Data Transmission In Wireless Networks Research Articles

Prediction and evaluation of wireless network data transmission security risk based on machine learning

Prediction and evaluation of wireless network data transmission security risk based on machine learning

Evolution of Energy Efficient Wireless Sensor Network: A Survey on Energy and Clustering Issues

In different fields of human endeavor, wireless sensor networks (WSNs) are being developed to collect, aggregate, fuse, and send data collected by a wide range of sensors in real-time. When developing a wireless network's data transmission routing system, energy consumption is among the most essential components. Designing an energy-efficient (WSN) routing framework is challenging. Several energyefficient routing algorithms exist for effectively transferring data packets between cluster members (CM) and cluster heads (CH). Some suggest the change of state of the nodes that made up the network from active to sleep in the event where the nodes are not sensing of sending data as a method of energy optimisation while others reduce the distance between the nodes because the distance between nodes is directly proportional to the amount of energy use during data transmission. Whatever the method may be, achieving reduced energy consumption in a WSN environment is an enormous task due to the need for both long network life and network efficiency. This paper reviews some research and energy saving techniques that had been carried out on WSN over a period of time.

WiMAX Network Optimization Using Frame Period with Channel Allocation Techniques

Internet connectivity in WiMAX networks, along with various applications, is increasing rapidly, so the connectivity of internet and data transfer speed are always challenge for effective data transmission in wireless networks. Several factors affect the performance of networks. One important factor is to choose a suitable frame period for effective data transmissions. The performance of different frame period with round-robin and strict priority are evaluated in this work. A frame period in round robin performs better than a strict priority in terms of throughput, but a strict priority performs better in terms of drop rates is observed. This paper also demonstrates that an effective frame period, when combined with a proper bandwidth allocation algorithm, yields better results. This work gives the analysis that round robin performs 83.8847% better while strict priority performs 86.0020% better than the earliest deadline first algorithms for 10 subscriber stations in terms of throughput. This work is helpful to researchers and industrialists for actual implementations in WiMAX networks.

Reconstruction of Communication Signal in Wireless Networks Based on Perturbation Compression Perception

<p>With the maturity and development of new generation communication technology, the demand for wireless network communication quality is getting higher and higher. However, the existing wireless network data transmission models are greatly affected by the signal quality in the data transmission process, which seriously affects the quality of data transmission. To address the problem of signal perturbation affecting communication quality in wireless network communication, this study designs an improved perturbation compression reconstruction algorithm that can be used to process block-structured data based on the block sparse structure in the original signal, and constructs a single-user wireless network communication data transmission model based on this algorithm. The performance simulation test of the model shows that the MSE values of the model are lower than those of the conventional and perfect schemes used as comparisons under the same noise conditions and the transmitted compressed data length conditions. When the variance of Gaussian white noise is 0.125, the MSEs of the research design model, the conventional scheme and the perfect scheme are 0.031, 0.048, and 0.047, respectively. Experimental data show that the improved disturbance compressed sensing reconstruction algorithm can better reconstruct the compressed information and reduce the information loss caused by the disturbance in the compression process on the premise of removing the signal disturbance. This research result has reference significance for improving the signal quality of wireless network communication.</p> <p> </p>

Secured Wireless Network Based on a Novel Dual Integrated Neural Network Architecture

The development of the fifth generation (5G) and sixth generation (6G) wireless networks has gained wide spread importance in all aspects of life through the network due to their significantly higher speeds, extraordinarily low latency, and ubiquitous availability. Owing to the importance of their users, components, and services to our everyday lives, the network must secure all of these. With such a wide range of devices and service types being present in the 5G ecosystem, security issues are now much more prevalent. Security solutions, are not implemented, must already be envisioned in order to deal with a range of attacks on numerous services, cutting-edge technology, and more user information available over the network. This research proposes the dual integrated neural network (DINN) for secure data transmission in wireless networks. DINN comprises two neural networks based on sparse and dense dimensions. DINN is designed for any presence of deep learning-based attack in a physical security layer. DINN is evaluated considering the various machine learning attack such as basic_iterative_method attack, momentum_iterative_method attack, post_gradient_descent attack, and C&W attack; comparison is carried out on existing and DINN, considering attack success rate and MSE. Performance analysis suggests that DINN holds a higher level of security against the above attacks.

