Data Transmission Method Research Articles

A Compressed Sensing Measurement Matrix Construction Method Based on TDMA for Wireless Sensor Networks.

Compressed sensing theory has been widely used for data aggregation in WSNs due to its capability of containing much information but with light load of transmission. However, there still exist some issues yet to be solved. For instance, the measurement matrix is complex to construct, and it is difficult to implement in hardware and not suitable for WSNs with limited node energy. To solve this problem, a random measurement matrix construction method based on Time Division Multiple Access (TDMA) is proposed based on the sparse random measurement matrix combined with the data transmission method of the TDMA of nodes in the cluster. The reconstruction performance of the number of non-zero elements per column in this matrix construction method for different signals was compared and analyzed through extensive experiments. It is demonstrated that the proposed matrix can not only accurately reconstruct the original signal, but also reduce the construction complexity from to (), on the premise of achieving the same reconstruction effect as that of the sparse random measurement matrix. Moreover, the matrix construction method is further optimized by utilizing the correlation theory of nested matrices. A TDMA-based semi-random and semi-deterministic measurement matrix construction method is also proposed, which significantly reduces the construction complexity of the measurement matrix from to , and improves the construction efficiency of the measurement matrix. The findings in this work allow more flexible and efficient compressed sensing for data aggregation in WSNs.

Energy efficiency based lifetime improvement for wireless body area network

The efficient selection of cluster head nodes for the transmission of the data to the sink node is the major requirement of the wireless body area network. The present work deals with the efficient selection of the cluster head node and uniform rotation of the cluster head based on the four important parameters, i.e. residual energy of the node, mean value of the Euclidean distance, priority level based on data sensitivity, and device physical capability. The proposed energy-efficient Bayesian clustering algorithm uses naïve Bayesian approach for the appropriate selection of the cluster head node. The selected cluster head node collects the data from the sensor nodes in each round. The collected data is first aggregated and then transmitted to the base station. In the steady-state phase, the proposed algorithm follows energy-analysed-TDMA based energy-efficient data transmission method which further reduces the energy consumption as compared to the standard LEACH protocol. The performance of the proposed protocol is compared to the existing protocol on the MATLAB simulator. The proposed scheme increases the overall lifetime of the network by approximately 1.5 times and also reduces the average energy consumption of the network.

MR-Pareto: A Multiattribute Opportunistic Routing Method Based on Pareto Optimal Solution for Mobile Crowdsensing

Mobile crowdsensing (MCS) is a new perception mode for solving large-scale mobile sensing tasks. Traditional data transmission methods are inapplicable, as the MCS is affected by coverage, user preference, and network access cost. Opportunistic network data transmission schemes in MCS have recently witnessed a surge of research efforts due to their ability of high delivery and low consumption. However, existing works only focus on the impact of the geographical location of nodes on user needs or the interaction between social information and data, which do not take into account the temporal and spatial characteristics of nodes. To address these issues, this paper proposes a multiattribute routing method based on Pareto optimal (MR-Pareto) solution to construct a balance between the energy consumption and resource constraints of nodes in transmission protocols. First, the attribute relationship between nodes is analyzed, which was aimed at selecting the nodes within a contact time threshold. Then, based on a nondominated sorting approach, we achieve a Pareto optimal set of candidate nodes. Finally, the relay nodes for forwarding messages are determined by comparing the cache size and the remaining energy. The experimental results demonstrate that our proposed method has low network overhead, low packet loss, and high message delivery rate, compared to epidemic and prophet routing strategies.

Using Zero-Knowledge Proof for Secure Data Transmission on Distributed Network

Data security plays a major role in computer network. Because it helps to transmit data in secure way over the Internet. So we need to use strong security method for secure data transaction. Cryptography is a security tool which helps to transmit information from one place to another place over computer network. Cryptography follows encryption and decryption methods for data transmission. Cryptographic technique is completely based on key generation because it needs keys to transmit data between users. However cryptography works well in secure data transmission but it needs keys to provide security for data. In cryptography generation of keys taking more time than transmission of data. So in this paper we discuss about Zero-Knowledge Proof (ZKP) which is also based on cryptographic technique. ZKP is also useful in secure data transmission without sharing key values between users. This paper tells about overview of ZKP and how it is useful in data transmission.

