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Wireless sensor networks which are based on distributed information processing technology are taking an increasingly key role in industrial digital twin scenarios. There are many important issues in the access of networks. One of the most important issues is how to improve network access control and the effectiveness of load balancing. Based on the industrial digital twin technology, this article first introduces several typical network access and network loads and performs tree-structured processing on the outliers generated during the chain formation process to reduce the length of the data transmission path, optimize the main chain head and subchain chain head selection strategy and chaining rules, and perform nonchain operations on common nodes and chain heads near sink to reduce data inverse transfer. The experimental results show that this paper uses the digital twin calculation formula to accurately and objectively determine the remaining cluster head and the distance head and the base station, so that when the node distance is limited, the network energy consumption can be balanced as much as possible, and the network load is promoted. [ABSTRACT FROM AUTHOR]

The study aimed to solve the common problem that hardware limitations and degradation make the data obtained in reality usually incomplete and improve the quality of communication transmission. In this paper, we propose a new low-rank tensor complementation model LRTC-CSC, which is based on tensor kernel parametrization (TNN), preserves the low-rank structure of information while restoring the detail features, and finally solves the problem using the efficient alternating direction multiplier method (ADMM). Based on the low-rank nature of the tensor, adding convolutional sparse coding (CSC) can well represent the characteristics of the high-frequency part of the information to handle the details while recovering the global information. The experimental results show that the training set of this paper saves much time compared with other models in several metrics by using only ten images of similar color for each data. At the same time, the data recovery effect is much higher than the novel TV canonical prior. In particular, the LRTC-CSC model is 5.18 dB higher than the LRTC-TV model in terms of PSNR value for image recovery at a 70% missing rate. The LRTC-CSC model proposed in this paper is more accurate and efficient for communication data restoration. [ABSTRACT FROM AUTHOR]

Due to the poor effect of the traditional vocational education platform, it is difficult to meet the requirements of the current Internet education platform. To solve this problem, this paper designs a vocational education platform system based on blockchain and Internet of Things (IoT) technology. First, the system access control strategy based on blockchain technology is introduced into the teaching system so as to improve the security of the teaching system. Then, in order to solve the single point of failure and efficient transmission problems of access control in the IoT environment, this paper proposes an access control strategy based on main side chain cooperation. This strategy introduces a side chain to expand the blockchain and improve the data carrying capacity of the blockchain. To meet the requirements of high-speed data transmission, this paper designs an access control model suitable for the main side chain blockchain structure. Experimental results show that compared with other algorithms, the data request speed of the system in this paper is faster, and the storage space is smaller. Therefore, the proposed technology based on blockchain and IoT can meet the use requirements of vocational education platforms. [ABSTRACT FROM AUTHOR]

The rapid development of mobile Internet has promoted the rapid rise of cloud computing technology. Mobile terminal devices have greatly expanded the service capacity of mobile terminals by migrating complex computing tasks to run in the cloud. However, in the process of data exchange between mobile terminals and cloud computing centers, on the one hand, it consumes the limited power of mobile terminals, and on the other hand, it results in longer communication time, which negatively affects user QoE. Mobile cloud can effectively improve user QoE by shortening the data transmission distance, reducing the power consumption, and shortening the communication time at the same time. In this paper, we utilize the property that genetic algorithm can perform global search seeking the global optimal solution and construct a dynamic task scheduling model by combining the device-cloud link. The task scheduling model based on genetic algorithm and random scheduling algorithm is compared through comparison experiments, which show that the assignment time of the task scheduling model based on genetic algorithm is shortened by 11.82% to 48.51% and the energy consumption is reduced by 22.28% to 47.52% under different load conditions. [ABSTRACT FROM AUTHOR]

The data acquisition of Internet of Things (IoT) is mostly brought out by wireless sensor networks (WSNs), and the efficiency of IoT is directly affected by the time delay in the process of data acquisition, which is researched mainly by the data aggregation of WSNs. Minimizing the delay in the data aggregation process is one of the most important operations. In order to reduce the data aggregation delay, a hybrid delay-minimization data aggregation scheduling (HDDAS) algorithm is proposed, which optimizes the delay from the two main aspects that affect the delay, namely, the transmission path and the collision rate. Accordingly, the algorithm is divided into two phases: the aggregation tree construction and the data transmission scheduling. In the aggregation tree construction phase, the fat tree (FT) is introduced to generate an optimal aggregation tree with the shortest path; in the data transmission scheduling phase, the maximum parallel transmission set (MPTS) is adopted to increase the amount of the collision-free data transmission. The simulation experiment results demonstrate that the HDDAS algorithm proposed in the paper has performed favorably in terms of the data aggregation delay. [ABSTRACT FROM AUTHOR]

6LoWPAN allows IEEE 802.15.4 standard-based wireless sensor networks (WSNs) to be connected to the Internet through the Internet protocol IPv6; however, its performance decreases as the network grows in size due to complications such as the bottleneck problem; therefore this paper aims to improve the performance of 6LoWPAN-based WSNs by using the IEEE 802.11AH standard as a backbone in these networks, since this emerging new technology is suitable for IoT applications, as it can provide a coverage range up to 1,000 m and data transmission rates up to 78 Mbps. The IEEE 802.11AH standard can be used as a backbone by utilizing its characteristics to improve some of the performance parameters of the 6LoWPAN networks such as end-to-end delay, frames delivery ratio, and the network throughput. This paper proposes a heterogeneous network infrastructure consisting of 6LoWPAN and the IEEE 802.11AH standard to enable bidirectional data transmission between the network components and the Internet via the Internet protocol IPv6 with two types of gateways, the edge gateways to connect the entire network to the Internet and the intermediate gateways to connect the 6LoWPAN clusters to the edge gateways. The simulation results demonstrate that the heterogeneous network approach can provide significant improvement gains compared to the 6LoWPAN homogeneous networks, since it shows clear improvements to the packets delivery ratio, the end-to-end delay mean value and the network throughput, subsequently leading to a distinct enhancement in the network's overall reliability. [ABSTRACT FROM AUTHOR]