SOHCL-RDT: A self-organized hybrid cross-layer design for reliable data transmission in wireless network

In this paper, we propose “SOHCL-RDT” which stands for a self-organized hybrid cross-layer design for reliable data transmission in wireless network. The communication paradigm is changing and new approach related to machine learning or other optimization algorithms are being introduce rapidly. The TCP/IP or OSI model is not at all equipped to accommodate such a vast changes in its established protocol stacks. Considering this, we have proposed the hybrid cross layer design where the communication or transmission will be handle using two set of protocol stack. One set for the established classical network, and another using cross layer approach. Our design leverages the strengths of both the physical and MAC layers to optimize packet transmission and minimize energy consumption. An optimization algorithm based on gradient descent is also developed to adjust transmission parameters in real-time. The objective is to invoke the classical model only when it needed; it means until unless gradient descent is able to make classification regarding the node scheduling and achieve the acknowledgment, the TCP/IP protocol stack will be in deactivation. Using this method, we have performed our experiments mainly on two parameters named as packet delivery ratio (PDR), end-to-end delay (E2ED); because these are important aspect of reliability. In addition to that, the energy consumption of network is also compared with the existing algorithms. The results show that the proposed hybrid cross-layer design outperforms the existing algorithms. The performance gain can be attributed to the cross-layer approach and the use of the optimization algorithm. Overall, the proposed hybrid cross-layer design is a promising solution for reliable data transmission in wireless sensor networks, with the potential to improve network performance and prolong network lifetime by reducing energy consumption.

CLUSTER-BASED GRID COMPUTING ON WIRELESS NETWORK DATA TRANSMISSION WITH ROUTING ANALYSIS PROTOCOL AND DEEP LEARNING

Grid computing based on clusters has emerged as a promising strategy for improving the efficacy of wireless network data transmission. This study examines the incorporation of cluster-based grid computing, routing analysis protocols, and deep learning techniques to optimize data transmission in wireless networks. The proposed method utilizes clusters to distribute computing duties and enhance resource utilization, resulting in efficient data transmission. To further improve the routing process, a novel routing analysis protocol is introduced, which dynamically adapts to network conditions and chooses the most optimal routes. In addition, deep learning algorithms are used to analyze network data patterns, allowing for intelligent data routing and resource allocation decisions. Experiment results exhibit the efficacy of the proposed method, revealing substantial enhancements in network performance metrics such as throughput, latency, and energy consumption. This research contributes to the development of cluster-based grid computing and offers valuable insights for the design of efficient wireless network data transmission systems.

Selection of the Protocol for Receiving Data Transmission and Development of an Algorithm for Selecting The "Master" Processor Module for a Reconfigurable Real-Time Computer Network

Purpose of research. Computing networks of a plurality of processor modules have existed for a long time, however, with the development of wireless technologies, the possibility of high-quality and inexpensive implementation of the idea of real-time reconfigurable computing networks (RRTCN) has emerged. The purpose of this work is to select a wireless data transmission network for the RRTCN and create an algorithm for the dynamic selection of the "master" processor module.Methods. The research methods of the work are based on the definitions of the theory of sets and graphs. In particular, a grapho-theoretical approach to distribution is taken as a basis, supplemented by the introduction of a system of criteria for a reconfigurable real-time computing system based on a wireless data transmission protocol.Results. In this paper, the most suitable data transfer protocol for the local RCSRV is selected, a developed mathematical model of changing a real-time computing system built on a wireless protocol is presented, and an algorithm for selecting the processor module (PM) of the RCSRV "master" is developed. The novelty of the work is the use of the distance matrix for the mathematical description of the change in the RRTCN and its use to determine the PM of the "master" in the aircraft.Conclusion. The developed algorithm for choosing the PM of the "master" RRTCN and the mathematical model of changing the position of the PM in a real-time computer system built on a wireless protocol allows organizing the optimal choice of the PM of the "master" in a reconfigurable computing system. On the basis of the presented mathematical model, in the future, it is possible to create a full-fledged mathematical model of the RRTCN and an algorithm for placing tasks in it.

