Network Life Cycle Research Articles

LEACH Clustering Routing Protocol Based on Balanced Energy Consumption

<p>Faced with the problems of unbalanced energy consumption (EC) and short lifetime of nodes in Wireless Sensor Networks (WSN), a Low Energy Adaptive Clustering Hierarchy (LEACH) clustering routing protocol based on energy balance, namely LEACH-EB (LEACH Based on Energy Balance) protocol was proposed. At the initial selection stage, the nodes which are close to the base station (BS) with great remaining energy and many neighbor nodes are selected as the cluster heads (CHs); then, the non-CH nodes enter the clusters which have the least costs based on the strength and remaining energy of the communication signals between themselves and different CHs. At the data transmission stage, if the CH which sends the information is one hop away from BS, the CH needs to select a neighbor CH with the largest forwarding probability as the next hop relay node based on the remaining energy of each neighbor CH, the number of nodes in the cluster, and the distance from BS. The selected neighbor CH continues to determine the next hop in the above manner until the data is successfully sent to BS. Simulation tests show that LEACH-EB protocol can receive more data and extend the network life cycle by 60%, 43.1%, and 13.36% compared with LEACH, LEACH-C, and FIGWO, respectively. </p> <p> </p>

Bot Monitoring Jaringan Pada BMT Mentari Lampung Timur Menggunakan Mikrotik Dan API Telegram

Network notifications are very much needed by the network technical team. In addition, network notifications function to provide information to the technical team to find out the current condition of the server or router which is under the supervision of the technical team so that if the server is down, it can be handled quickly. The research method used is DIO Network Lifecycle. DIO Network Lifecycle is a network design method or commonly referred to as a network service life cycle designed to support network development. The research phase begins with design, implementation and operation. The research output produced is in the form of BOT monitoring of the BMT Mentari Lampung Timur network using Mikrotik and the Telegram API.

Construction of Landscape Ecological Planning Evaluation Model Based on Sensor Network

The application of wireless sensor network (WSN) technology promotes the modernization of forestry. WSN application technology in forest areas is an important research topic for the sustainable development of forestry in China and is also a research hotspot for forestry ecological monitoring at present. The application of wireless sensor networks in forest areas, first of all, solves the problem of limited energy supply and low-latency data transmission in the forest environment. Due to the large area of the forest environment and uneven tree density, dynamic changes in forest height, easy to block the signal, and other characteristics, the forest environment is prone to node energy depletion fast, the network life cycle is short, and data transmission delays large dilemma. Second, the application of wireless sensor networks is usually centered on maximum data acquisition, but the contradiction between high data acquisition rate and limited energy supply is inevitable, so it is necessary to construct a maximum data acquisition rate model with limited energy supply as a constraint to guarantee the optimal acquisition conditions for wireless sensor networks. In this paper, from the application of wireless sensor network technology in forest environment, the research on the application of wireless sensor network in forestry is carried out around the analysis of energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision-making fire danger warning process, so as to provide a solution to the overall problem of forest fire warning based on rechargeable wireless sensor network. In this paper, we analyze the dynamic replenishment of energy in rechargeable wireless sensor networks and propose an energy-based transmission control protocol that effectively improves data transmission efficiency. In the rechargeable wireless sensor network, the network E2E (end-to-end) average delay time is calculated based on the number of nodes on the data transmission link. The research idea of this paper starts from the application technology of wireless sensor network in the forest environment, and the design of the energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision fire danger warning process are realized vertically.

Enhancing Child and Adolescent Psychiatry Recruitment Through a Medical Student Mentorship Network: A Qualitative Study.