With the rapid development of 5G communication and wireless Internet of Things technology, the application of intelligent wearable devices based on wireless data transmission technology is becoming more and more popular. However, due to the bandwidth of wireless data transmission nodes and the power consumption of the device system, the use time and data storage of wearable devices are severely restricted. The compressed sensing (CS) technology has become an effective method to tackle this problem. CS technology includes data compressive sensing at the transmission end and data reconstruction at the receiving end. In this paper, we consider the reconstruction of nonnegative sparse vectors, an important problem in the area of CS for wireless data transmission. It is known that the interval-passing (IP) algorithm is a low-complexity message-passing type method for the problem. However, the reconstruction performance of the IP algorithm is inferior to that of the other state-of-the-art CS reconstruction algorithms such as the orthogonal matching pursuit (OMP) algorithm. In order to address the problem, we propose a two-stage reconstruction algorithm in this paper. The proposed algorithm applies the IP algorithm for the first stage of reconstruction. If the reconstruction fails, the OMP algorithm is then used on the basis of the results in the first stage. The proposed algorithm is evaluated and compared with other state-of-the-art algorithms by the probability of perfect reconstruction under the given sparsity order value. Simulation results suggest that the proposed two-stage algorithm can greatly improve the reconstruction performance of the IP algorithm and can even outperform the OMP algorithm. In addition, the low-complexity advantages of the IP algorithm are maintained in the proposed algorithm. [ABSTRACT FROM AUTHOR]

Mobile computing is a new technology emerging with the development of mobile communication, Internet, database, distributed computing, and other technologies. Mobile computing technology will enable computers or other information intelligent terminal devices to realize data transmission and resource sharing in the wireless environment. Its role is to bring useful, accurate, and timely information to any customer at anytime, anywhere, and to change the way people live and work. In mobile computing environment, a lot of Internet rumors hidden among the huge amounts of information communication network can cause harm to society and people's life; this paper proposes a model of social network rumor detection based on convolution networks, the use of adjacency matrix between the nodes represent user and the relationship between the constructions of social network topology. We use a high-order graph neural network (K-GNN) to extract the rumor posting features. At the same time, the graph attention network (GAT) is used to extract the association features of other nodes of the network topology. The experimental results show that the method of the detection model in this paper improves the accuracy of prediction classification compared with deep learning methods such as RNN, GRU, and attention mechanism. The innovation of the paper proposes a rumor detection model based on the graph convolutional network, which lies in considering the propagation structure among users. It has a strong practical value. [ABSTRACT FROM AUTHOR]

In order to realize intelligent video surveillance of substation, this paper presents a substation robot working state monitoring system based on video surveillance. In this paper, the intelligent monitoring system of substation robot working state is constructed by combining virtual reality technology. Through the cooperation of each unit in the system, the real-time monitoring of substation robot working state and the early warning of abnormal working state are realized. The system can transmit video data at a high frame rate to ensure the timeliness of video data transmission and clearly and smoothly present the virtual scene of substation robot work. It can realize the high-precision positioning measurement of the robot under different distances and speeds, obtain the working dynamic trajectory of the robot according to the measurement results, analyze its working state, and give an early warning in case of abnormal working state, so as to achieve the purpose of intelligently monitoring the working state of the substation robot. The experimental results show that each group of video data transmission frame rate of the system can reach 29 f/s and is relatively stable. The average transmission frame rate is 30.62 f/s. The video transmission frame rate is high, which can ensure the timeliness of video transmission. Conclusion. The designed substation intelligent video monitoring system has good output stability and reliability. [ABSTRACT FROM AUTHOR]

At present, complex discrete dynamic systems are widely used in the field of medicine. The control system in the complex discrete dynamic model is gradually transformed into intelligent control. It has become the main research direction of researchers to improve the medical platform system by adding different modeling strategies. The traditional discrete modeling technology can only be used as the knowledge content of students' textbooks because it can no longer meet the needs of the development of human society. In order to improve the application of a discrete system in the public platform, this paper studies the improvement of the public health service platform system based on the complex discrete dynamic system. Firstly, a time-driven control strategy is proposed to study the output feedback control with random sampling in the platform. Then, the stability of random parameters and the addition of dynamic scheduling strategies are further studied. Compared with the traditional system, the optimized system greatly strengthens the data transmission problem of input and output channels. The results show that by improving the performance of the public health service platform system, the probability of problems in the process of data transmission is greatly reduced. After adding controllable and observable performance to the system, the stability of the whole system is further improved. The improved public health service platform system studied in this paper can store and transmit a large number of user data in the network environment, automatically maintaining the stability of the system and has a good social application value. [ABSTRACT FROM AUTHOR]

Internet of Things search has great potential applications with the rapid development of Internet of Things technology. Combining Internet of Things technology and academic search to build academic search framework based on Internet of Things is an effective solution to realize massive academic resource search. Recently, the academic big data has been characterized by a large number of types and spanning many fields. The traditional web search technology is no longer suitable for the search environment of academic big data. Thus, this paper designs academic search framework based on Internet of Things Technology. In order to alleviate the pressure of the cloud server processing massive academic big data, the edge server is introduced to clean and remove the redundancy of the data to form a clean data for further analysis and processing by the cloud server. Edge computing network effectively makes up for the deficiency of cloud computing in the conditions of distributed and high concurrent access, reduces long-distance data transmission, and improves the quality of network user experience. For Academic Search, this paper proposes a novel weakly supervised academic search model based on knowledge-enhanced feature representation. The proposed model can relieve high cost of acquisition of manually labeled data by obtaining a lot of pseudolabeled data and consider word-level interactive matching and sentence-level semantic matching for more accurate matching in the process of academic search. The experimental result on academic datasets demonstrate that the performance of the proposed model is much better than that of the existing methods. [ABSTRACT FROM AUTHOR]

The existing routing protocols for wireless sensor networks were not reasonable in design, which limited their application. Most of the existing studies did not take into account the energy consumption of the network and the balanced use of the energy of sensor nodes, which led to the unsatisfactory application effect of wireless sensor networks in some fields. Therefore, from the perspective of energy balance in wireless sensor networks, this paper proposed a construction method of an energy balance routing protocol in wireless sensor networks based on a fuzzy control strategy. Firstly, based on the analysis of the basic composition of wireless sensor networks and the structure of sensor nodes, this paper expounded the basic process of wireless data transmission and summarized the classification and characteristics of routing protocols in wireless sensor networks from different angles. Secondly, according to the node data transmission characteristics of wireless sensor networks, the energy balance use model of sensor nodes was established, and the design method of the energy balance routing protocol based on fuzzy control strategy was proposed, and the data transmission link was optimized. Finally, through experimental comparative analysis, the results showed that the energy balanced routing protocol proposed in this paper can effectively realize the energy balanced use of the network data transmission process. Compared with other common routing protocols, the wireless sensor network routing protocol proposed in this paper can not only improve the data transmission efficiency and reduce the data redundancy but also save energy consumption and prolong the network running time. The design method of routing protocol proposed in this paper will be conducive to the optimization and application of routing protocol in wireless sensor networks and provide a theoretical basis for the related research of wireless sensor networks. [ABSTRACT FROM AUTHOR]