Research on Winter Wheat Growth Stages Recognition Based on Mobile Edge Computing

The application of deep learning (DL) technology to the identification of crop growth processes will become the trend of smart agriculture. However, using DL to identify wheat growth stages on mobile devices requires high battery energy consumption, significantly reducing the device’s operating time. However, implementing a DL framework on a remote server may result in low-quality service and delays in the wireless network. Thus, the DL method should be suitable for detecting wheat growth stages and implementable on mobile devices. A lightweight DL-based wheat growth stage detection model with low computational complexity and a computing time delay is proposed; aiming at the shortcomings of high energy consumption and a long computing time, a wheat growth period recognition model and dynamic migration algorithm based on deep reinforcement learning is proposed. The experimental results show that the proposed dynamic migration algorithm has 128.4% lower energy consumption and 121.2% higher efficiency than the local implementation at a wireless network data transmission rate of 0–8 MB/s.

Deep Neural Certificate less Hessian Heap Sign cryption for Secure Data Transmission in Wireless Network

Systematic and well grounded data transmission over wireless networks has been substance of uninterrupted research over the last few years. The paramount is scrutinizing the amount of security provisioning owing to the security challenges during transmission over wireless network. In fact, it is moderate to eavesdrop and alter data packets. Accessing the personal computer and public network possess the potentiality to apprehend the network traffic possibly compromising the privacy. Therefore for wireless applications, it is essential to ensure data integrity during data transmission. To efficiently address the above issues, a Deep Neural Certificate less Hessian Curve Heap Sign cryption (DNC-HCHS) method for secured data transmission in wireless network is proposed. Compared with the conventional, Certificate less Sign cryption DNC-HCHS method improves the data confidentiality and data integrity by generating smaller keys employing the Hessian Curve Heap function. Additionally with the assistance of the access point or the aggregator, the sensitivity of heaped sign crypted cipher text can improve the security of data transmission and reduce the message delivery time. Aimed at reducing the delay in data transmission, application of Certificate less Hessian Curve Heap Sign cryption in Deep Learning (i.e., Deep Neural Network) performs the overall process in a swift manner and performs a much better encryption. Simulation is performed to validate the viability and efficiency of the proposed method. The results show that the data confidentiality and data integrity rate are strongly improved, while the delay is minimized.

Generative Adversarial Networks for Secure Data Transmission in Wireless Network

In this paper, a communication model in cognitive radios is developed and uses machine learning to learn the dynamics of jamming attacks in cognitive radios. It is designed further to make their transmission decision that automatically adapts to the transmission dynamics to mitigate the launched jamming attacks. The generative adversarial learning neural network (GALNN) or generative dynamic neural network (GDNN) automatically learns with the synthesized training data (training) with a generator and discriminator type neural networks that encompass minimax game theory. The elimination of the jamming attack is carried out with the assistance of the defense strategies and with an increased detection rate in the generative adversarial network (GAN). The GDNN with game theory is designed to validate the channel condition with the cross entropy loss function and back-propagation algorithm, which improves the communication reliability in the network. The simulation is conducted in NS2.34 tool against several performance metrics to reduce the misdetection rate and false alarm rates. The results show that the GDNN obtains an increased rate of successful transmission by taking optimal actions to act as a defense mechanism to mislead the jammer, where the jammer makes high misclassification errors on transmission dynamics.

