Data Transmission Model Research Articles

Improving Energy Efficiency and QoS of LPWANs for IoT Using Q-Learning Based Data Routing

Recent proliferation of Internet of Things (IoT) demands large scale connectivity among smart IoT devices over a vast geographical area. However, limited radio range and lack of scalability of conventional wireless sensor networks do not allow a wide area connectivity among IoT devices. To address these challenges, Low-Power Wide-Area Networks (LPWANs) are emerging to provide long-range communication capability with low-power consumption of the end devices. Nevertheless, given the demand in delivering an increasingly large volume of data generated by IoT devices, the direct data transmission model is not suitable due to its poor network lifetime. Therefore, in this work, a multi-hop data routing method is proposed for LPWANs. Since multi-hop data transmission faces several challenges such as increased data latency, higher interference, and reduced data throughput (i.e., poor bandwidth utilization), we propose a reinforcement learning method to address those challenges. The proposed method updates the Q-matrix of the network at varying discrete time instants and selects relay devices in such a way that maximizes the cumulative reward value between selected device-gateway pairs. The applicability and effectiveness of the proposed method are illustrated over both simulated LPWAN testbed and real field data sets. The obtained results clearly demonstrate the improved network performance in terms of energy efficiency and QoS of the proposed method as compared to various existing methods.

Blockchain with deep learning-enabled secure healthcare data transmission and diagnostic model

At these times, internet of things (IoT) technologies have become ubiquitous in the healthcare sector. Because of the increasing needs of IoT, massive quantity of patient data is being gathered and is utilized for diagnostic purposes. The recent developments of artificial intelligence (AI) and deep learning (DL) models are commonly employed to accurately identify the diseases in real-time scenarios. Despite the benefits, security, energy constraining, insufficient training data are the major issues which need to be resolved in the IoT enabled medical field. To accomplish the security, blockchain technology is recently developed which is a decentralized architecture that is widely utilized. With this motivation, this paper introduces a new blockchain with DL enabled secure medical data transmission and diagnosis (BDL-SMDTD) model. The goal of the BDL-SMDTD model is to securely transmit the medical images and diagnose the disease with maximum detection rate. The BDL-SMDTD model incorporates different stages of operations such as image acquisition, encryption, blockchain, and diagnostic process. Primarily, moth flame optimization (MFO) with elliptic curve cryptography (ECC), called MFO-ECC technique is used for the image encryption process where the optimal keys of ECC are generated using MFO algorithm. Besides, blockchain technology is utilized to store the encrypted images. Then, the diagnostic process involves histogram-based segmentation, Inception with ResNet-v2-based feature extraction, and support vector machine (SVM)-based classification. The experimental performance of the presented BDL-SMDTD technique has been validated using benchmark medical images and the resultant values highlighted the improved performance of the BDL-SMDTD technique. The proposed BDL-SMDTD model accomplished maximum classification performance with sensitivity of 96.94%, specificity of 98.36%, and accuracy of 95.29%, whereas the feature extraction is performed based on ResNet-v2

Marketing Resource Allocation Strategy Optimization Based on Dynamic Game Model

Game theory has become an important tool to study the competition between oligopolistic enterprises. After combing the existing literature, it is found that there is no research combining two‐stage game and nonlinear dynamics to analyze the competition between enterprises for advertising. Therefore, this paper establishes a two‐stage game model to discuss the effect of the degree of firms’ advertising input on their profits. And the complexity of the system is analyzed using nonlinear dynamics. This paper analyzes and studies the dynamic game for two types of application network models: data transmission model and transportation network model. Under the time‐gap ALOHA protocol, the noncooperative behavior of the insiders in the dynamic data transmission stochastic game is examined as well as the cooperative behavior. In this paper, the existence of Nash equilibrium and its solution algorithm are proved in the noncooperative case, and the “subgame consistency” of the cooperative solution (Shapley value) is discussed in the cooperative case, and the cooperative solution satisfying the subgame consistency is obtained by constructing the “allocation compensation procedure.” The cooperative solution is obtained by constructing the “allocation compensation procedure” to satisfy the subgame consistency. In this paper, we propose to classify the packets transmitted by the source nodes, and by changing the strategy of the source nodes at the states with different kinds of packets, we find that the equilibrium payment of the insider increases in the noncooperative game with the addition of the “wait” strategy. In the transportation dynamic network model, the problem of passenger flow distribution and the selection of service parameters of transportation companies are also studied, and a two‐stage game theoretical model is proposed to solve the equilibrium price and optimal parameters under Wardrop’s criterion.