Sensor-Integrated Tool for Self-Optimizing Single-Lip Deep Hole Drilling

Single-lip deep-hole drilling (SLD) is characterized by high surface quality and compressive residual stress in the subsurface of the drill hole. These properties depend significantly on the thermo-mechanical conditions in the machining process. The required subsurface properties can be adjusted in-process via process monitoring and control when the thermo-mechanical conditions are maintained in the optimum range. Herein, a sensor-integrated SLD tool is introduced, which allows the temperatures near the cutting zone to be measured and the vibrations occurring directly at the drill head to be recorded. A microcontroller-based wireless measurement data transmission method is presented.

Physically-secured high-fidelity free-space optical data transmission through scattering media using dynamic scaling factors.

In this paper, we propose a method of physically-secured high-fidelity free-space optical data transmission through scattering media using physically- and dynamically-generated scaling factors. Optical channel characteristics are explored, and scaling factors are physically and dynamically generated to serve as security keys in the developed free-space optical data transmission system. The generated dynamic scaling factors provide a security layer for free-space optical data transmission. To the best of our knowledge, it is the first time to physically and dynamically generate scaling factors in free-space optical data transmission system to realize data encryption. The scaling factors existing in free-space optical data transmission channel are physically and dynamically controlled by using two optical devices, i.e., variable beam attenuator (VBA) and amplitude-only spatial light modulator (SLM). Nonlinear and dynamic variation of scaling factors is realized in different free-space wave propagation environments. It is experimentally demonstrated that high security can be guaranteed in the developed physically-secured high-fidelity free-space optical data transmission system, since one random scaling factor is physically and dynamically generated for the transmission of each signal pixel value. In addition, the proposed physically-secured free-space optical data transmission scheme is robust to noise and scattering, and high-fidelity signals are retrieved at the receiving end. The proposed method could open up a new research perspective for the secured free-space optical data transmission.

METHOD OF CONSTRUCTION MATRIX CARDANO’S GRIDS FOR COMPRESSION OF INFORMATION

Due to the rapid development of computer technology and the information field, issues related to information security are becoming increasingly important. Knowledge of information security tools is required for the effective organization of the process of transmission and storage of classified information. The main means of information protection such as encryption, compression and covert transmission of information are present in the article . Information security techniques, including cryptographic data protection systems, play an important role in today’s information-filled world. The means of cryptographic data protection, in particular encryption using the Cardano’s encryption grid are list and analyze in the article. Existing mechanisms for reliable storage and transmission of information today do not provide adequate protection. The problem of lack of effective means of information protection is explained by rapid and systematic changes in information technology. The article is devoted to the method of constructing Cardano matrix gratings for compression and hidden data transmission. The developed method is based on the integrated use of existing approaches and methods of information protection. In particular, on the classic cipher of the route permutation – Cardano’s encryption grid. Cardano matrix lattice is based on frequency analysis of English text. The algorithm of frequency analysis of the text and its results are presented in the article. As a result of performing operations of matrix cryptographic transformation of numbers – the rules of distribution of symbols on a lattice are received. In the future, the proposed method will build new algorithms for encrypting information by analogy with the encryption lattice. Also, the created algorithmic models are the basis for building a method of compression and covert data transmission. The methods of information protection considered in the article – encryption, compression and covert transmission, allow us to draw the general conclusion that only their integrated use will ensure an adequate level of protection.

Channel assignment and users mobility influence on primary users QoE in Cognitive Radio Network

Over the recent years, the fifth-generation (5G) of mobile communications, as projected for future requirements, has brought significant changes to our lives. This proliferation, in turn, has led to increasing demands in wireless technologies and developing expectations of wireless applications. As an immediate result, the current spectrum allocation, static allocation policy, has increased the resource demands. Subsequently, Cognitive Radio Network (CRN) has provisioned to resolve spectrum shortages in wireless networks. Additionally, due to a noticeable reduction in signal strength in cell-edges, Coordinated Multi-Point Joint Transmission (CoMP JT) has targeted the performance of cell-edge users. This paper proposes an adaptive data transmission method, namely Adaptive CoMP JT (ACJT), for mobile users in an interweave CRN under 5G technology. We have endeavored to maintain a satisfactory level of Quality of Experience (QoE) for Primary Users (PUs) in the device-to-device (D2D) communications. The ACJT is utilized to meet users’ requirements located in the boundary of cells. Moreover, resources are assigned to PUs based on services with distinct requirements. The evaluations of the proposed method on various circumstances confirm that the ACJT achieves affordable performance in terms of enhancing PUs’ QoE and energy consumption.