ObjectiveThere is a shortage of psychiatrists necessary to meet the clinical needs of children and adolescents. Efforts over the past decade to enhance the workforce have had a limited impact. This study sought to identify the critical components of a medical student mentorship network designed to increase recruitment into the subspecialty.MethodsThe authors conducted interviews via synchronized videoconferencing of network site leaders and medical students at 14 schools throughout the USA. In addition, they analyzed verbatim transcripts using a thematic-phenomenological qualitative approach.ResultsThe authors interviewed thirty-eight program participants during seven focus group sessions: nine program directors and 29 medical students or graduates, a median of five participants per session. They constructed a framework consisting of two overarching domains, comprised of three themes each: (1) life cycle of a subspecialty mentorship network (Origins, Initiation, and Continuity); and (2) next steps to improve the program (Refining goals, Increasing accessibility, and Defining a path forward).ConclusionPreliminary data have already documented the positive impact of participation in this mentorship program on medical student match rates into psychiatry. The qualitative model of this study provides a blueprint to develop, maintain, and optimize this and similar efforts aimed at increasing the child and adolescent psychiatry workforce.

Application of virtual reality technology in multimedia resource with a focus on the COVID-19 outbreak

In order to solve the problem of high energy consumption caused by unable to extract color space parameters in multimedia resource compression and transmission algorithm, the application of virtual reality technology in multimedia resource compression and transmission algorithm is studied. The research's main part is based on the Covid-19 Outbreak and the use of VR technology. The pixels are classified according to labeled and unlabeled, the multimedia resource allocation strategy is established, the resource target area is extracted by virtual reality technology, and the over-segmentation is controlled to a small extent, so as to control the quality of resources. In order to reduce the number of data transmissions and reception in the process of data aggregation in the network, a transmission signal reconstruction model is constructed, and the data is compressed and encoded. A compression transmission algorithm is designed, which uses compressed sensing and network coding to reduce the amount of data transmission. The experimental results show that the energy consumption of the compression transmission algorithm designed in this paper increases the slowest with the increase of single hop distance, and the energy consumption is also the lowest. Taking the bit rate of 0.25bpp as an example, the maximum energy consumption of the algorithm is 3.89J, which is 4.97J and 2.45J less than the direct transmission algorithm and the centralized compression transmission algorithm, respectively. Therefore, the algorithm can reduce energy consumption and prolong the life cycle of transmission network.

An improved approach for energy consumption minimizing in WSN using Harris hawks optimization

Wireless Sensor Network (WSN) is made up of minimal power devices (or) units spread over geographically separated locations. Sensors are grouped in the form of clusters. Every cluster has a key node known as the Cluster Head (CH). CH gathers sensed information out of its sensor nodes and transmits into a Base Station (BS). Sensors are indeed installed using non-replaceable batteries. WSN is concerned about its energy usage to reduce (or) minimize the consumption of energy as well as increase network lifetime. An improved upgraded technique is presented, which is accomplished by improving appropriate energy balancing in clusters across every sensor node in order to reduce power dissipation while networking connections. The enhanced technique was built by employing a well-known technique named cluster head selection. Accordingly, the energy consumption of WSN is reduced to prolong the network life cycle other than the network models. Furthermore, an efficient routing CH is optimized by the Average Fitness-based Harris Hawks Optimization (AF-HHO). In the WSN network, this proposed algorithm is used to locate neighbouring nodes with higher energy efficiency measurements. As a result, when compared to other conventional approaches, the simulation results demonstrate superior performance. Through the sink node, an optimal routing path for transferring data packets to neighbouring sensor nodes was discovered. The suggested technique is evaluated using energy consumption, network lifespan, and residual energy performance estimations.

