructure

Abstract: Wireless sensor networks (WSNs) have great potential to revolutionize many science and engineering domains. We present a novel environmental monitoring system with a focus on overall system architecture for seamless integration of wired and wireless sensors for long-term, remote, and near-real-time monitoring. We also present a unified framework for sensor data collection, management, visualization, dissemination, and exchange, conforming to the new Sensor Web Enablement standard. Some initial field testing results are also presented. The monitoring system is being integrated into the Texas Environmental Observatory infrastructure for long-term operation. As part of the integrated system, a new WSN-based soil moisture monitoring system is developed and deployed to support hydrologic monitoring and modeling research. This work represents a significant contribution to the empirical study of the emerging WSN technology. We address many practical issues in real-world application scenarios that are often neglected in the existing WSN research

Application Research of Wireless Sensor Network Based on Computer BIM Technology and ZigBee in Interior Art Design

With the rapid development of computer technology and automation technology, modern interior art design has attracted more and more attention. This paper chooses BIM technology and ZigBee technology, which have the advantages of low cost, low power consumption, low complexity, etc., and can be used to establish the communication protocol of indoor art design and home wireless network, so as to achieve residential comfort and wireless data security transmission and convenient, real-time monitoring. This paper starts with many environmental parameters that are closely related to human comfort, such as temperature and humidity, light, and air cleanliness, and conducts an investigation on the comfort of intelligent houses and the appreciation of modern indoor art; this paper discusses the security of BIM and ZigBee and the algorithm of AES starting from the specific implementation process; according to the internal characteristics and password requirements of the family, a smart home safety net is constructed and encrypted, so as to ensure the safe transmission of family information; complete the modern artistic design of the home controller. The hardware and software were constructed, and a web server was constructed on Linux, which was invoked using the CGI interface, thereby connecting the web server to the terminal device that was comfortably controlled. The test proves that the control scheme can work normally in the laboratory network, which has great guiding significance for practical work.

Hybrid optimization for fault‐tolerant and accurate localization in mobility assisted underwater wireless sensor networks

SummaryMobility prediction and fault tolerance are extremely difficult due to underwater characteristics. Energy drain is one of the major causes for node faults. Hence, in this research article, a hybrid optimization algorithm is developed for fault‐tolerant and accurate localization in UWSN. In this technique, Artificial Butterfly Optimization (ABO) algorithm is applied for finding the distance between the anchors and the sensors. Each non‐localized node runs ABO algorithm for finding the distance amid the anchor or beacon nodes. Then, applying Quaternion‐based Backtracking Search Optimization (QBSA) algorithm, non‐localized sensor nodes are localized and to decrease the localization error based on the Received Signal Strength Indicator (RSSI), battery energy, and distance parameters. Aqua‐Sim a tool kit of NS2 is an open‐source software developed for Underwater Wireless Sensor Network research, and this proposed algorithm will be implemented using this software. By simulation results, it is shown that the proposed optimization algorithm reduces the localization error, latency, and cost and energy consumption.

Key Technologies of Real-Time Location Service in Satellite Navigation and Positioning Network Based on Internet of Things.

In this day and age, the necessities for route and situating exactness are getting ever more elevated. The global positioning and navigation system (GPS) can give high-accuracy and long haul route and situating data. But it largely depends on the external environment and is susceptible to environmental disturbances. As a result, the number of visible stars is insufficient, and even placement fails. The research on node positioning technology is of great significance to the research of wireless sensor networks, and node positioning technology is one of the important technologies in wireless sensor networks. Therefore, this paper will introduce the relevant algorithms and technologies of positioning in detail. The purpose of this text is to research how to analyze and research based on Internet of things (IoT) satellite navigation and positioning technology. And the wireless sensor network is described. The two simulation results have showed that, with the positioning technology proposed in this paper, the average positioning error of the anchor node can be kept a small constant regardless of the conditions of different packet sending intervals, changing moving rates, or increasing the transmission power and changing distance. The average positioning error provided in this paper has been kept at about 0.80 m, and the positioning accuracy is high, which is naturally newer and better than the Ssu positioning technology.

Three-dimensional localization algorithm of mobile nodes based on received signal strength indicator-angle of arrival and least-squares support-vector regression

Node localization is one of the key technologies in the wireless sensor network research field, which is crucial to the high-accuracy localization of mobile nodes, but the positioning error of traditional algorithms such as received signal strength indicator and angle of arrival is more than 4 m, which has almost no practical value. For example, the localization accuracy of the localization algorithm based on received signal strength indicator will be reduced sharply when affected by signal reflection, multipath propagation, and other interference factors. To solve the problem, a three-dimensional localization algorithm of mobile nodes was proposed in this article based on received signal strength indicator–angle of arrival and least-squares support-vector regression, which fused the ranging information of received signal strength indicator algorithm and the angle of arrival algorithm and optimized the estimated distance of unknown nodes. Next, the mobile node model and least-squares support-vector regression modeling mechanism were built according to the hop count of the shortest distance between nodes. Finally, the unknown mobile nodes were localized based on least-squares support-vector regression modeling. The experimental results showed that compared with the localization algorithms without optimized ranging information or least-squares support-vector regression modeling, the algorithm proposed in this study exhibited significantly improved stability, a reduced mean localization error by more than 50%, and increased localization accuracy.