An integrity control model for mass data transmission under big data cloud storage

In order to improve the control level of massive data transmission integrity, improve the space utilisation efficiency and data transmission integrity under cloud storage, an integrity control model of mass data transmission under big data cloud storage is constructed. Firstly, the basic principle of big data cloud storage is studied. The developing process of big data, data storage technology, and data retrieval technology is studied. Secondly, the mass data feature extraction model is established. The theory model and framework of feature extraction model for mass data are analysed. Thirdly, the massive data integrity control algorithm is designed based on an ant algorithm. The prior control models of single node rate are studied and system level parallel data transmission rate are analysed. Finally, simulation analysis is carried out, and the effectiveness of the proposed method is verified.

Simulation modeling of multi-stream data transmission in the AnyLogic environment

The paper considers a simulation model of multi-path data transmission built in the AnyLogic environment. The use of a multi-path data transmission scenario is extremely relevant today since user devices have more than one communication interface, and the amount of traffic is growing. We analyzed the QoS characteristics for a scenario with two sub-paths. It has been shown that a policy of allocation data into subpaths according to the amount of free resources can lead to the problem of incorrect packet order on the receiving side. In addition, it is obvious that the AnyLogic environment can be used to model telecommunication systems at a high level of abstraction.

Trust Aware Manta Ray Foraging Optimization based Secure Routing Protocol for Wireless Sensor Networks

In Wireless sensor network (WSN) is a different type of ad-hoc network has of battery powered minimum cost sensor node with restricted computation and communication abilities used densely from a target region. The routing in WSN roles is an essential part due to their inherent energy storing ability and is suitable to extremely scalable networks. The trust in WSN roles an essential play in creating the network and addition or deletion of sensor nodes in a network very smooth and translucent. The trust was formalized as a computational method. This study develops a novel Trust Aware Manta Ray Foraging Optimization based Secure Routing (TAMRFO-SR) protocol for WSN. The proposed TAMRFO-SR model accomplishes optimal and secure routes for WSN. In addition, the TAMRFO-SR model is mainly stimulated by the fascinating characteristics of manta rays. Besides, the TAMRFO-SR model derives a fitness function with multiple parameters for secure route selection process. Moreover, the inclusion of trust in the route selection process assists in accomplishing enhanced security. The design of TAMRFO-SR model for secure data transmission depicts the novelty of the study. The experimental validation of the TAMRFO-SR model demonstrates better performance over the other approaches.

An integrity control model for mass data transmission under big data cloud storage

An integrity control model for mass data transmission under big data cloud storage

MODELING OF RELIABILITY AND AVAILABILITY OF DATA TRANSMISSION IN RAILWAY SYSTEM

The analysis of the reliability and availability of the data transmission system within the integral railway system is realized through the modeling of the system, i.e. its conditions and their connections. According to the defined measure of safety of the International union of railways (UIC) i.e. its committee ORE, defined by recommendations A 158 and A 124/RP, based on previous experience and the achieved level of technical development, we can estimate an acceptable value for the probabilities of certain conditions of the integral railway system and data transmission system. In the paper, the reliability and availability analysis was modeled using the Markov model for data transmission in the railway system with four conditions, for: correct system condition, presence of disturbances in the system, illegal (dangerous) system condition and system blocking condition. The validity for the application of process development modeling the reliability and availability of data transmission in the railway system will contribute to reducing the risk of inadmissible (dangerous) failures, improving maintenance planning and spare parts planning, moving from maintenance by time to maintenance by condition and reducing exploitation costs.