Routing Protocol for Wireless Sensor Networks Based on Archimedes Optimization Algorithm

One of the key design problems of wireless sensor networks is to reduce energy consumption and improve node survival. Because the battery in sensor nodes is difficult to replace and the energy is limited, the design of energy-saving routing protocol becomes very important. Aiming at the problems of limiting node energy and shortening network lifetime in wireless sensor networks, a WSNs routing protocol based on improved archimedes optimization algorithm (IAOAR) is proposed in this paper. Firstly, in the cluster establishment phase, the protocol defines different fitness functions according to the energy, number and distance of sensor nodes to select the appropriate initial cluster. Then the fitness value of the node is calculated, and the weight is dynamically updated according to the number of iterations to improve the optimization ability of AOA algorithm. Virtual force is introduced to adjust the selected cluster head position to ensure the selection of optimal cluster heads, reduce the transmission energy consumption of common sensor nodes. In the data transmission stage, combined with the improved ant colony algorithm, the shortest transmission path to the sink node is constructed to reduce the energy consumption of long-distance data transmission at the cluster head. The simulation results showed that compared with LEACH, E-LEACH, LEACH-ANT and MAXLEACH protocols, the network life cycle of the protocol proposed in this paper was improved by 140.55%, 107.09%, 99.24% and 96.76% respectively. It effectively reduced the speed of node death, balances the network energy consumption and prolonged the network lifetime.

Blockchain-Enhanced Spatiotemporal Data Aggregation for UAV-Assisted Wireless Sensor Networks

Wireless sensor networks (WSNs) are widely used in the field of monitoring. For data collection of sensor nodes in large-scale monitoring scenarios, unmanned aerial vehicle (UAV)-assisted WSNs have emerged. For the security and validity of data collection, a blockchain-enhanced data collection framework for UAV-assisted WSNs is presented in this article. To reduce data redundancy in WSNs, a sparsity-optimized and compressed sensing-based spatiotemporal data aggregation model is built. A UAV identity authentication mechanism based on a Merkle tree is also designed to ensure the security of data transmission. By combining blockchain building and data aggregation, a disaster semantic blockchain (DSB) based on a data reconstruction-directed consensus mechanism is presented. Disaster semantics are extracted by analyzing the semantic association relationship of disaster, background, event, and sensor data. The experimental results show that the blockchain-enhanced spatiotemporal data aggregation effectively increases the network life cycle and data reconstruction accuracy. The disaster situation can be described accurately through the DSB.

Research on intellectual property protection, innovation, and data protection algorithm based on wireless communication network

In today's world, with the developing technologies, data protection has become an absolute requirement, many organizations are focusing on the security of the data and information. Because many unauthorized individuals can hack computer system, putting the confidential files of the organization at danger. Therefore, there is need to employ various data security techniques in order to secure information. Furthermore, to resolve the problem of high energy consumption caused by large amount of data transmission in data protection algorithm, a data protection algorithm based on wireless communication network is proposed. Furthermore, we investigated that nowadays the protection of intellectual property is become significant issue. Because intellectual property security is essential for promoting innovation. Without intellectual property protection, individuals and firms would not gain the full advantages of their creations and would devote less time to development. The communication channel and data transmission link are established. Each node calculates the residual energy when clustering and sends it to the cluster head before the link is generated. The random number of nodes is encrypted and sorted according to the order of data link. Based on the wireless communication network, the privacy data within and between clusters are fused, and the data difference of each node is calculated respectively. Each cluster head uses homomorphic transformation to realize data sharing. The data protection algorithm is designed. The node data is partitioned and encrypted and decrypted by hybrid operation. The fusion results are uploaded to the base station to complete data protection. Apart from this, in this research, we proposed various methodologies in order to secure information as much as possible including text, photography, forms, videos and many more. Experimental results show that compared with CPDA algorithm, CMT algorithm and HRCDA algorithm, the data protection algorithm designed in this paper consumes the least total energy in each round. The algorithm can protect the privacy of data, reduce the consumption of data, and extend the life cycle of the whole network.