The present industrial Internet platform (IIP) is subjected to numerous complex security issues, and thus technologies that focus on achieving data security of the IIP has become top priority. The data security crisis of IIP gets mainly reflected in the malicious deletion and theft of data, the random access of terminal devices, and the low security of traditional security authentication methods. Blockchain technology adopts distributed network architecture, wherein through asymmetric encryption mechanism, it helps to solve problems associated with single point of downtime and privacy data leakage of central management of industrial Internet. In addition, considering the accept of random access and deletion of industrial interconnection terminal equipment, this paper uses the role access control mechanism based on Hyperledger, thereby regulating user access according to the user's role in the platform and management of terminal equipment through chain code. The paper includes the following contributions: (1) firstly, it expounds the research background and significance of the IIP and introduces the research status of the industrial Internet and blockchain at home and abroad. (2) Secondly, the IIP architecture is designed based on blockchain technology and implements a sensor node management and monitoring system. (3) Thirdly, the paper uses the gateway to preprocess the collected data, thereby reducing the data transmission delay and improving the real-time and effectiveness of the data. The paper finally implements neural network to evaluate the construction quality of industrial Internet sensor nodes and obtains promising test results. [ABSTRACT FROM AUTHOR]

M2M is a concept and a general term for all technologies that enhance the communication and network capabilities of machines and equipment. It is a combination of different types of communication technologies. M2M enables all devices and users to share information, saving operation time and improving work efficiency. M2M is not a simple data transmission, but it is an intelligent and interactive communication between machines. Even if no real-time signal is sent, the machine will actively communicate according to the established program and select intelligently according to the obtained data. The communication system refers to the general term of the technology that completes the information transmission function. The modern communication system is mainly realized by the propagation of electromagnetic waves in free space or the transmission mechanism in the guiding medium. When the wavelength of the electromagnetic wave reaches the light wave range, such a telecommunication system is called an optical communication system, and the communication system in the other electromagnetic wave range is called an electromagnetic communication system, abbreviated as a telecommunication system. The purpose of this paper is to explore the study of wireless data sharing method for M2M mobile telecommunication systems in the 5G era. It is expected that the new algorithm will make the wireless resource allocation more reasonable and improve the resource utilization rate. The performance of the deterministic measurement matrix proposed in this paper is close to or even better than that of the random measurement matrix. The M-SP algorithm greatly improves the performance of the SP algorithm. The experimental results of this paper show that when the number of microbase stations is 10, the energy consumption of the direct algorithm is 175000 W, the energy consumption of the indirect algorithm is 350000 W, and the energy consumption of the direct algorithm is much smaller than that of the indirect algorithm. [ABSTRACT FROM AUTHOR]

Network data is distributed data on electricity, with the explosive growth of network data, and it has become an inevitable trend of network development to synergized and shared crossdomain scattered data and enhances the value transmission of network data. Federated learning, as a technology that combines data value delivery and data privacy security, is widely concerned in the process of data sharing. However, currently federated learning is used within a single business system. In the process of crossdomain data sharing, how to ensure the data trust, model trust, and result trust of federated learning is still an urgent problem to be solved. To this end, we designed to use blockchain structure to record each behavior of data sharing. Based on its tamper-proof and traceability, combined with cryptography technology, we constructed an endogenous trusted architecture for crossdomain data sharing. In addition, a reverse auction node incentive mechanism based on high credit preference is designed to solve the common problems in data sharing, such as low enthusiasm of users in sharing, unstable data quality of contributions, and unreasonable distribution of data sharing benefits. Through theoretical analysis and experimental verification, it can be seen that the incentive mechanism designed in this paper can meet the authenticity, user rationality, and budget feasibility. On this basis, it can motivate users to participate in data sharing, improve the average quality of data shared by users, and ensure security and trustworthiness and resist malicious attacks to a certain extent. [ABSTRACT FROM AUTHOR]

Based on mobile edge computing and user perception technology, this paper analyzes and discusses the respective advantages and disadvantages of the important optimization models and mobile models in the animation art design, as well as the wireless block data transmission mechanism and protocol. In order to solve the problem that user mobility cannot be sensed, a content-centric mobile edge animation art design mechanism based on user mobility perception is proposed. This mechanism comprehensively calculates the centrality of users' perception of nodes, the idle rate of animation design, and the staying time of users in a small area. The mobile edge network controller integrates the information of each edge user's perception node, calculates the importance of each edge user's perception node and prioritizes it, and selects the appropriate content animation to design the user perception node according to the ranking result. Finally, various simulation or platform test experiments were carried out for all the design schemes in this paper, and the experimental results were analyzed. The simulation experiment results show that compared with the traditional animation design mechanism, the animation art design system effectively reduces the average number of hops for users to obtain content by up to 15.9%, improves the hit rate of edge user perception node animation design by at least 13.7%, and reduces the traffic entering the core network by up to 32.1%. According to the comparison results, the various designs in this work can successfully use sensor data to preclassify migration tasks in the mobile edge network environment. Compared with the latest block data transmission protocol, it has a significant performance improvement, reducing the data distribution delay by 34.8%, thereby helping to improve the overall efficiency of mobile edge computing. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Whether the traditional water equipment is equipped with remote transmission unit depends on whether the power consumption of the installed equipment can meet the expected life cycle. In the paper, by using intelligent strategies to save the power consumption of sending data, more sites can be selected to install remote transmitting units. In the process of transmitting data packet sequence, the remote transmission device needs to perceive the environment, interact with the environment and make decisions, and adjust the strategy according to the effect of the decision actions. Therefore, in this paper, the transmission process is modeled as Markov sequence decision model. And the real time signal interference noise ratio of the channel and the transmission delay of the data packet are defined as the state space. The decision action space consists of immediate transmission and delayed one, and the minimum total power consumption is taken as the objective function. The model is solved by Proximal Policy Optimization (PPO) algorithm, and the optimal decision sequence of site selection threshold is obtained. [ABSTRACT FROM AUTHOR]

Multipath data transmission is a key problem that needs to be solved urgently in wireless sensor networks. In this paper, sensor node failure, link failure, energy exhaustion, and external interference affect the stability and reliability of network data transmission. A multipath transmission strategy for wireless sensor networks based on improved shuffled frog leaping algorithm is proposed. A mathematical model of multipath transmission in wireless sensor networks is established. In the shuffled frog leaping algorithm, combined with the transition probability in the particle swarm optimization algorithm, random individuals in the subgroup are introduced to assist the search when updating the frog individual position, which improves the algorithm's ability to jump out of the local optimum and improves the quality of the optimization algorithm solution. The model is applied to multipath transmission in wireless sensor networks. Then, the shuffled frog leaping algorithm is used to update, divide, and reorganize the sensor nodes to select the optimal node to establish the optimal transmission path and improve the stability and reliability of the network. Simulation experiments show that the algorithm in this paper can ensure the reliability of data transmission, reduce the network packet loss rate and network energy consumption, and reduce the average delay of data transmission. [ABSTRACT FROM AUTHOR]