High speed data transmission method of substation intelligent auxiliary monitoring system

In order to better ensure the effective operation of substation intelligent auxiliary monitoring system, aiming at the problems of slow data transmission speed and poor data processing security of current monitoring system, a high-speed data transmission method of the substation intelligent auxiliary monitoring system is proposed. By constructing the data processing platform of substation intelligent auxiliary monitoring system, the data transmission algorithm of auxiliary monitoring system is optimized, reasonably select the optimal path of data transmission and conduct security encryption processing, so as to improve the high-speed data transmission efficiency of substation intelligent auxiliary monitoring system. Finally, the experiment shows that the high-speed data transmission method of the substation intelligent auxiliary monitoring system has higher practicability in the process of practical application and fully meets the research requirements.

A Data Transmission Method with Spectral Switches via Electroabsorption

In the past, the waveguide electroabsorption effect has generally been used as an intensity modulator for quasi-monochromatic light, such as lasers. Here, we study how this effect affects polychromatic light spectra. We find that for light with a Gaussian distribution spectrum, the spectral peak shift (red shift or blue shift) can be controlled by the magnitude of the applied voltage, as long as the center wavelength and the spectral band are properly selected. This result can be used as a data transmission scheme at the integrated chip level or in free space. It may offer a good option for some other light sources, such as low-cost LED or ELED (edge emitting LED), with wider spectral bandwidths.

Feature-driven 3D range geometry compression via spatially-aware depth encoding

The ever-growing variety of capture methods and applications for 3D range geometry continually increases the need for efficient methods of data storage and transmission. Compression techniques address this need by offering reduced file sizes while maintaining the precision needed for a particular application. Several such compression methods use phase-shifting principles to encode the 3D data into a 2D RGB image. In some applications, such as telepresence, high precision may only be required in a particular region within a scan. This paper proposes a feature-driven compression method that provides a way to encode regions of interest at higher precision while encoding the remaining data at lower precision to reduce file sizes. This method supports both lossless and lossy compression, enabling even greater file size savings and a wider range of applications. In the case of a depth scan of a bust, an extracted bounding box of the face was used to create an encoding distribution such that the facial region was encoded at higher precisions. When using JPEG 80, the global RMS reconstruction accuracy of this novel encoding was 99.72%; however, in the region of interest, the accuracy was 99.88%. This feature-driven encoding achieved a 26% reduction in compressed file size compared to a fixed, high precision encoding.

Deep Q-Learning-Based Neural Network with Privacy Preservation Method for Secure Data Transmission in Internet of Things (IoT) Healthcare Application

The healthcare industry is being transformed by the Internet of Things (IoT), as it provides wide connectivity among physicians, medical devices, clinical and nursing staff, and patients to simplify the task of real-time monitoring. As the network is vast and heterogeneous, opportunities and challenges are presented in gathering and sharing information. Focusing on patient information such as health status, medical devices used by such patients must be protected to ensure safety and privacy. Healthcare information is confidentially shared among experts for analyzing healthcare and to provide treatment on time for patients. Cryptographic and biometric systems are widely used, including deep-learning (DL) techniques to authenticate and detect anomalies, andprovide security for medical systems. As sensors in the network are energy-restricted devices, security and efficiency must be balanced, which is the most important concept to be considered while deploying a security system based on deep-learning approaches. Hence, in this work, an innovative framework, the deep Q-learning-based neural network with privacy preservation method (DQ-NNPP), was designed to protect data transmission from external threats with less encryption and decryption time. This method is used to process patient data, which reduces network traffic. This process also reduces the cost and error of communication. Comparatively, the proposed model outperformed some standard approaches, such as thesecure and anonymous biometric based user authentication scheme (SAB-UAS), MSCryptoNet, and privacy-preserving disease prediction (PPDP). Specifically, the proposed method achieved accuracy of 93.74%, sensitivity of 92%, specificity of 92.1%, communication overhead of 67.08%, 58.72 ms encryption time, and 62.72 ms decryption time.