Modeling of information transmission systems in modern mobile terms

The work is dedicated to information transmission systems in modern mobile networks. The main task of any information transmission system is to combat various kinds of interference which lead to distortion or complete information loss and thus reduced communication channel reliability. Therefore, it became necessary to develop adaptive data transmission systems, in which adaptive methods help to achieve high-quality control in the absence of sufficiently complete a priori information about the characteristics of the controlled process or under conditions of uncertainty. The research was carried out on a simulation model of data transmission built on the basis of binary symmetry. The proposed adaptive system is based on the assessment of the state of the data transmission channel, according to which the bit rate of the transmitted data and the parameters of the noise-correcting code are selected, which provides a certain level of errors on the receiving side, taking into account the limited bandwidth of the communication channel. The developed simulation model of adaptation to the state of the communication channel demonstrates the required level of reliability and allows to work with different levels of noise in the communication channels, and the occurrence of an error in the channel can be either uniform during data transmission or random. The results of simulation modeling testify to the correctness of the proposed solution and allow the evaluation the main parameters of information transmission systems in mobile networks. The proposed model of information transmission with adaptation to the state of the communication channel may be applied in modern mobile networks, telecommunications and computer systems with an increased level of quality requirements for information transmitted at low speed, since the proposed solution does not require complex calculations.

Efficient Neighbour Feedback Based Trusted Multi Authenticated Node Routing Model for Secure Data Transmission

The Mobile Ad Hoc Network (MANET) is a network that does not have a fixed infrastructure. Migratory routes and related hosts that are connected via wireless networks self-configure it. Routers and hosts are free to wander, and nodes can change the topology fast and unexpectedly. In emergencies, such as natural/human disasters, armed conflicts, and emergencies, the lowest configuration will ensure ad hoc network applicability. Due to the rapidly rising cellular service requirements and deployment demands, mobile ad-hoc networks have been established in numerous places in recent decades. These applications include topics such as environmental surveillance and others. The underlying routing protocol in a given context has a significant impact on the ad hoc network deployment power. To satisfy the needs of the service level and efficiently meet the deployment requirements, developing a practical and secure MANET routing protocol is a critical task. However, owing to the intrinsic characteristics of ad hoc networks, such as frequent topology changes, open wireless media and limited resources, developing a safe routing protocol is difficult. Therefore, it is vital to develop stable and dependable routing protocols for MANET to provide a better packet delivery relationship, fewer delays, and lower overheads. Because the stability of nodes along this trail is variable, the route discovered cannot be trusted. This paper proposes an efficient Neighbour Feedback-based Trusted Multi Authenticated Node (NFbTMAN) Routing Model. The proposed model is compared to traditional models, and the findings reveal that the proposed model is superior in terms of data security.

Optimal multiple key‐based homomorphic encryption with deep neural networks to secure medical data transmission and diagnosis

AbstractMedical database classification problems can be considered as complex optimization problems to assure the diagnosis support precisely. In healthcare, several computer researchers have employed different deep learning (DL) approaches to enhance the classification performance. Besides, encryption is an effective way to offer secure transmission of medical data over public network. With this motivation, this paper presents new privacy‐preserving encryption with DL based medical data transmission and classification (PPEDL‐MDTC) model. The presented model derives multiple key‐based homomorphic encryption (MHE) technique with sailfish optimization (SFO), called MHE‐SFO algorithm‐based encryption process. In addition, the cross‐entropy based artificial butterfly optimization‐based feature selection technique and optimal deep neural network (ODNN) based classification is carried out. In ODNN model, the hyperparameter optimization of the DNN model is carried out utilizing the use of chemical reaction optimization (CRO) algorithm. The proposed method has been simulated utilizing Python 3.6.5 tool, which is tested using activity recognition and sleep stage dataset. A detailed comparative outcomes analysis makes sure the higher efficiency of the PPEDL‐MDTC on the state of art techniques with the detection accuracy of 0.9813 and 0.9650 on the applied activity recognition and University College Dublin Sleep Stage dataset.

