Structure Of Wireless Sensor Networks Research Articles

Smart Agriculture Application Using Secured and Energy-Efficient IoT-Based WSN Framework

The use of wireless sensor networks (WSNs), in several sectors, including communication, agriculture, manufacturing, smart health, monitoring and surveillance is increasing in R&D. An IoT-based WSN in agricultural production has been effective in detecting yield conditions and automating agriculture precision by using multiple sensors. To collect data on crops, plants, temperature estimates and stickiness as well as to boost yields by making smart agriculture decisions, they are deployed in rural regions. Sensors, on the other hand, are constrained by their inability to handle, store, communicate, and process large amounts of data due to a lack of available resources. Additionally, the safety and security of the IoT-based agricultural sensors against damaging competitors are crucial factors, as is their efficacy. One idea put up in this article is to employ a WSN structure based on the Internet of Things (IoT) for smart agriculture. The selection of group leaders is also based on data collected by rural sensors and multi-rules choice capacity. A transmission link’s SNR (signal-to-noise ratio) is used to gauge the intensity of signals being sent over it in order to guarantee accurate and timely data transfer. In addition, the direct congruential generator is repeated in order to enable data flow from agricultural sensors to central stations (BS). Compared with previous arrangements, smart agriculture obtained an average of 13.5 percent in the organisation throughput, 38.5 percent in the parcel drop percentage, 13.5 percent in the organisation inactivity, and 16 percent in energy usage. Comparatively speaking, this is a huge step forward.

Research on the Integration of Wireless Sensor Networks Based on IoT Technology

Wireless Sensor Network (WSN) is a wireless network formed by a group of sensors with wireless transceiver capabilities, connected in a multi-hop autonomous manner. It has several advantages: low traffic, greater stability, longer wireless communication, and higher coverage areas at a lower cost. The incorporation of new NB-IoT technologies in wireless sensor networks, combining the advantages of both and the establishment of NB-IoT-based wireless sensor networks, has a very promising application in defense and military, medical, intelligent transportation, and commercial applications. This study first investigates both WSN and NB-IoT technologies separately and then combines them to investigate the networking structure of NB-IoT and WSN as well as the related technologies based on the fusion. Then the coverage method of the traditional network node redeployment of wireless sensors is described, and many problems such as poor node connectivity and low coverage are caused by the traditional method due to the lack of local search of subgroup nodes. The initialization of the nodes is carried out. The global information exchange is combined with the subgroup to determine the detectable area of the wireless sensor, and the calculus method is used for the irregular area to obtain the optimal network node so that the nodes of the wireless sensor network can be redeployed.

English

This paper proposes a solution to enhance the key management of Wireless Sensor Networks (WSNs) by integrating blockchain technology with Hierarchical Identity-Based Encryption. The aim is to establish a highly secure WSN structure. The current wireless network is improved by incorporating blockchain technology to increase security and reliability. However, the security of key management in dynamic WSNs is threatened by the vulnerability of untrusted Head Nodes(HN) to attack. The presence of an untrusted HN imposes a heavy burden on the sensors for key management, in addition to the already existing challenges. In order to overcome these issues, blockchain technology has been used to propose a secure key management scheme (BSKM). We offer a secure node movement technique and a safe cluster-building mechanism, with the blockchain acting as a trust machine to replace the major functions of the Head node. We run extensive simulations for security analyses. The findings show that the BSKM scheme is efficient and effective and is more suitable for enhancing the reliability of dynamic WSNs.

A novel approach based on bio‐inspired efficient clustering algorithm for large‐scale heterogeneous wireless sensor networks

SummaryIn large‐scale heterogeneous wireless sensor networks (WSNs), clustering is particularly significant for lowering sensor nodes (SNs) energy consumption and creating algorithm more energy efficient. The selection of cluster heads (CHs) is a crucial task in the clustering method. In this paper, optimised K‐means clustering algorithm and optimised K‐means based modified intelligent CH selection based on BFOA for large‐scale network (lar‐OK‐MICHB) is hybridised for CH selection process. Here, we utilised the extended capabilities of OK‐MICHB algorithm for large‐scale network. Furthermore, in many applications where energy is a primary constraint, such as military surveillance and natural disaster prediction, the stability region is also a significant factor, with a longer network lifespan being a primary requirement. In the proposed approach, only the CH selection is made after every round in place of cluster and CH change as done in conventional hierarchical algorithm. The simulation results reveal that, while keeping the distributive structure of WSNs, suggested lar‐OKMIDEEC can locate real greater leftover energy nodes for selection of CH without utilising randomise or estimated procedures. Furthermore, as compared with the multi‐level MIDEEC protocol, this offers a larger stability region with 68.96% increment, more consistent selection of CH in every round, and greater packets (i.e., in numbers) received at the base station (BS) with a longer network lifetime with 327% increment.