In order to improve the synergy effect of cross-border e-commerce slogistics, this paper combines intelligent logistics communication technology to construct a cross-border e-commerce collaborative logistics model. Moreover, this paper proposes a parallel energy-efficient routing algorithm based on 3D cell space to improve the system operation effect. In addition, this paper deeply analyzes the data fusion function performed by MA when accessing nodes and proposes a data fusion criterion to judge the necessity of data fusion on nodes. Finally, this paper balances the energy consumption of e-commerce logistics data fusion and data transmission so that the sum of the two is minimized. The data simulation analysis shows that the cross-border e-commerce logistics collaboration model proposed in this paper has certain effects, and it can be applied to the actual operation of cross-border e-commerce. [ABSTRACT FROM AUTHOR]

In order to improve the effect of English teaching, this paper combines with the intelligent algorithm to construct an intelligent interactive English teaching system for engineering education. In the process of interactive data processing, this paper specifies the time that a single pulse needs to be maintained and controls a counter to maintain a certain number of FPGA clocks. Moreover, data processing is completed in the digital domain, the modulation method is digital quadrature amplitude modulation, data transmission is generally in the form of a real signal, and the modulated IQ signal is converted back to a real signal. After constructing an intelligent interactive English teaching system for engineering education, this paper verifies that the intelligent interactive English teaching system for engineering education has certain effects through simulation teaching combined with the expert evaluation method. [ABSTRACT FROM AUTHOR]

This paper establishes a unified perception information transmission model for the difference in the number of cognitive radio users in wireless communication network systems. The model can effectively improve the utilization of spectrum resources. At the same time, this paper introduces a cyclic delay full diversity sensing information coding transmission scheme for the security risks of wireless communication networks. We established a system simulation model to compare performance under different correlation coefficients. The study found that the total interference intensity in the cyclic delay diversity system is lower than that of the frequency division duplex and time division duplex. Its antijamming attack capability also becomes stronger accordingly. [ABSTRACT FROM AUTHOR]

With the progress of society and the improvement of economic level, the traditional manufacturing industry is gradually transformed and upgraded in the changing times. In addition to the need for innovation in production technology, product design also plays a vital role in the sustainable development of the entire industry. However, the existing design methods have been unable to meet the high-quality requirements of consumers for material life. Therefore, this paper integrates multimodal sensor data fusion and transmission into product design. The multimodal sensor data fusion and transmission technology is developed on the basis of the human organs' ability to comprehensively judge the environmental information. This paper gives a brief overview of product design methods on the basis of this theory. Among them, the generation, development, classification, attribute level, and emotional level of products of product design methods are studied. And through the research on multimodal data fusion algorithm, the design method based on multimodal sensor data fusion and transmission technology is designed and practiced, and compared with the traditional QFD technology design method. The experimental results show that the design method proposed in this paper has the highest market demand adaptability of 86.37%, which proves its effectiveness. Popularizing this technology and method in the current stage of manufacturing industry product design can effectively improve the quality and efficiency of the design process. This has practical significance for enhancing the core competitiveness of products in the market. [ABSTRACT FROM AUTHOR]

With the development and progress of society, science and technology have entered the field of view of scholars at home and abroad. As the science and technology with the biggest potential in recent years, wireless sensor network has been involved in many scientific fields. This paper aims to study the wireless sensor modeling optimization algorithm of artificial intelligence neural network. In this paper, a WSN data fusion algorithm (DFRMP) based on regression model prediction is proposed, and the four algorithms of SLR, PAQ, TINA, and DFRMP are compared. The experimental results of this paper show that when the mean square error and mean absolute error are not much different, the data transmission rate of DFRMP algorithm is the smallest. When the absolute error threshold is 1, the data transfer rates of these four algorithms are 0.033, 0.0327, 0.035, and 0.017, respectively. This shows that the DFRMP algorithm proposed in this paper has superior performance. [ABSTRACT FROM AUTHOR]

Data aggregation technique removes redundant message in original data, reduces the amount of data transmission, reduces network communication overhead, improves message acquisition accuracy and collection efficiency, and prolongs the effective working time of the network. It is an energy-saving technique widely used in wireless sensor networks, one of the techniques. However, with the continuous operation in the wireless sensor network, the data aggregation technique saves the energy cost of the network, but also brings new security risks to the network. Therefore, how to ensure the confidentiality and integrity of data in the process of aggregation, calculation, storage, and forwarding is the core link of wireless sensor network security research. This paper uses SURF algorithm to study this question. The algorithm in this paper not only has good robustness to the data, but also introduces data aggregation and box filter in the calculation, so that the registration time can be better improved. After the research in this paper, the accuracy of the algorithm in this paper is 19% better than the traditional algorithm. At the same time, the accuracy of the aggregated data increases over time as the channel congestion decreases in the traditional process. [ABSTRACT FROM AUTHOR]

This paper is aimed at the problem that the process of students' developmental assessment is too comprehensive and the process of data collection is too old. It is very important but the performance of existing methods cannot meet the actual needs. So, this paper puts forward the design of distributed collection model of students' developmental information based on Internet of Things technology, which is based on the hardware design of students' developmental information distributed collection such as RF RC500F chip, TIMSP430 microprocessor, and interface in Internet of Things environment. Experimental results show that the model has less noise interference and strong data transmission ability, has higher collection accuracy of student development information, and can improve the authenticity and comprehensiveness of student development assessment. [ABSTRACT FROM AUTHOR]

Background/Motivation. Recently, a lot of interest in health is increasing due to the technology of the 4th industrial revolution. In particular, personal medical information through intelligent self-diagnosis is emerging as very important. However, such personal medical information causes many problems in security and reliability. Problem/Issues. Personal medical information accidents may occur on the server, but most of all, they occur more often in information sharing and data transmission. Therefore, in this paper, blockchain technology is applied to improve the reliability of such personal information management. Research Objective/Methodology. For intelligent healthcare incorporating blockchain technology, this study utilized the blockchain-based Internet of Things. In addition, information was accumulated using a number of measurement sensors to analyze individual ECG information. The measured biosignals were monitored for personalized diagnosis by analyzing the fused threshold. Result. In this paper, we implemented a monitoring system using measurement sensors to analyze individual biometric information. The implemented system information has improved reliability and security by incorporating blockchain technology. [ABSTRACT FROM AUTHOR]