Использование DNS-туннелирования для передачи вредоносного программного обеспечения

Purpose of the article: to develop a way to increase the level of protection of an information system from an attack using DNS tunneling. Method: using entropy to identify domains and subdomains used when transferring data through a DNS tunnel. The result: a method of data transmission through the DNS protocol bypassing the information security tools is considered. A malicious file was transferred using DNS tunneling, and an analysis was made of the operation of information protection tools during transmission. Information security tools do not detect the transfer of a malicious file via the DNS protocol, but they do if it is transferred in clear text. The concept of information entropy, its role in data processing is given. By calculating the entropy for domain names, the domain used in the transmission of a malicious file through the DNS tunnel was identified. It is concluded that entropy can be used not only to detect data transfer through the DNS tunnel, but also to detect the activity of malicious software that uses random domain and subdomain names in its work. The scientific novelty lies in the fact that malicious activity is detected without using the knowledge base. There is no need to signature check each DNS request, it is enough to calculate the entropy to detect an attack.

Recommendation system for managing a Smart Home

Based on the results of the analysis of the history of development and the final stage of the smart home concept and data transmission methods, it can be concluded that the history of development has gone through a long and full of updates, finding the most optimal concept of operation. The chosen topic is currently particularly relevant, as the IoT concept can significantly improve many areas of our lives and help us create more convenient, smart and safe homes. The term “smart home” was first coined by the American Association of Homebuilders in 1984. With the invention of microcontrollers, the cost of electrical appliances was falling rapidly. The same organization noted that such a home is different from the usual one in its ability to ensure productive and efficient use of the working and living environment. Today, technology allows you to assemble home automation in a componentized manner: selecting only those smart home functions that the user really needs. Nowadays, the latest room management technologies appear every day. Even things that were previously seen only as beautiful interior items can now perform a number of multimedia or household functions. In the practical part, we evaluated the main characteristics of a software product designed to manage a smart home using cloud computing. Below is an analysis of various software implementation options in order to select the optimal one, taking into account both economic factors and product characteristics that affect performance and compatibility with hardware. For this purpose, we used a functional and cost analysis tool. A functional and cost analysis of the software was conducted. The use of remote control technology was investigated and modeled. The work included options for implementing significant economic alternatives. The comparison was based on labor, electricity, and capital costs. After the functional and cost analysis, the software is in development. After completing all the surface analyzes, it was found that the options for the server and client side programming languages are Javascript, and the use of the Amazon cloud platform and its virtual server is the most efficient goal.

Privacy Preserving Reliable Data Transmission in Cluster Based Vehicular Adhoc Networks

VANETs are a subclass of mobile ad hoc networks (MANETs) that enable efficient data transmission between vehicles and other vehicles, road side units (RSUs), and infrastructure. The purpose of VANET is to enhance security, road traffic management, and traveler services. Due to the nature of real-time issues such as reliability and privacy, messages transmitted via the VANET must be secret and confidential. As a result, this study provides a method for privacy-preserving reliable data transmission in a cluster-based VANET employing Fog Computing (PPRDA-FC). The PPRDA-FC technique suggested here seeks to ensure reliable message transmission by utilising FC and an optimal set of cluster heads (CH). The proposed PPRDA-FC technique utilizes a moth flame optimization with levy flight based clustering (MFO-LFC) process to identify and form clusters from a suitable set of CHs. The CHs are responsible for monitoring each vehicle in their respective clusters. Simultaneously, the CHs provide the most efficient and secure pathways for message transmission. Finally, a deep neural network (DNN) is used as a classification tool to distinguish between attacker-controlled and real-world automobiles. To evaluate the suggested PPRDA-FC technique’s increased performance, a series of simulations were run and the results analyzed using a variety of metrics. The acquired experimental findings illustrate the suggested PPRDA-FC technique’s superiority to recent state-of-the-art procedures.