Signal enhancement of vehicle wireless sensor network based on adaptive filter

A signal enhancement method of vehicle wireless sensor network (WSN) based on adaptive filter is designed in this paper. By analyzing the vehicle WSN structure and node deployment mode, the signal operation process of WSN in the vehicle is determined, the relationship between Received Signal Strength Indication (RSSI) and distance is analyzed, and the signal of vehicle WSN is acquired. In order to reduce the workload of signal enhancement, set the signal strength judgment conditions of vehicle WSN, among the collected signals, the signal with poor intensity is taken as the research object. On this basis, the adaptive filter is used to remove the signal noise of vehicle WSN and enhance the signal strength. The signal enhanced by the proposed method has less noise and good stability.

МОДЕЛЮВАННЯ ТА УДОСКОНАЛЕННЯ СЕНСОРНОЇ МЕРЕЖІ СИСТЕМИ ОБЛІКУ СПОЖИВАННЯ ЕНЕРГЕТИЧНИХ РЕСУРСІВ У МІКРОРАЙОНІ

The research is aimed at the development of new algorithms for the selection of a main node and methods of placement of sensor nodes for the effective construction of wireless sensor networks (WSNs), therefore it is relevant.The analysis of the literature made it possible to establish that many scientists were engaged in the research of methods of building smart energy systems for a smart city management. However, the researchers did not analyze the potential and real threat of data transmission from energy consumption control sensors.The purpose of the research is to improve the accuracy of control and accounting of energy resources consumed by residents for the neighborhood using wireless sensor networks.The article analyzes the state of the art in the field of research on wireless sensor networks (WSNs), determines the most important characteristics and structure of WSNs in the organization of the automated system of control and accounting of energy resources (ASCOE). An analysis of the existing algorithms for routing, self-organization and selection of ta main node of the cluster in wireless sensor networks of sensors for controlling the consumption of energy parameters by the consumer was carried out. The duration of the network's life cycle, the period of stability and the bandwidth of the BSM was evaluated based on the ratio between the radius of coverage and the radius of the communication range.Studies have shown that the applied algorithm for selecting the main node of the cluster based on fuzzy logic using Voronoi diagrams significantly increases the life cycle of the sensor network compared to the LEACH and Fuzzy C-Means algorithms

Research on Optimization of 3D Location Algorithm Based on Non-ranging Wireless Sensor Network

In order to solve the problem of node location in 3D space WSN (Wireless sensor network), this article summarizes the structure and characteristics of WSN, then uses weighted centroid algorithm to estimate the location, designs a new non-ranging 3D node location algorithm for wireless sensor network, and gives the theoretical basis and implementation steps of this algorithm design. The algorithm does not need to measure the actual distance between nodes, but only needs the anchor nodes to broadcast their own beacon information, and the unknown nodes within the one-hop communication range of the anchor nodes receive and store the monitored beacon information, and estimate their own positions according to these information. The final simulation results show that, compared with the existing 3D localization algorithm based on non-ranging, there is no need for unknown nodes to communicate with each other, which has less communication overhead and does not depend on the proportion of anchor nodes. And it is robust to the network topology. As a non-ranging positioning algorithm, its positioning error is only about 15% in the set 3D space.

Cooperative Networking Strategy of UAV Cluster for Large-Scale WSNs

To solve the shortcomings of wireless sensor networks (WSNs) in data collection in a wide range, long distance, and other complex environments, such as high networking cost, short network life cycle, and difficult data collection, a data collection strategy based on the unmanned aerial vehicle (UAV) cluster collaborative networking is proposed. First, the node structure and deployment application of WSNs are analyzed, and the architecture of UAV collaborative data collection is designed. Second, the related models of communication energy consumption between WSNs’ network and UAV cluster, UAV cluster task allocation, and path planning are established successively. Then, a simple but efficient task planning strategy considering UAV forward and return distances is proposed. Finally, for the problem of model solving, the solution strategy of the heuristic swarm intelligence algorithm is proposed. The simulation results verify that the strategy reduces the overall network energy consumption by 42.16% and the total range of UAV by 9.7% and realizes the relative minimization of WSNs energy consumption and UAV flight cost on the premise of ensuring the full coverage of WSNs’ nodes.