In direct position determination (DPD), a large number of observation data need to be integrated and transmitted, which creates higher requirements for the transmission performance of the network. To alleviate the problem of performance degradation in a large number of data transmissions, this paper proposes a heterogeneous network architecture and transmission control algorithm for cross-regional heterogeneous networks. Through the heterogeneous integration of satellite and multihop networks, a transmission control model suitable for the long delay and high bit error rate environments is established, the congestion window of each stage of network transmission is analyzed, and the efficiency and accuracy of the algorithm are verified by experiments. The results show that a large amount of data can be transmitted in a heterogeneous network. When dealing with direct location, the algorithm can effectively transmit a large number of observation data for cross-regional heterogeneous networks. This simple and applicable transmission control algorithm can improve the satellite link throughput and reduce the download response time compared with the traditional transmission algorithm. These studies provide a reference for a large number of data transmissions in direct position determination. [ABSTRACT FROM AUTHOR]

The practical employment of network coding (NC) has shown major improvements when it comes to the transmission reliability of sender data and bandwidth utilization. Moreover, network coding has been employed recently to secure the transmission of data and prevent unauthorized recovery of sender packets. In this paper, we employ network coding (NC) in a practical way in networks with constrained resources with the goal of improving the reliability and security of data transfer. More specifically, we apply NC on the recent options of block-wise transfer (BWT) of the constrained application protocol (CoAP). The goal is to enhance the reliability of CoAP when used to transfer larger data blocks using BWT. Also, we employ an innovative homomorphic encryption approach to secure the BWT of CoAP. [ABSTRACT FROM AUTHOR]

Data collection and energy consumption are critical concerns in Wireless sensor networks (WSNs). To address these issues, both clustering and routing algorithms are utilized. Therefore, this paper proposes an intelligent energy-efficient data routing scheme for WSNs utilizing a mobile sink (MS) to save energy and prolong network lifetime. The proposed scheme operates in two major modes: configure and operational modes. During the configure mode, a novel clustering mechanism is applied once, and a prescheduling cluster head (CH) selection is introduced to ensure uniform energy expenditure among sensor nodes (SNs). The scheduling technique selects successive CHs for each cluster throughout the WSNs' lifetime rounds, managed at the base station (BS) to minimize SN energy consumption. In the operational mode, two main objectives are achieved: sensing and gathering data by each CH with minimal message overhead, and establishing an optimal path for the MS using the genetic algorithm. Finally, the MS uploads the gathered data to the BS. Extensive simulations are conducted to verify the efficiency of the proposed scheme in terms of stability period, network lifetime, average energy consumption, data transmission latency, message overhead, and throughput. The results demonstrate that the proposed scheme outperforms the most recent state-of-the-art methods significantly. The results are substantiated through statistical validation via hypothesis testing utilizing ANOVA, as well as post hoc analysis. [ABSTRACT FROM AUTHOR]

Mobile smart devices, such as mobile phones, wearable devices, and in-vehicle navigation systems, bring us convenience and have become necessities in modern daily life. The built-in global positioning system (GPS) of these mobile devices collects the users' mobility data to support path planning, navigation and other location-related applications, which also inevitably causes privacy issues. Previous research has shown that employing count-min sketch (CMS) to aggregate mobility datasets is a valid privacy-preserving method for resisting the reconstruction attack on population distributions. However, as the utility/accessibility of the protected datasets is excessively correlated with the size of CMS, decreasing the data transmission cost has become an unsolved issue of that approach. In this paper, we propose an efficient scheme with differential privacy to protect mobility datasets, which releases the privacy-preserving population distributions and achieves better utility as well as a much smaller data transmission cost compared to the CMS-based method. Our proposed scheme is comprised of two collaborative components, global sketch and temporal sketch. The global sketch is responsible for aggregating the raw mobility data and decreasing the data transmission cost, while the temporal sketch is in charge of guaranteeing the utility of the population distributions aggregated by the global sketch. Besides, to enhance the privacy preservation, we employ the Laplace mechanism to make the transmitted data satisfy ϵ -differential privacy. Through our analysis and empirical experiments, compared to the other three state-of-the-art privacy-preserving methods on mobility datasets, our scheme could preserve the privacy of the mobility datasets with much less data transmission cost under the same utility loss. [ABSTRACT FROM AUTHOR]

Real-time early warning based on deformation monitoring is an important measure to reduce the threat related to landslides. However, due to the complexity of landslide deformation, equipment accuracy, and data transmission interference, the displacement obtained by existing monitoring equipment has random errors, resulting in inaccurate landslide warning. In this paper, a tangent angle model based on the improved filtering method is proposed for the early warning of landslides. An improved filtering method is proposed based on the least-square method to smooth the measurement errors of monitoring equipment, considering both "data smoothing effect" and "accelerated deformation real-time determination". By comparing the least-squares method and the improved filtering method, the results demonstrate that the improved filtering method can more effectively smooth the fluctuation of the deformation rate. The amplitude of the error-induced tangent angle warning value fluctuation can be reduced, which provides correct early warning. The improved method provides a new approach for the real-time filtering of subsequent landslide deformation data. [ABSTRACT FROM AUTHOR]

Since the low cost and high flexibility, wireless automatic meter reading network (WAMRN) is widely used by utility companies to realize automatic collection and transmission of remote energy consumption information. Considering that WAMRN is composed of several wireless communication nodes, the lifetime of the network will be affected by factors such as the changeable deployment environment and the limited energy of nodes. Thus, a novel niche quantum ant colony-based WAMRN clustering optimization method is proposed in this paper to address the problem of how to make full use of the limited energy to extend network lifetime and improve data transmission efficiency. In the proposed approach, a clustering model of WAMRN is defined; moreover, an improved Niche Quantum Ant Colony Optimization (NQACO) is proposed to optimize the model therefore to obtain an optimal clustering scheme, which can help WAMRN reduce unnecessary energy loss to achieve the purpose of extending the lifetime of the entire network. To verify the performance of the proposed method, NQACO is compared with some popular clustering methods, i.e., GA and SA, under different scenarios. The results show that under the premise of ensuring network communication, NQACO is superior to the other two methods in reducing the total energy consumption and prolonging the network lifetime. [ABSTRACT FROM AUTHOR]

To ensure the security of data transmission and recording in Internet environment monitoring systems, this paper proposes a study of a secure method of blockchain data transfer based on homomorphic encryption. Blockchain data transmission is realized through homomorphic encryption. Homomorphic encryption can not only encrypt the original data, but also ensure that the data result after decrypting the data is the same as the original data. The asymmetric encrypted public key is collected by Internet of things (IoT) equipment to realize the design of blockchain data secure transmission method based on homomorphic encryption. The experimental results show that the accuracy of the first transmission is as high as 88% when using the transmission method in this paper. After several experiments, the transmission accuracy is high by using the design method in this paper. In the last test, the transmission accuracy is still 88%, and the data transmission effect is relatively stable. At the same time, compared to the management method used in this article, the transfer method used in this paper is more reliable than the original transfer method and is not prone to data distortion. It can be seen that this method has high transmission accuracy and short transmission time, which effectively avoids the data tampering caused by too long time in the transmission process. [ABSTRACT FROM AUTHOR]