АНАЛІЗ МЕТОДІВ СТЕГАНОГРАФІЧНОЇ ПЕРЕДАЧІ ДАНИХ В ІНФОРМАЦІЙНИХ ТЕЛЕКОМУНІКАЦІЙНИХ МЕРЕЖАХ

Recently, network steganography methods based on the use of structural properties of OSI (Open System Interconnection) protocols have been widely used to mask the fact of information transmission in information and telecommunication networks. This allows to covertly transmit important data based on background traffic, without significantly reducing the data rate in the base (open) channel. With the correct choice of properties (groups of properties) of the protocol (protocols) of the OSI model, the methods of network steganography do not allow the steganoanalyst to detect the fact of hidden data transmission. In network steganography, the process of detecting hidden data transmission is based on the analysis of the protocol characteristics of the used protocols of the OSI model for compliance with standards. When using protocols of channel and network levels of the OSI model, as a technological basis for organizing a hidden data transmission channel, concealment is carried out by placing data, the fact of transmission of which must be hidden, in the visible fields of the headers of the corresponding protocols, i.e. in open form. Due to the fact that the IP encryption technology covers only the payload of network layer protocols, it is advisable to use transport layer protocols of the OSI model. At this level, the TCP protocol is the most common, and it is standardized and used by opposing parties, including the military. The paper analyzes the current state of hidden data transmission in public information telecommunications networks and methods of steganographic data transmission in information and telecommunications networks. The network protocols used in information telecommunication networks were also analyzed, the concept of "network steganography" was revealed, the main task of which is to hide the very fact of message transmission in data transmission channels.

Applicability and Performance of Standard Compression Methods for Efficient Data Transmission and Storage in Radar Networks

Modern sensor networks—those used for autonomous driving, security systems, human motion tracking, or smart city/smart factory applications—are shifting to a more centralized data processing approach to enable efficient multimodal sensor fusion for optimal environment perception in complex dynamic situations. Among lidars and cameras, radars are typical for these applications, but they generate huge amounts of data, which cannot be transmitted or stored effectively in current setups. Consequently, manufacturers usually have to process the data “on sensor.” This results in transmitting only a few extracted features as point clouds or object lists to a central processing unit, which usually causes a significant loss of information. With this approach, advanced processing—such as enhancement of resolution by coherent combination of sensors or ghost target removal with advanced algorithms—is hardly possible. To overcome this, we suggest an alternative method by using signal-based compression with defined losses. The following topology will be proposed: the sensors encode raw data without prior radar-specific processing and after transmission, a central unit decodes and processes the radar data, thus benefiting from its more powerful heterogeneous processing system. We will analyze lossless compression algorithms with rate savings of about 30% to 65%, but the focus is on lossy compression algorithms that incorporate higher compression ratios by allowing negligible errors. It is shown that state-of-the-art multimedia compression algorithms can obtain rate savings of 99%, and radar specific algorithms can add a 50-fold gain on top, reaching 99.98%. To assess the distortions of compressed data, we then present different radar-specific evaluation metrics.

Model Research of Visual Report Components

The existing mainstream report system in the market can meet the daily report generation. However, it is difficult to maintain the system later due to the poor satisfaction of its report personalization and the high front-end and backend dependencies. In order to solve the above problems, this paper studies the development idea of Vue components. The technical characteristics of Vue and the source code of the Axios framework are analyzed, and a visual component model is proposed in combination with the application scenarios and development process. The data transmission method of the components is clarified in the actual application layer, which enhances the control of the page in the front-end component development process. The ability to convert complex reports into the construction of visual components and the dynamic data components to obtain data effectively improves the reporting system's development speed and meets the needs of personalized reports.

A Stable Data Transmission Method of Industrial Internet of Things Communication Based on Bat Algorithm

A Stable Data Transmission Method of Industrial Internet of Things Communication Based on Bat Algorithm

A stable data transmission method of industrial internet of things communication based on bat algorithm

A stable data transmission method of industrial internet of things communication based on bat algorithm