The method of intelligent wireless sensor to improve the water permeability of permeable asphalt concrete pavement

AbstractThis research aims to study the intelligent wireless sensor to improve the water permeability of permeable asphalt concrete pavement. The water permeability of pavement is extremely important for the traffic environment. This study first briefly introduces the background and significance analysis, and then exemplifies the deployment algorithm and model of wireless sensors on asphalt pavement. For example, the wireless sensor deployment strategy along the asphalt pavement based on linear dual sink nodes can be divided into linear wireless sensor node deployment, wireless sensor energy consumption model, and wireless sensor zone coverage principle. Another example is the wireless sensor network (WSN) deployment model along the asphalt road and the wireless sensor structure model, which are divided into WSN structure, sensor node structure, gateway interconnection of WSNs and other types of networks. Then this study conducts experiments and results analysis based on wireless sensors for improving the permeability of asphalt pavement and asphalt content. In this study, the factors affecting the water permeability of asphalt pavement are tested, and the application of sensors in testing its performance, and the optimal asphalt ratio is selected in the experiment to make its water permeability better. Finally, the study discusses and summarises the experiments, and it is concluded that the optimum asphalt content in the mixture is 5.48%–6.22%. Influencing factors include temperature and humidity, void ratio, cross slope gradient and so on. This experiment has a good reference prospect.

Adaptive clustering in energy efficient routing protocol for mobile nodes in WSNs

Introduction: Wireless Sensor Networks (WSN) is a collection of large number of small sensor nodes which communicate sensed data over a radio channel covering wide geographical region. Problem statement: A number of algorithms have been developed to enhance the network lifetime of WSN by efficiently utilizing the sources of energy. The most commonly used approach is clustering that is prone to uneven load balancing and instability issues. Furthermore, topological changes in WSN structure especially with mobile nodes significantly effect network lifetime. Methodology: In this study, we have proposed an Adaptive-Cluster-based Energy Efficient Routing Protocol (A-EECBRP), which employs a novel geometrical Voronoi-based configuration to solve load balancing and mobility issues while maintaining network stability and coverage. Furthermore, energy cost function and Energy Harvesters (EH) devices were implemented to reduce energy consumption and increase network life. Moreover, the concept of handshaking and random waypoint model for nodes movement between cluster groups was examined to define mobile nodes. Results: Simulation results obtained from network analysis performed on MATLAB® showed that A-EECBRP reduced energy consumption by almost 1500 rounds as compared to LEACH-M. This significantly improved the network lifetime of WSN as compared to the LEACH-M routing protocol. Therefore, our proposed scheme provides a huge potential for implementing energy-efficient routing protocols in mobile wireless sensor networks.

A blockchain-empowered authentication scheme for worm detection in wireless sensor network

Wireless Sensor Network (WSN) is a distributed sensor network composed a large number of nodes with low cost, low performance and self-management. The special structure of WSN brings both convenience and vulnerability. For example, a malicious participant can launch attacks by capturing a physical device. Therefore, node authentication that can resist malicious attacks is very important to network security. Recently, blockchain technology has shown the potential to enhance the security of the Internet of Things (IoT). In this paper, we propose a Blockchain-empowered Authentication Scheme (BAS) for WSN. In our scheme, all nodes are managed by utilizing the identity information stored on the blockchain. Besides, the simulation experiment about worm detection is executed on BAS, and the security is evaluated from detection and infection rate. The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.

Video-Like Lossless Compression of Data Cube for Big Data Query in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) contain many sensor nodes which are placed in chosen spatial area to temporally monitor the environmental changes. As the sensor data is big, it should be well organized and stored in cloud servers to support efficient data query. In this paper, we first adopt the streamed sensor data as "data cubes" to enhance data compression by video-like lossless compression (VLLC). With layered tree structure of WSNs, compression can be done on the aggregation nodes of edge computing. Then, an algorithm is designed to well organize and store these VLLC data cubes into cloud servers to support cost-effect big data query with parallel processing. Our experiments are tested by real-world sensor data. Results show that our method can save 94% construction time and 79% storage space to achieve the same retrieval time in data query when compared with a well-known database MySQL

Integration of Machine Learning Techniques in Virtual Wireless Sensor Network for insect monitoring