This paper presents a backpropagation neural network algorithm for data compression and data storage. Data compression or establishing model ten coding is the most basic idea of traditional data compression. The traditionally designed ideas are mainly based on reducing the redundancy in the information and focus on the coding design, and its compression ratio has been hovering around dozens of percent. After the traditional coding compression of information, it is difficult to further compress by similar methods. In order to solve the above problems, the information that takes up less signal space can be used to represent the information that takes up more signal space to realize data compression. This new design idea of data compression breaks through the traditional limitation of relying only on coding to reduce data redundancy and achieves a higher compression ratio. At the same time, the information after such compression can be repeatedly compressed, and it has a very good performance. This is the basic idea of the combination of neural network and data compression introduced in this paper. According to the theory of multiobjective function optimization, this paper puts forward the theoretical model of multiobjective optimization neural network and studies a multiobjective data compression method based on neural network. According to the change of data characteristics, this method automatically adjusts the structural parameters (connection weight and bias value) of neural network to obtain the largest amount of data compression at the cost of small information loss. This method has the characteristics of strong adaptability, parallel processing, knowledge distributed storage, and anti-interference. Experimental results show that, compared with other methods, the proposed method has significant advantages in performance index, compression time and compression effect, high efficiency. and high-quality robustness. [ABSTRACT FROM AUTHOR]

By introducing wireless interfaces in conventional wired routers or hubs, wireless network-on-chip (WiNoC) is proposed to relieve congestion pressure from high volume inter-subnet data transmission. Generally, processing elements on chip receive input data and return feedback through network interface, and data transmission function in Network-on-Chip (NoC) is completed by routers. Hubs equipped with wireless interface are fixed to certain wired routers. While wireless channels may not be fully utilized due to unbalanced workload and constant hub-router connection, e.g., certain nodes processing excess inter-subnet data traffic are far away from hubs. In this paper, we proposed a workload-aware WiNoC design with intelligent reconfigurable wireless interface to improve wireless resources utilization and mitigate congestion. Through multidimensional analysis of traffic flow, a 4-layer neural network is trained offline and applied to analyze workload in each tile, and return three most potential tiles for wireless interface reconfiguration to fully utilize wireless channel and lowing latency. We also implement a historical traffic information-based reconfigurable scheme for comparation. Evaluation results show that in an 8 × 8 hybrid mesh topology, the proposed scheme can achieve 10%–16% reduction in network latency and 5%–11% increment in network throughput compared with fixed-link hub-node connection scheme under several mixed traffic patterns. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth study and analysis of information security protocols for industrial Ethernet using wireless sensor networks. The optimal number of cluster heads for nonuniform subclustering is derived based on the sensor energy consumption model, and then, the EEUC contention radius formula is optimized to select candidate cluster heads with random values and energy as weights. A multihop approach based on the shortest offset is also proposed for intercluster information transmission. Experimental results show that the EEUC-based improved cluster routing protocol proposed in this paper balances the node energy consumption and extends the network lifetime. In response to the problem that the coarsened hop value and average hop distance of the DV-Hop localization algorithm cannot reflect the network topology, the improved DV-Hop algorithm based on multicommunication radius and hop distance correction is proposed. Simulation experiments show that the improved algorithm based on multiple communication radius and hop count correction can significantly reduce the localization error and improve the accuracy of the algorithm. Aiming at the shortcomings of MRP with excessive risk concentration and transmission medium limitation, this paper proposes a fast self-healing mechanism of industrial Ethernet with a multiexpert strategy. The PCP-AP common platform architecture for openSAFETY sites is designed on the base sleeve of the implementation of the industrial Ethernet protocol Ethernet POWERLINK; the main communication part of POWERLINK is implemented through an FPGA hardware solution, and the openSAFETY site is implemented using AM335X high-performance processor to implement openSAFETY security application functions. Finally, the article conducts field tests on the wireless signal information transmission, WSN data transmission, network connection, and power supply system in the system and compares and analyzes the data collected by the system with the monitoring data of the national control site. The data obtained by the system has real reliability. The communication module used is inexpensive, lightweight, and easy to operate. It can realize the collection of multiple pollution sources, and compared with traditional monitoring equipment, it avoids the difficulties of complicated wiring, difficult positioning of pollution sources, and restricted monitoring areas and largely reduces the investment in human and material resources. [ABSTRACT FROM AUTHOR]

With the advent of the era of big data and mobile Internet, the traditional teaching model of colleges and universities has been hit unprecedentedly. In the current big data and artificial intelligence network environment, new teaching concepts, characteristics, and model applications should be analyzed, and an education model based on artificial intelligence adaptive control and negative feedback adjustment mechanisms under the big data environment should be explored. The study of this model can provide practical experience and reference value for the application, popularization, and innovation of teaching information technology in the future. Combining the characteristics of big data games, this paper proposes a college student education model based on discrete dynamic model big data game. The scores of college students represent comprehensive information such as their qualifications to provide big data university education, the credit of historical records, and the degree of reliable data transmission. Based on the general model of the adaptive learning system, we have perfected the functions of each module in the overall structure of the domain-based special subject system and designed the overall workflow of the system. Computerized evaluation is introduced into the learner module, and an adaptive evaluation system structure based on cognitive diagnosis theory is designed to achieve a personalized topic selection model for different learners and enrich learners' experience through more detailed and specialized evaluation results. The model lays the foundation for adaptive course path recommendation. This paper proposes a discrete real-time linear dynamic logic that can express discrete real-time characteristics and all regular characteristics. It can easily describe the behavior of some complex real-time systems. Experiments show that the discrete dynamic model big data game efficiency is improved by 35.71%, which can better optimize the education model of college students. In addition, it can be concluded that the research on the effectiveness of college student education in the era of big data not only determines the safety of the ideological field of colleges and universities but also affects the thinking orientation of college students. [ABSTRACT FROM AUTHOR]

In order to solve the problems of many lines, troublesome movement and redundant management of traditional electrical parameter monitoring system, a design and implementation of electrical parameter monitoring system based on ZigBee wireless communication is proposed. Taking the monitor as an example, this paper briefly introduces the application status of the monitor monitoring system and electrical safety detection. According to the comparison of wireless communication technology and the analysis of actual demand, this paper expounds the advantages of ZigBee wireless technology. Based on the combination of received signal strength indication (RSSI) ranging algorithm and trilateral positioning algorithm, the wireless positioning of mobile targets is realized. Then, the sparse correlation matrix of signal attenuation coefficient between base stations is established in the upper computer to optimize the positioning by using the look-up table method. The relevant test results show that through the serial port test software 2000 times of data transmission and reception, 1866 times of communication are successful, and the success rate is 93.3%, which basically meets the requirements of data transmission stability; After data transmission time detection, it takes about 1.4 seconds to send data from the monitor to the client for reception. The client sends the module query command, and the time when the command reaches the monitor is 1.6 seconds. The data transmission speed can basically meet the requirements of real-time monitoring. The design and implementation of the monitoring system can not only help to reduce the workload of medical staff in hospital nurse stations and improve their work efficiency, but also provide the possibility of practical significance for developing into an application tool for patient family members or personal health management in the future. [ABSTRACT FROM AUTHOR]