Разработка алгоритма повышения эффективности протокола маршрутизации С-LEACH

In the process of studying wireless sensor network protocols and communication mechanisms, the extension of network service life and minimization of node power consumption have become important indicators. In order to reduce the energy consumption caused by communication in a wireless sensor network, improve network scalability and extend the network lifecycle, it is important to intelligently connect network nodes using a certain clustering algorithm. The paper proposes an improved routing protocol for wireless sensors with low power consumption LEACH, based on data aggregation (C-LEACH). The Kalman filter algorithm was used to solve the problem of data accuracy on cluster member nodes. The principle of operation of the Kalman filter is explained by the example of the noise signal of the sensor. The above data modification model can be performed continuously to achieve the optimal evaluation and filtering effect. Thus, the volume of data sent by the node is reduced. Experimental results have shown that the proposed LEACH protocol based on data fusion (C-LEACH) effectively reduces data redundancy, reduces the power consumption of sensor nodes and prolongs the life cycle of wireless sensor networks compared to the traditional LEACH algorithm, significantly improves network integrity.

IBRE-LEACH: Improving the Performance of the BRE-LEACH for Wireless Sensor Networks

Wireless sensor networks are extensively used in different fields, including severe and harsh environments such as battlegrounds, volcanic areas, healthcare, and so on. The major constraint of WSNs is the limited power supply, which impacts the lifecycle of the entire network. Clustering is a performing method used in WSNs to optimize power consumption and extend the lifetime of WSNs. LEACH is considered the first classical clustering protocol used in WSNs to optimize energy consumption. Many protocols have been developed to enhance the conventional LEACH protocol. BRE-LEACH (Balanced Residual Energy LEACH) is one of them. It is used to enhance the performance of the LEACH protocol. In this paper, we propose a new improved BRE-LEACH protocol called IBRE-LEACH (Improved Balanced Residual Energy LEACH), which improves the performance of the BRE-LEACH approach. The IBRE-LEACH combines clustering and multi-hop techniques. It selects CHs according to the residual energy and limits the maximum number of nodes in each cluster to balance the energy consumption. Thus, IBRE-LEACH allows the Abandoned Nodes to send their data to the BS. Furthermore, it routes the gathered data using CHs, ANs, and a root node, which is a node with maximum residual energy and minimum distance to the BS. The simulation results in MATLAB show that the IBRE-LEACH protocol increases the throughput, optimizes energy consumption, extends network lifetime, and ameliorates stability by 81.99%, 94.33%, and 91.47% compared to BRE-LEACH, LEACH-C, and LEACH, respectively.

Design and Research of Building Indoor Environment Monitoring System Relying on 3D Modeling and Image Processing

In order to improve the monitoring effect of building indoor environment, this paper carries out indoor environment simulation through 3D modeling, uses image processing technology to collect environmental monitoring data, and proposes a routing algorithm applied in this environment. Moreover, this paper introduces the energy consumption model of sensor nodes and the multi-attribute decision-making method and uses the multi-attribute decision-making to propose an adaptive energy balance routing algorithm based on the indoor environment of the building. In addition, this paper establishes a simulation analysis, compares it with several other routing algorithms, and verifies that the proposed algorithm has better balance in network energy consumption and longer network life cycle. Finally, this paper combines three-dimensional modeling and image processing technology to construct the building indoor environment monitoring system. It can be seen from the simulation experiments that the proposed building indoor environment monitoring system based on 3D modeling and image processing can meet the actual needs of intelligent building indoor monitoring.

Multiscale Layout and Planning of Smart Gardens in the Environment of Agricultural Internet of Things.