Autonomous detection of malevolent nodes using secure heterogeneous cluster protocol

Surfing of internet by the users has been more vital from the inception of the network. However, the number of users using the internet is increasing gradually. As a result, it has also become a serious threat to users who are using the internet because due to the false information and security threat by malicious users. In this context, it is vital to provide the trusted information to the users. In order to achieve the same, the Heterogeneous Cluster-Based Secure Protocol (HCBSP) can be used to detect the malicious nodes and thereby, to provide a secure path for data transmission. Initially, the nodes are deployed, then clusters are formed and subsequently, the data are transmitted between cluster and base. The HCBSP operates over the cluster for effective attack detection and secures the data transmission in wireless network. This performance is evaluated and compared with the existing methods. Here, the result shows that the HCBSP is the most effective platform in detecting the malicious nodes with high accuracy rate.

Physical (PHY) Layer Analysis of Data Transmission in MIMO Wireless Networks in Line- of-Sight (LoS) Environments

This research paper presents the Physical (PHY) layer analysis of multiple input multiple output (MIMO) systems in line-of-sight environments between a user equipment (UE) and a base station when an information data is transmitted. The data transmission in wireless networks often takes place in non-line-of-sight in urban environments and Line-of-Sight (LoS) in rural environments depending on the bandwidth, power constraints. Using MIMO technology, the data transmission takes place with increased number of transmit and receive antennas which results in reduced signal to noise ratio (SNR) requirement. In this research work, simulation for PHY layer metric of probability of error, mean square error (MSE) for data transmission in MIMO wireless networks is obtained Matrix Laboratory (MATLAB) for LoS environment which follows Rician distribution. Probability of error reduces to a significant extent when the Rician factor increases as the line-of-sight component prevails which also takes lesser power in the lower SNR limits. Further, in MIMO systems also the probability of error and MSE reduces in concatenation with single antenna terminals thereby exploring power control a significant possibility for implementation in massive MIMO and millimeter wave communication systems for 5G and 6G systems.

A New Fuzzy Controlled Antenna Network Proposal for Small Satellite Applications

This research contributes to small satellite system development based on electromagnetic modeling and an integrated meta-materials antenna networks design for multimedia transmission contents. It includes an adaptive nonsingular mode tracking control design for small satellites systems using fuzzy waveless antenna networks. By analyzing and modeling based on electromagnetic methods, propagation properties of guided waves from metallic structures with simple or complex forms charge partially or entirely by anisotropic materials such as metamaterials. We propose a system control rule to omit uncertainties, including the inevitable approximation errors resulting from the finite number of fuzzy signal power value basis functions in antenna networks. Moreover, both the stability and the tracking performance of the closed-loop robotic system are experimentally validated. The research lies within the scope of the improvement of speed, effectiveness, and precision of numerical methods applied to electro-magnetic modeling with complex structures, essentially rectangular metallic waveguides filled with isotropic or anisotropic metamaterials. Three axes of our research are presented: waveguides, filters, and antennas. The proposed controller does not require prior knowledge about the dynamics of the fuzzy system controller for antenna networks or the offline learning phase. In addition, this work contributes to solving the problem of non-visibility stations to ensure data transmission in wireless networks. The proposed solution maximizes inter-connection by using a fuzzy controlled antenna network, and the novelty guarantees non-limited interconnection in wireless networks compared to traditional methods.