Agriculture industries are comparatively slow in adopting emerging technologies than any other industries despite lot of exciting research. The use of Wireless sensor network (WSN) is very important role in agriculture for more productive and sustainable growth. The structure of WSN is tightly application dependent. Every WSN have sensors, processing unit, low frequency radio wave transmitter and power supply using battery. With increasing number of interconnected WSN devices, there is substantial increase in data generation. It contains both control messages as well as application dependent data, collected by the sensors. The collected data are frequently sent to the nearest centralized controller for further processing and decision making. For continuous functioning of WSN, uninterrupted power supply is needed. Many researches are carried out to overcome these challenges. In this manuscript we are proposing a simple and effective machine learning techniques combined with pause and play method to increase battery life of WSN. This could be achieved in three stages play-pause-play (PPP) model. First by gathering data for some time (play mode), Second by putting WSN to sleep (pause mode), in the backend, apply machine learning algorithm that helps to build model from training data to predict the future data. At the final stage, put WSN back to play mode. Compare the result with actual data and fine tune the model to reduce the error. Using this method WSN will get enough sleep time to increase overall life by simulating the normal behaviour of sensor node. The sleep time will be calculated dynamically.

Evaluation key generator of Multiple Asymmetric methods in Wireless Sensor Network (WSNs)

The wireless sensor network (WSNs) is constructed with a combination of the sensor nodes and the sink nodes. WSNs applied in many applications. The Security in WSNs is necessary because of limitations of storage, computing capacity, power use. Encryption is one of the most important tools utilized to supply the security services for WSNs. Asymmetric and symmetric encryption algorithm can be utilized in the WSNs structure to supply the security. The asymmetric key encryption algorithm gives a higher level of the security, but compared to symmetric key encryption, that causes extra sensor overhead. In this research KCMA method used to generate chains key of twelve experiments of the algorithms (ECC, RSA, ELGamal). These chains merged with hash function SHA2 and XOR. Diehard test was utilized in all experiments to evaluate the randomness of the secret key generated, and show it’s more security system. SHA2 was the best as compared with XOR. Also, the work evaluated the performance (time) for the system and throughput network.

Employing Blockchain Technology to Strengthen Security of Wireless Sensor Networks

The proposed approach uses blockchain-based technology to strengthen the data security of wireless sensor networks (WSNs). This paper integrates blockchain-based technology with data transfer to establish an extremely secure WSNs structure. The present wireless network is built on the architecture of the Internet of Things (IoT) and employs a blockchain-based method to make the reliability of data transmission strong. In this proposed research, many small-area wireless sensor networks establish the entire WSNs structure, and every small-area wireless sensor network has a primary data collection node called a “mobile database.” The “mobile database” node of this study uses embedded microcontrollers with an operating system, such as Raspberry Pi and Arduino Yun. This block contains the sensor data collected by itself and the hash value of the previous block. Then the hash value of its own block, which is also part of the hash calculation of the next block, was calculated through the mining calculation program. Any block in the proposed method includes the encrypted hash-value of the previous block, the current timestamp, and the transaction data. In our research content, the transaction data is represented as wireless network sensing data. Basically, the system employs the hash function for calculation using the Merkel-tree algorithm. Such programming makes the block with blockchain-based technology difficult to tamper with content. This study approach revises the blockchain-based transaction ledger to become a sensor data record. Therefore, the proposed system gathers and analyzes sensor data for more reliability in the wireless sensing network structure. Furthermore, the innovative system with blockchain-based technology can treat a private cloud-end. This paper also carries on to visualize the uploaded sensing data by the sensors and draws corresponding charts based on big data analysis. The wireless network architecture proposed in this paper is built on embedded devices, making it easy for the system to build a web server. Using Python or JavaScript programming language in the web environment is relatively more convenient for data visualization and data analysis. Finally, this study uses traditional methods and innovative methods to compare data transmission. When the system uses innovative methods with blockchain-based technology, it is almost impossible for any operator to tamper with the data transmitted by the sensor.

MOMHR: A Dynamic Multi-hop Routing Protocol for WSN Using Heuristic Based Multi-objective Function

Wireless sensor networks (WSNs) are the networks which mainly focuses on the applications and are composed of considerable sensor nodes. The use of energy in a valuable way is considered as a feature for the design structure of WSNs. In the WSNs, the nodes power sources are limited. Moreover, because of this, there is a must for a different approach regarding the energy availability and this is mainly for long distance communication, for this multi-hop (MH) systems are chosen. Even though MH decreases the energy cost used by all node along the path, however, to obtain the best routing path among nodes is yet an interesting subject. In this article, we present a multi-objective multi-hop routing (MOMHR) protocol for optimal data routing to gain the network lifetime. In the first phase, the K-means algorithm is applied to split the nodes into k clusters. Next, the artificial bee colony optimisation algorithm is applied to obtain the best possible CH within each cluster then using a multi-objective functions finally the multi-hop routing protocol finds a multihop path with minimum communication cost from the node to the base station. Our proposed method is simulated in MATLAB platform and compared with two recent protocols such as low energy adaptive clustering hierarchy and energy efficient centroid-based routing protocol. The execution of the proposed MOMHR protocols using multi-objective function is evaluated using metrics such as energy efficiency and network lifetime.