Grid-Based Routing Model for Energy Efficient and Secure Data Transmission in WSN for Smart Building Applications

Presently, due to the establishment of a sensor network, residual buildings in urban areas are being converted into smart buildings. Many sensors are deployed in various buildings to perform different functions, such as water quality monitoring and temperature monitoring. However, the major concern faced in smart building Wireless Sensor Networks (WSNs) is energy depletion and security threats. Many researchers have attempted to solve these issues by various authors in different applications of WSNs. However, limited research has been conducted on smart buildings. Thus, the present research is focused on designing an energy-efficient and secure routing protocol for smart building WSNs. The process in the proposed framework is carried out in two stages. The first stage is the design of the optimal routing protocol based on the grid-clustering approach. In the grid-based model, a grid organizer was selected based on the sailfish optimization algorithm. Subsequently, a fuzzy expert system is used to select the relay node to reach the shortest path for data transmission. The second stage involves designing a trust model for secure data transmission using the two-fish algorithm. A simulation study of the proposed framework was conducted to evaluate its performance. Some metrics, such as the packet delivery ratio, end-end delay, and average residual energy, were calculated for the proposed model. The average residual energy for the proposed framework was 96%, which demonstrates the effectiveness of the proposed routing design.

RETRACTED ARTICLE: Research on data transmission model of agricultural wireless sensor network based on game theory

This article has been retracted from publication in the Taylor & Francis journal, Acta Agriculturae Scandinavica, Section B — Soil & Plant Science. Following publication, concerns were raised by multiple third-parties around the content of the special issue and the decision-making process. Following an investigation by the Taylor & Francis Publishing Ethics & Integrity team in full cooperation with the Editor-in-Chief, it was confirmed that this article included in Special Issue titled “ Envisage Computer Modelling and Statistics for Agriculture”, guest edited by Gunasekaran Manogaran was not peer-reviewed appropriately, in line with the Journal's peer review standards and policy. As the stringency of the peer review process is core to the integrity of the publication process, the Editor and Publisher have decided to retract all of the articles within the above-named Special Issue. The journal has not confirmed if the authors were aware of this compromised peer review process. The journal is committed to correcting the scientific record and will fully cooperate with any institutional investigations into this matter. The authors have been informed of this decision. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines.

Data Ownership and Secure Medical Data Transmission using Optimal Multiple Key-Based Homomorphic Encryption with Hyperledger Blockchain

Recent healthcare systems are defined as highly complex and expensive. But it can be decreased with enhanced electronic health records (EHR) management, using blockchain technology. The healthcare sector in today’s world needs to address two major issues, namely data ownership and data security. Therefore, blockchain technology is employed to access and distribute the EHRs. With this motivation, this paper presents novel data ownership and secure medical data transmission model using optimal multiple key-based homomorphic encryption (MHE) with Hyperledger blockchain (OMHE-HBC). The presented OMHE-HBC model enables the patients to access their own data, provide permission to hospital authorities, revoke permission from hospital authorities, and permit emergency contacts. The proposed model involves the MHE technique to securely transmit the data to the cloud and prevent unauthorized access to it. Besides, the optimal key generation process in the MHE technique takes place using a hosted cuckoo optimization (HCO) algorithm. In addition, the proposed model enables sharing of EHRs by the use of multi-channel HBC, which makes use of one blockchain to save patient visits and another one for the medical institutions in recoding links that point to EHRs stored in external systems. A complete set of experiments were carried out in order to validate the performance of the suggested model, and the results were analyzed under many aspects. A comprehensive comparison of results analysis reveals that the suggested model outperforms the other techniques.

An Optimistic Security Model for Improving Cyber Security Using Adaptive Algorithms to Prevent SQL Injection Attacks

Throughout today's economic and social life, the use of web-based services (such as e-commerce, online banking, and web-based communications, to name a few) has become a common habit. Countless applications operate worldwide on millions of servers, and their numbers are steadily increasing. It has become a focus of attackers and hackers for the attacks because of the huge growth of internet usage. It is necessary for all companies to develop and protect their applications in order to maintain their credibility and keep their products relevant for users. Web applications have brought in new classes of computer security vulnerabilities, such as SQL injection (SQLIA), and it has exceeded previously prominent vulnerability classes in recent years. SQL injection is the instance of the broader class of vulnerabilities that are based on input validation. The primary purpose of this research is to study the vulnerabilities of SQL injection and to propose an optimistic security model for secure data transmission. In this work, the authors proposed an adaptive algorithm to prevent SQL injections.