Development of cyber-physical system security management process model

Cyber-physical systems (CPS) combine general-purpose information and telecommunication systems and industrial networks and devices (controllers), forming a heterogeneous hierarchical distributed information technology computing environment designed for control and monitoring of technological processes. FSCs are being actively implemented in the industrial, urban and household spheres, allowing for more efficient use of resources, as well as transferring management and feedback processes to a new level. CPS are formed as a result of the aggregation of several heterogeneous information and telecommunication systems, which makes them susceptible to the destructive factors of the digital environment – cyber attacks. The peculiarities of the construction and functioning of the CPS require a new approach to defining attack surfaces and modelling threats. This is due to the fact that the "traditional" goals of attackers - the availability, integrity and confidentiality of information processed in the system - are not the only ones. In addition, the value of the information itself can be extremely low. At the same time, control and feedback processes play a decisive role in a cyber-physical system. Their stability directly affects the ability of the FSC to perform target functions, as well as the physical safety of technological facilities, personnel and consumers. Depending on the degree of criticality of the technological processes of the real world, which are controlled by the cyber-physical system, the violation of these flows inside it can lead to serious consequences, such as large material damage or a threat to the life and health of people. The severity of the identified threats is confirmed by the constantly growing number of attacks on CPS and the consequences, including potential ones, to which these attacks lead. In addition, it should be noted that in the context of the rapid development and improvement of programmable control devices (Programmable Logic Controller (PLC)), making them more accessible in the mass market segment, as well as the proliferation of high-speed wireless data transmission networks, the concept of a smart home is gaining wider application. This approach implies the integration of PLCs that interact with each other and the control centre via multi-service broadband wireless networks into the domestic environment. Thus, the concept of a smart home is based on the implementation of FSCs in places of permanent residence of people with the transfer of automatic control functions of climatic equipment, lighting, household appliances, physical elements of protection against intrusions to them. At the same time, it is extremely important to ensure the information security of the CFS. To ensure the required level of their security, it is necessary to effectively solve the problems of managing the process of ensuring their information security. The article proposes an approach to the development of a model for the information security management process of a CFS operating in a smart home.

Convergence Bounds for Limited Processor Sharing Queue with Impatience for Analyzing Non-Stationary File Transfer in Wireless Network

The data transmission in wireless networks is usually analyzed under the assumption of non-stationary rates. Nevertheless, they strictly depend on the time of day, that is, the intensity of arrival and daily workload profiles confirm this fact. In this article, we consider the process of downloading a file within a single network segment and unsteady speeds—for arrivals, file sizes, and losses due to impatience. To simulate the scenario, a queuing system with elastic traffic with non-stationary intensity is used. Formulas are given for the main characteristics of the model: the probability of blocking a new user, the average number of users in service, and the queue. A method for calculating the boundaries of convergence of the model is proposed, which is based on the logarithmic norm of linear operators. The boundaries of the rate of convergence of the main limiting characteristics of the queue length process were also established. For clarity of the influence of the parameters, a numerical analysis was carried out and presented.

BEAM ANTENNA FOR CONTROLLING WIRELESS 5 GHZ DATA TRANSMISSION NETWORKS

Recently, there has been an intensive development of wireless data networks in the 2.4 and 5 GHz ranges, or Wi-Fi. The popularity of these networks is mainly due to the transmission of multimedia information. Existing standards and data protocols for these networks ensure their smooth and high-performance operation in «ideal conditions». In fact, in cities and densely populated centers with a significant amount of such equipment as well as lack of backup channels, there is radio frequency interference. These interferences are caused by the impact of one piece of equipment on another when it is impossible to adjust by switching to backup channels. Due to the interference, the data transmission speed is reduced, and in some complex cases, the data transmission is stopped completely. This negative phenomenon especially affects the 5 GHz range, in which the signal range is less than that for the 2 GHz range. To assess the quality of wireless data transmission networks, the following characteristics are monitored: the average emission frequency and the emission bandwidth. When these characteristics go beyond the standard values, there are interferences detected by the radio frequency monitoring bodies. Monitoring is carried out monthly throughout the year by specialized measuring systems, which include spectrum analyzers and antennas. Existing antennas have the following disadvantages: instability of the amplification gain, significant noise radiation, low reliability of pushbutton switches and significant weight. To eliminate these shortcomings, the design of an active antenna with a conical horn, which has the ability to change the parameters of the antenna within the entire range of 5 GHz. The optimal parameters of the horn are calculated as well. To obtain high values of the amplification gain of the horn antenna and maintain them with high stability at temperatures from -20 to +45оС used a signal amplification unit on a high-frequency operational amplifier SZA5044Z with a thermostat on a powerful transistor. Additional stability of the electrical characteristics of the amplifier is provided by double stabilization of the supply voltage. Electronic antenna control increases the reliability of the antenna by using electronic switching instead of push-button. Electronic control also protects the antenna amplifier from overheating, changing the polarity of the battery and electromagnetic interference. Laboratory and field studies of the directional horn antenna showed high stability of its parameters, reliability and ergonomics. Additional stability of the electrical characteristics of the amplifier is provided by double stabilization of the supply voltage. Electronic antenna control increases the reliability of the antenna by using electronic switching instead of push-button one. Electronic control also protects the antenna amplifier from overheating, change of the battery polarity and electromagnetic interference. Laboratory and field studies of the beam horn antenna showed high stability of its parameters, reliability and ergonomics.