This paper studies the general architecture and key technologies of the Agricultural Internet of Things and summarizes the latest progress of the Internet of Things system model. On this basis, a general system architecture model suitable for the Agricultural Internet of Things is initially established, and the key technologies of the Agricultural Internet of Things are expounded to provide a reference for the in-depth application and development of the Agricultural Internet of Things. Aiming at the problem that the energy consumption of each node in the network is uneven in the process of monitoring agricultural production environment by wireless sensor network, which leads to the failure of some nodes in the network too fast, an event-driven wireless routing algorithm for agricultural production environment monitoring is proposed. By reducing the number of pieces of control information sent in the cluster, the algorithm selects the next hop forwarding node from candidate nodes according to the forwarding cost function to shorten the data transmission distance, reduce energy consumption, and improve the life cycle of the entire network. The experimental results show that the algorithm in this paper effectively avoids the waste of node energy consumption caused by the active transmission mode and at the same time better balances the overall energy consumption of the network and prolongs the life cycle of the network. The platform satisfies the needs of a local garden bureau to integrate comprehensive landscaping business information and display comprehensive landscaping information in a comprehensive, timely, and dynamic manner. At the same time, it has made useful explorations in the development and integration of landscaping business data interfaces and GIS data interfaces. All system functions of the smart garden information management platform project are reasonably designed and completely correct and basically meet the software function requirements specified in the requirements specification. Some functions were found not realized during the test. After rectification, various systems have been improved. All system interfaces of the smart garden information management platform project have reasonable layout, simple operation, and good ease of use. The smart garden information management platform project meets the business logic requirements and fulfills the requirements of the information construction of the Garden and Greening Administration. All systems of the smart garden information management platform project are simple to install and easy to operate and meet the user's requirements after installation. The system has a strict permission setting function. People with different permissions can only see the content of the fields that they have permission to access, which effectively ensures the security of the data.

Survivability development of wireless sensor networks using neuro fuzzy-clonal selection optimization

Wireless Sensor Networks (WSN) are a kind of wireless network, transmitting data utilizing the multi-hop radio relaying technique, and with no fixed infrastructure. WSN has the ability to function as network host for transmission and reception of data. The unique characteristics of WSN include distributed routing; frequent path breaks due to mobility, packet switching, and self-organization. The energy restriction is an important aspect to consider while designing a sensor network in order to increase the network's survivability. Clustering is an essential approach for overcoming energy limits and increasing network longevity. In the LEACH-technique, simulated annealing optimization is employed to generate the optimal cluster construction. This approach consumes more energy in order to build the best clustering, and the sensor nodes quickly lose energy, reducing the network's survivability. So, Neuro Fuzzy-Clonal Selection Optimization (NF-CSO) model is constructed for minimizing the energy consumption, to identify the optimal position for multi-sink placement and to improve the network survivability. Initially Clonal Selection (CSO) algorithm does the task of determining the optimal position for placing the multi-sink and the Neuro Fuzzy algorithm were utilized to determine the best cluster head, resulting in less energy usage and an increase in network survivability. WSN's energy consumption has been decreased by about 58%, and the network life cycle has been increased by 65% compared to LEACH. The network simulator is used to implement the existing and proposed techniques. From the simulation analysis, it has been proven that the proposed NF- CSO algorithm performs better in selecting the optimal position of the multi-sink, and also reduces the energy consumption and increases network survivability. The proposed approach outperforms the existing LEACH, PSO and BFO techniques.

An adaptive threshold of remaining energy based ant colony routing algorithm

Because the node energy distribution among wireless sensor networks is not balanced and their routing algorithm is trapped in local optimal solution, this paper proposes the ant colony routing algorithm for wireless sensor network based on the adaptive residual energy threshold (ATRE-ARA). It introduces the search angle correction pheromone heuristic function to limit the search path and to reduce node energy costs. The residual energy threshold of the node is adaptive; the formula of pheromone increment is improved. The upper and lower limits of pheromone concentration are set; the pheromone updating strategy is optimized, thereby improving the accuracy of pheromone increment and the global optimization capability and balancing the residual energy of nodes in the wireless sensor network. The simulation results show that the ant colony routing algorithm reduces its average energy consumption by 15.12% and 11.68% in two environments and that its optimal path length is shortened by 1.47% and 1.59%, respectively, thus proving that the algorithm can effectively balance the global network energy consumption, improving the capability of the algorithm to search for global optimal solutions and extending the life cycle of the wireless sensor network.