In this paper, we consider the Vennia algorithm to conduct in-depth research and analysis on the traceability of dual-chain blockchain agricultural products' E-commerce information. This paper adds a collaborative verification module to the traceability system and carries out a detailed design of information storage, traceability consensus algorithm, and smart contract for agricultural products according to the characteristics of the agricultural products supply chain, among which the collaborative verification module adopts dynamic data storage technology; the ConsiderVinia consensus algorithm is improved by introducing the way of integral penalty mechanism to ensure the block data validity. After a comparative study of the features and differences of the three major blockchain technology platforms, this paper selects the super ledger to implement the agricultural traceability system based on blockchain technology, introduces the partitioning and credit mechanism into the ConsiderVinia algorithm, and elaborates the improvement process of the algorithm. The improved algorithm reduces the malicious behavior of nodes and maintains the system security through a credit mechanism while maintaining the consistency of blockchain. In the event of a transaction dispute, the third-party platform will determine the party at fault based on the transaction records and other evidence and make corresponding punishments and compensations. The experiment proves that the algorithm proposed in this paper can reduce the amount of network data transmission in the process of node consensus, which is better than the ConsiderVinia algorithm in terms of both throughput and latency, improves the consensus efficiency, and alleviates the communication bottleneck caused by the increase of users in blockchain applications, and the solution of applying the blockchain technology to the agricultural products traceability system is practical and feasible. The blockchain-based agricultural products information traceability system solves the problems of information asymmetry, difficult sharing, easy tampering, and storage centralization in the traditional IoT-based agricultural products traceability system and truly realizes the credible and reliable traceability of the whole chain of agricultural products information. The research content and results of this paper have certain theoretical and practical values. [ABSTRACT FROM AUTHOR]

To provide a basic quantitative mathematical model for data analysis, decision-making support, and application of information systems oriented to emergency research, this paper established an information transmission response model for school students under such system mathematically based on actual school information transmission data during COVID-19 prevention. This paper proposes an emergency information management method—a two-step emergency information management method. It can be referenced for promotion of the development of IT-based school management, enhancement of IT application in school emergency information management, and improvement of the speed and accuracy of information transmission. [ABSTRACT FROM AUTHOR]

In this paper, the reliability of data transmission in social networks is thoroughly studied and analyzed using wireless sensor network topology technology. This paper, based on the introduction of sensor network reliability analysis-related technology, combined with the characteristics, and needs of the sensor network itself, focuses on the study of the reliability analysis of the sensor network under the state of perturbation scheme. Based on the idea of making full use of data changes to respond to the sensor state, this paper takes the actual monitoring data of the wireless sensor network as the research object, selects the temporal correlation and spatial correlation of the measured environmental data as the reliability index by extracting the features of the wireless sensor network data, and proposes the Evidential reasoning rule- (ER-) based wireless sensor network data reliability assessment model based on Evidential reasoning rule (ER) is proposed. The data are mined, analyzed, and quantified from the perspective of content popularity, and the interest indicators of nodes on data under content popularity are analyzed to derive stable interest quantification values. Combined with the network properties, i.e., node autoassembly community, we analyze the data dissemination characteristics of social networks in wireless sensor network topology environment and derive the upper and lower bounds of data transmission capacity under node interest-driven and its variation on network performance. Social relationships among nodes affected by social attributes are considered; in turn, the data forwarding behavior of nodes is modeled using data transmission probability and data reception probability; finally, the data forwarding process is analyzed and a closed expression for the average end-to-end transmission capacity is derived in turn. [ABSTRACT FROM AUTHOR]

The digital multimedia network data traffic is huge, and many end devices are applied to the digital multimedia network; therefore, the digital media network communication delay transmission must be analysed in order to improve the performance of the digital multimedia network communication transmission. Due to the presence of a large number of data packets in the communication network used, some random delays in data can occur during use. Conventional data transmission methods rely solely on extended data storage capacity to achieve this, making it difficult to achieve intelligent scheduling, resulting in delays and optimized performance degradation during communication data transmission. The aim of this paper is to enhance the communication quality of digital multimedia networks by developing an algorithmic model that rapidly mitigates communication delays. The proposed approach employs a delay cancellation algorithm in a network predictive control system. Simulation techniques are utilized to simulate and compensate for delays in multimedia communication networks. The efficacy of the network control strategy is demonstrated through simulation tests on a large-scale multimedia network communication system. The research findings indicate that the network control prediction model and elimination algorithm can substantially reduce the packet loss rate and quickly eliminate communication delays in digital multimedia networks. [ABSTRACT FROM AUTHOR]

Leach (low energy adaptive clustering hierarchy) algorithm is a self-clustering topology algorithm. Its execution process is cyclical. Each cycle is divided into two phases: cluster building phase and stable data communication phase. In the stage of cluster building, the adjacent nodes cluster dynamically and randomly generate cluster heads. In the data communication phase, the nodes in the cluster send the data to the cluster head, and the cluster head performs data fusion and sends the results to the aggregation node. Because the cluster head needs to complete data fusion, communication with the convergence node and other works, the energy consumption is large. Leach algorithm can ensure that each node acts as cluster head with equal probability, so that the nodes in the network consume energy relatively evenly. The basic idea of Leach algorithm is to randomly select cluster head nodes in a circular way. It evenly distributes the energy load of the whole network to each sensor node in the network. It can reduce network energy consumption and improve network life cycle. Leach repeatedly performs cluster refactoring during its operation. This paper studies the parameter detection of wireless sensor network based on Leach algorithm on the on-chip embedded debugging system. Because the classical low-power adaptive clustering layered protocol (Leach) has the problem of energy imbalance and short node life cycle, this paper uses embedded debugging technology based on Leach algorithm and the residual energy and position of nodes in wireless sensor networks were tested for research. This Leach algorithm uses the concept of wheel. Each round consists of two phases: initialization and stabilization. In the initialization stage, each node generates a random number between 0 and 1. If the random number generated by a node is less than the set threshold T (n), the node publishes a message that it is a cluster head. Through the research on the parameter detection, the simulation results show that the research in this paper has good feasibility and rationality. [ABSTRACT FROM AUTHOR]