Reduce delay of multipath TCP in IoT networks

Multi-homed devices such as smartphones, tablets and laptops are enabled with multiple heterogeneous interfaces available for transmission. Those interfaces can be utilized for simultaneous transmission of a single TCP flow using Multipath TCP (MPTCP). MPTCP is a protocol that is designed to increase end-to-end throughput and reliability of communications by splitting data through multiple parallel paths. Although delay in MPTCP enhanced significantly in the recent years, high number of data transmissions remains an issue. In this paper, we reduce MPTCP delay by reducing the number of transmissions using Opportunistic Routing (OR) technique. OR is a routing model used to increase the delivery rate and reliability of data transmission in wireless networks by using the broadcasting method. This enables each subflow data to be delivered by multiple relays. We adapted OR on a number of MPTCP protocols namely, traditional MPTCP, Multipath TCP Traffic Splitting Control (MPTCP-TSC) and Redundant MPTCP (ReMP TCP) in an Internet of Things (IoT) environment. The results show that OR-based MPTCP schemes outperform existing schemes. We further compared the OR-based MPTCP protocols in terms of startup delay and energy efficiency. We found that ReMP TCP is better than other schemes in all scenarios.

Automatic Control System of Balancing Agricultural Stereo Cultivation Based on Wireless Sensors

As a new development direction in the field of information science, wireless sensor network (WSN) has attracted wide attention of academia and industry with its huge application prospect. This research mainly discusses the automatic control system of balcony agriculture stereoscopic cultivation based on wireless sensor network. With the application background of environmental monitoring of protected cultivation, this paper analyzes the specific requirements of plant protected cultivation, and designs the overall scheme of wireless sensor network system with temperature, humidity and light as detection parameters. In this paper, a distance based routing algorithm is designed to realize the networking of wireless sensor networks, and the network simulation is carried out with TOSSIM. Aiming at the problem of packet loss in wireless network data transmission, this paper analyzes the operation mechanism and message structure of TinyOS operating system, and designs MAC protocol based on network synchronization to ensure reliable data transmission. The experimental results show that when the communication distance is 230 m, the two nodes can carry out normal data transmission; when the communication distance is less than 310 m, the bit error rate is very small; when the distance is more than 360 m, the bit error rate is significantly improved; when the distance is more than 400 m, the bit error rate is 100%. It can be seen that wireless sensor network can bring greater convenience to the acquisition of agricultural information, and it is of great significance to extend the application of wireless sensor network to the field of agricultural automation.

Autonomous Mobile Learning Model of Cloud Education Based on Intelligent Algorithm of Wireless Network Communication

The rapid development of a new generation of information technology and its widespread application in colleges and universities have promoted profound changes in campus informatization. On the one hand, wireless campus networks as the main infrastructure of digital campuses are gradually popularized in domestic colleges and universities, expanding the campus information network coverage. This article is aimed at studying the addition of intelligent algorithms to wireless network communications to optimize and build autonomous mobile learning for cloud education. In order for children to communicate with teachers face to face, no matter where they are, this article proposes how to reduce the energy loss in wireless communication and find the best intelligent algorithm to realize the cloud education mobile learning platform. Experimental results show that the transmission delay of the wireless communication system of this method is significantly shorter than that of the other two methods, close to 5%, which speeds up the data transmission speed of the wireless communication system. It can be implemented under time‐sensitive conditions and has high practical application value. The wireless network communication system of this method has a low packet loss rate and less wireless network data transmission errors, which is nearly 10% lower than the other two methods, thereby improving the data transmission power of the wireless communication network.