Algorithm for energy-efficient interaction of wireless sensor network nodes

The actual problem of developing methods of interaction in wireless sensor networks focused on energy saving is discussed. It is shown that the operation of a wireless sensor network is built taking into account compromise mechanisms that make it possible to extend the life of the network in the presence of low-power sensor nodes on which the network is built. It is concluded that it is necessary to introduce new algorithms into the operation of wireless sensor networks, which make it possible to reduce the number of operations when calculating a route, transmitting data, or other operations without losing functionality, but contributing to a reduction in energy consumption. The paper proposes one of such algorithms that develops the idea of clustering wireless sensor networks in order to reduce the power consumption of sensor nodes by transferring some of the functions to the head nodes of the clusters. Unlike the well-known adaptive clustering algorithm with low energy consumption LEACH, the proposed algorithm is based on swarm intelligence and allows choosing not only the head nodes of clusters in the current round of functioning of the wireless sensor network, but also promising nodes that become heads of clusters in subsequent rounds. If we consider that one cycle of the wireless sensor network consists of a certain predetermined number of rounds, then the procedure for searching for cluster heads can be performed not at the beginning of each round, but only at the beginning of each cycle of the wireless sensor network. It is shown that the determination of the heads of wireless sensor network clusters in the future allows to reduce the total energy consumption and thereby increase the duration of the network life cycle. The advantage of adding the bee swarm algorithm to the wireless sensor network clustering procedure is demonstrated in terms of such indicators as the time of death of the first sensor node, the dependence of the number of functioning nodes on the network operation time and the data packet delivery coefficient. The wireless sensor network clustering procedure with the addition of the bee swarm algorithm to select cluster heads for the future can be useful when deploying a wireless sensor network in real applications.

Energy-efficient power scheduling and allocation scheme for wireless sensor networks

The focus in this paper is on coverage energy-efficient of WSN (wireless sensor networks). Communication path lengths of a randomly distributed BSs and sensor nodes field are characterized by distance distributions. For sensor nodes, this paper will use theory of Poisson point process (PPP) and Boolean Model (BM) to purpose a power allocation scheme results in green communication of sensor nodes. The energy allocation scheme of wireless sensor networks can help to prolong the life of the whole network. In this paper, we prove that the scheduling and allocation scheme can achieve energy saving, so as to prolong the life cycle of the whole wireless sensor networks. In the uniform placement migration case, we simulation 1000 times. In Boolean Model, There is 71.3% for power scheduling and allocation schemes and 28.7% is not. From these results, we see that, in wireless sensor networks, 20%–30% of total energy, which was being consumed from the part of power scheduling and allocation. The scheduling scheme improves response time, throughput and overall energy consumption over base case. Compared with other allocation schemes, the advantage of the scheme proposed in this paper is that the less sensors selected can still provide more than 95% detection area coverage. It will enable robust communication against cross-tier interference and co-layer interference thereby obtaining a substantial improvement in link quality.

A Study on routing optimization of Wireless Sensor Networks using an Enhanced LEACH protocols

The LEACH routing protocol equalizes network power consumption by randomly selecting cluster headnodes in a loop, which will cause network malfunctions. Therefore, to solve this problem, it is necessary to reduce the data transmission energy consumption in the routing protocol and increase the network life cycle. However, there is also the problem that cluster headers have a wide range, and forwarding data from cluster headers consumes a lot of power in LEACH, which has not yet been resolved. In this article, we present an approach to optimize the routing protocol. First, the optimal number of cluster heads is calculated according to the total energy consumption per round to reduce the probability of excessive distribution of cluster heads. The cluster head is then used as the nucleus to construct the Voronoi diagram. Nodes in the same Voronoi diagram become a cluster, so the energy consumption of intra-cluster communication would be lower. Finally, to optimize the multi-hop routing protocol, an ant colony algorithm is added using a cluster header close to the BS to receive and forward it from a remote cluster header. Based on MATLAB simulation data, the protocol can significantly extend the lifetime of WSNs compared to the LEACH protocol and increase the energy efficiency per node unit per round. The energy consumption of the proposed approach is unique. The approach improved first node kill time (FND) by 127%, 22.2%, and 14.5% relative to LEACH, LEACH-C, and SEP, respectively.