An overview on wireless sensor networks and finding optimal location of nodes

In this review, our aim is to make a brief description about technology of Wireless Sensor Network (WSN) and its capability to pave the way in order to make connection between physical and virtual world based on Internet worldwide network. Hence, in this technology, sensor nodes play an important role to transmit data from a node to other defined nodes in its broaden range. Due to gain most optimal state from WSNs, subject of localization for radio frequency networks has a great importance in many technical applications such as military devices to detect specified local points to attack or defend, civil engineering and in general sensor networks. The main technology to obtain direct locations is GPS (Global Positioning System). After expressing a brief history on introduction part, we will go through in order to interrogate on main structure of WSNs regarding mathematical formulations and algorithms to find best and optimal access points based on Localization action. Then, we summarize algorithms and approaches to develop in order to introduce the best strategy in order to access nodes in the best possible state in WSNs. As a result, we conclude about the mentioned issues in order of comparison and reaching a final result. Therefore, final aim of this review is to explain efficiency and reliability of localization based on different opinions. Results show this overwhelming technology can be completely modified in order to find new solutions to find nodes in most optimal nodes based on spontaneous structure of WSNs.

An Overview on Wireless Sensor Networks and Finding Optimal Location of Nodes

In this review, our aim is to make a brief description about technology of Wireless Sensor Network (WSN) and its capability to pave the way in order to make connection between physical and virtual world based on Internet worldwide network. Hence, in this technology, sensor nodes play an important role to transmit data from a node to other defined nodes in its broaden range. Due to gain most optimal state from WSNs, subject of localization for radio frequency networks has a great importance in many technical applications such as military devices to detect specified local points to attack or defend, civil engineering and in general sensor networks. The main technology to obtain direct locations is GPS (Global Positioning System). After expressing a brief history on introduction part, we will go through in order to interrogate on main structure of WSNs regarding mathematical formulations and algorithms to find best and optimal access points based on Localization action. Then, we summarize algorithms and approaches to develop in order to introduce the best strategy in order to access nodes in the best possible state in WSNs. As a result, we conclude about the mentioned issues in order of comparison and reaching a final result. Therefore, final aim of this review is to explain efficiency and reliability of localization based on different opinions. Results show this overwhelming technology can be completely modified in order to find new solutions to find nodes in most optimal nodes based on spontaneous structure of WSNs.

Reliable Data Fusion of Hierarchical Wireless Sensor Networks With Asynchronous Measurement for Greenhouse Monitoring

This paper investigates the data fusion problem of wireless sensor networks (WSNs) for the greenhouse monitoring system. Considering the characteristics of local consistency and slow change of the greenhouse environmental information, the hierarchical structure of WSNs is proposed for the greenhouse monitoring system, and the two-stage data fusion scheme is presented for the hierarchical network. In the first stage, the weighted data fusion algorithm of WSNs on local state estimation is designed for the cluster, which would improve the fusion accuracy and the ability of anti-interference of the system. Moreover, the multirate measurement mode is proposed to reduce the energy consumption of WSNs under the premise of satisfying the information sensing performance of the system. In the second stage, the data fusion at the sink node is conducted on the support function with the consistency analysis of data from different clusters. The simulation analysis on the greenhouse temperature information is provided to show the effectiveness of the proposed data fusion scheme.

A Hierarchical Matrix Decomposition-Based Signcryption without Key-Recovery in Large-Scale WSN

The sensors in wireless sensor network (WSN) are vulnerable to malicious attacks due to the transmission nature of wireless media. Secure and authenticated message delivery with low energy consumption is one of the major aims in WSN. The identity-based key authentication scheme is more suitable for the WSN. In this paper, the Hierarchical Matrix Decomposition-based Signcryption (HMDS) algorithm was proposed, which is a kind of identity-based authentication scheme. In HMDS scheme, three-layer architecture, base station (BS), cluster head, and intracluster, is employed to adapt to the common structure of WSN. As the key generation center (KGC), the BS adopts matrix decomposition to generate the identification information and public key for cluster head, which not only reduces the cost of calculation and storage but also avoids the collusion attack. Experiments show that the HMDS algorithm has more advantages over other algorithms and is very suitable for the large-scale WSN.