For the severe impact of limited energy and network attacks caused by open transmission channels on data transmission, this paper presents a low-power and secure multihop routing mechanism based on the Markov state transition theory. The random selection of transmission paths enables the network to resist typical attacks such as interference and interception, thus ensuring the security of data transmission. Meanwhile, the proposed algorithm can reduce the overall energy consumption of the network and balance the load according to the residual energy of each path. Simulation results prove that the routing mechanism proposed in this paper can improve the energy efficiency and the security of the wireless ad hoc network. [ABSTRACT FROM AUTHOR]

The United Nations defined tenable progress as a development that responds to the demands of the current without adjusting the capacity of further generations to fulfil their own requirements; this is a fundamental idea in this article. This study recognizes three aspects, financial, social, and environmental sustainability, although its emphasis is on the latter. An electronic copy is sometimes characterized a physical thing, a real counterpart, and the data, which indicates the presence of a connector and block for effective and efficient data transmission. This article offers a systematic literature review on the sustainability of designed technology-based systems. This article also introduces the major requirements which can be helpful in designing optimal design for sustainability of a digital double-form system. Many articles on DT have also been chosen since they referenced the studied SLRs and were deemed to be significant for the objectives of this study. Selected and analysed for papers revealed so many flaws and challenges: the boons of are not clear; DTs throughout the result the wheel of life of the DTs is not adequately surveyed; DTs can contribute to cost reduction or to support decision-making is unclear; Internet practice should be improved and better integrated Moreover, it has not been feasible from our study to locate a publication which solely discusses DTs in relation with situational sustainability. [ABSTRACT FROM AUTHOR]

This paper studies a semiconductor wireless sensor system, which is composed of a semiconductor wireless sensor sampling circuit, gas-sensitive signal alarm and wireless transmitting circuit, and wireless radio frequency signal receiving circuit. The system is suitable for wireless monitoring of hydrogen fluoride gas in chemical plants. The hydrogen fluoride gas sensor is designed, integrated, and classified according to the polarity and size of the sensor output signal. The signal processing circuit of the sensor output signal is made with an integrated design. This paper developed a simulation experimental system for the wireless monitoring network characteristics of toxic hydrogen fluoride gas and completed the monitoring system's sensor characteristic calibration and accuracy comparison simulation experiment, the communication distance test experiment of the communication system, and the research experiment on the influence of environmental humidity on the sensor characteristics of the monitoring system. In terms of software, the workflow of network nodes has been optimized. Since the structure of the wireless sensor network is not exactly the same in different application fields, the toxic gas monitoring system based on wireless sensor networks must focus on extending the network's life cycle. Without affecting the normal operation of the system, distributed compressed sensing can greatly extend the service life of the system. Therefore, this subject combines the compressed sensing technology developed in recent years with the air monitoring system for the processing of transmission data, in order to achieve the purpose of further reducing the energy consumption of the system. The simulation experiment demonstrated that the lmF neural network combined with gas sensor array technology can realize qualitative identification, quantitative analysis of single gas, and quantitative analysis of mixed combustible gas. The research work in this area also provides a new way to further combine the miniature hydrogen fluoride gas sensor unit with sensor technology, integrate the hydrogen fluoride gas sensor unit and the electronic tag, and expand the wireless application of the gas sensor. [ABSTRACT FROM AUTHOR]

In low-load wireless sensor networks, the power consumption of the node consists mainly of two parts: data transmission and node state switching. The lower node workload causes low energy consumption on data transmission, and the state switching energy of the node cannot be ignored. This paper proposes a one-shot time division multiple access (TMDA) scheduling with unlimited channels (SUC) on the assumption that the number of available channels is unlimited. SUC combines the receiver-based consecutive slot allocation with channel allocation, which minimises the number of node state switching and optimizes energy efficiency. Theoretical analysis demonstrates that the number of channels required by SUC does not exceed log 2 N + 1 , where N indicates the number of nodes. Seeing that the number of available wireless channels is limited in practice, the paper proposes the scheduling with limited channels (SLC) and uses a Lookahead Search mechanism to solve slot conflict. For the scalability of the algorithm, a distributed implementation based on the token change is proposed. The algorithm uses the depth-first-search (DFS) to pass the token to all nodes and terminates slot and channel assignment. The simulation results show our algorithm can reduce the energy consumption by minimizing the number of state switching and shorten the data aggregation time by reusing slots among nodes. [ABSTRACT FROM AUTHOR]

Considering the importance of energy in our lives and its impact on other critical infrastructures, this paper starts from the whole life cycle of big data and divides the security and privacy risk factors of energy big data into five stages: data collection, data transmission, data storage, data use, and data destruction. Integrating into the consideration of cloud environment, this paper fully analyzes the risk factors of each stage and establishes a risk assessment index system for the security and privacy of energy big data. According to the different degrees of risk impact, AHP method is used to give indexes weights, genetic algorithm is used to optimize the initial weights and thresholds of BP neural network, and then the optimized weights and thresholds are given to BP neural network, and the evaluation samples in the database are used to train it. Then, the trained model is used to evaluate a case to verify the applicability of the model. [ABSTRACT FROM AUTHOR]

With the advent of the era of big data, Internet of things technology and wireless communication technology have been in a state of rapid development. Opportunities and challenges in all walks of life are being subverted. Financial management, as the foundation of corporate governance, is important for improving economic efficiency and achieving sustainable business development which plays an important role. In order to realize the management and classification of financial big data, better identify the financial data of different enterprises, strengthen the safe storage of financial information, and provide early warning for the security issues involved, this article is based on the Internet of things and wireless communication networks. In the method part, this article introduces the framework of the Internet of things, Bluetooth, and infrared data transmission in wireless network communication and the principles of financial big data. The algorithm introduces a single-user MIMO system, free space propagation, and spectrum and energy efficiency. The analysis part analyzes the spectrum efficiency of different algorithms, social utility, average number of retransmissions, comprehensive scores of competitiveness in various fields of the Internet of things, and the significance of financial indicators. By comparing the data, it can be seen that the algorithm in this paper is superior to the two algorithms of IAN-CoMP and IA-CoMP. When the number of users is 100, the social utility of the algorithm in this paper is 4.45, while IAN-CoMP is 3.43 and IA-CoMP is 3.67. When the number of users increases to 700, the social utility of the algorithm in this paper is 28.34. The other two algorithms are, respectively, 24.45 and 25.99, and we know that the social utility of the algorithm in this paper is the best. Through comprehensive analysis, it is concluded that the financial big data model based on the Internet of things and wireless network communication in this paper can better realize data management and collection, so as to meet the needs of information developers. [ABSTRACT FROM AUTHOR]