Construction of an Innovative Development Model of Intelligent Media under the Coverage of a Wireless Sensor Network

A distributed network composed of sensor nodes with limited computing and communication capabilities is a wireless sensor network, which is a system that can autonomously and intelligently complete target tasks according to the surrounding environment. With its wide application in the fields of smart medical care, smart home, networks of vehicles, and smart media, its communication performance requirements are also increasing. According to the needs of different application scenarios, the first key problem to be solved in wireless sensor networks is what optimization coverage strategy to adopt, which will have a direct impact on the optimal allocation of very limited resources such as node energy, communication bandwidth, computing power, and other network services’ quality. Nodes adopt a probability-based joint perception model, and its algorithm is a node scheduling mechanism based on the connected dominating set to construct a tree. Each node sets the waiting time and becomes a candidate node priority according to the remaining energy and the distance from the parent node. In this paper, the issue of energy fairness is considered in heterogeneous wireless sensor networks. In order to prevent the occurrence of “energy holes,” this paper proposes a node deployment model similar to cellular networks. By deploying heterogeneous sensor nodes in this way, energy saving can be achieved. Based on this model, game theory is used to simulate the data packet transmission process between sensor nodes, an energy consumption mechanism suitable for each stage of data transmission is proposed, and Nash equilibrium is finally obtained by rationally designing the measurement function. The node deployment scheme proposed in this paper not only balances the energy consumption of the network but also prolongs the life cycle of the network. Aiming at the three-dimensional (3D) space environment, this paper studies a node deployment mechanism that guarantees connectivity and has a perceptual coverage degree of k with the help of the Reuleaux tetrahedron model. In this paper, a node deployment strategy is proposed and compared with the node deployment algorithm for 3D sensor network based on truncated octahedron. The simulation experiment results show that the wireless sensor network with artificial intelligence can not only optimize the production process of intelligent media but also improve each link of the media industry chain and further catalyze the development of new formats in the media industry. The experimental results also show that the algorithm can effectively meet the requirements of sensing coverage and connectivity coverage, the number of working nodes is small, the network life cycle is significantly prolonged, and the overall energy consumption of the network is reduced. The study results of this paper provide a reference for follow-up research on the construction of innovative development model of intelligent media under the coverage of wireless sensor network.

Algorithm for wireless sensor networks in ginseng field in precision agriculture.

In the research on energy-efficient networking methods for precision agriculture, a hot topic is the energy issue of sensing nodes for individual wireless sensor networks. The sensing nodes of the wireless sensor network should be enabled to provide better services with limited energy to support wide-range and multi-scenario acquisition and transmission of three-dimensional crop information. Further, the life cycle of the sensing nodes should be maximized under limited energy. The transmission direction and node power consumption are considered, and the forward and high-energy nodes are selected as the preferred cluster heads or data-forwarding nodes. Taking the cropland cultivation of ginseng as the background, we put forward a particle swarm optimization-based networking algorithm for wireless sensor networks with excellent performance. This algorithm can be used for precision agriculture and achieve optimal equipment configuration in a network under limited energy, while ensuring reliable communication in the network. The node scale is configured as 50 to 300 nodes in the range of 500 × 500 m2, and simulated testing is conducted with the LEACH, BCDCP, and ECHERP routing protocols. Compared with the existing LEACH, BCDCP, and ECHERP routing protocols, the proposed networking method can achieve the network lifetime prolongation and mitigate the decreased degree and decreasing trend of the distance between the sensing nodes and center nodes of the sensor network, which results in a longer network life cycle and stronger environment suitability. It is an effective method that improves the sensing node lifetime for a wireless sensor network applied to cropland cultivation of ginseng.