Sistem Pemantauan Dapur Menggunakan Teknologi Hybrid WiFi - Visible Light Communication

Visible Light Communication (VLC) is a technology that allows the sending of data information through visible light that will be received as a piece of information. In its implementation, a sensor can send information data using VLC in this technological era. One model of data transmission that is widely used in life is to use radio frequency or better known as wireless.In this final project, a transmitter and receiver of data is realized through the transmission of light, this device consists of a lamp as an electrical converter to light, a photodioda as a converter of light to electric, and receiving data. Through the realization of this tool we can know that the transmission of data through light can occur can be used to transmit data. Data transmitted in this final project is the result of three sensor data namely temperature sensors, gas sensors, and fire detection sensors on the transmitter and on the receiver used firebase to monitor data. From the test results produce parameter values such as distance with a maximum distance of the data is accepted either 45cm, 50cm of data is damaged and 55cm of data is not accepted, the variations in angles and distances show that at a distance of 10cm it can receive data well from an angle of 0ᵒ to an angle of 35ᵒ, a distance of 35cm and 40 cm at an angle of 10ᵒ the received data is damaged and at a distance of 45cm and 50cm at a 5ᵒ angle cannot receive data and as well as the sending speed parameters obtained at a baudrate of 2400 bps, 4800 bps and 9600 bps the data sent can be received well.

Two-Level Congestion Control Mechanism (2LCCM) for Information-Centric Networking

As an emerging network architecture, Information-Centric Networking (ICN) is considered to have the potential to meet the new requirements of the Fifth Generation (5G) networks. ICN uses a name decoupled from location to identify content, supports the in-network caching technology, and adopts a receiver-driven model for data transmission. Existing ICN congestion control mechanisms usually first select a nearby replica by opportunistic cache-hits and then insist on adjusting the transmission rate regardless of the congestion state, which cannot fully utilize the characteristics of ICN to improve the performance of data transmission. To solve this problem, this paper proposes a two-level congestion control mechanism, called 2LCCM. It switches the replica location based on a node state table to avoid congestion paths when heavy congestion happens. This 2LCCM mechanism also uses a receiver-driven congestion control algorithm to adjust the request sending rate, in order to avoid link congestion under light congestion. In this paper, the design and implementation of the proposed mechanism are described in detail, and the experimental results show that 2LCCM can effectively reduce the transmission delay when heavy congestion occurs, and the bandwidth-delay product-based congestion control algorithm has better transmission performance compared with a loss-based algorithm.

Détection du cancer du sein à l’aide de soutiens-gorge connectés en 2021 : analyses et perspectives

ObjectivesBreast cancer is the leading cancer in women worldwide with about 2 million new cases and 685,000 deaths each year. Mammography is the most widely used screening and diagnostic method. Currently, digital technologies advances facilitate the development of connected and portable devices. To overcome some of the disadvantages of mammography (breast compression, difficulty in analyzing dense breasts, radiation, limited accessibility in some countries, etc.), portable devices, conventionally known as connected bras (CB), have been created to offer an alternative method to mammography. The objective of our review was to list all the published CBs in order to know their main characteristics, their potential indications and their possible limitations. MethodA bibliographical search in the PUBMED database selecting only articles written in French or English, between 2011 and 2020, found 7 CBs under development. ResultsThese CBs use thermal, ultrasonic and impedance sensors. Their advantages are an absence of irradiation, an absence of breast compression and a flexibility of use (outside an X-ray cabinet). Mammary gland analysis times vary, depending on the device, between 30min and 24h. They are all connected to data transmission systems and models that analyze the results. Discussion and conclusionThese CBs are mostly still undergoing clinical validation (only [iTBra] has been evaluated in a clinical trial) and require evaluation steps that will eventually allow their future use for breast cancer detection in high-risk women, particularly in women with dense breasts and in women between screening waves.

A Trusted Water Fall Model for Efficient Data Transmission in VANET

Vehicular adhoc networks are slowly gaining importance as the demand for faster communication increases. The vehicular nodes need to communicate securely via an established and effective route. Control and protocol information between the vehicles is transmitted using the technique of broadcasting. The nodes are never stagnant and even though their energy rarely dissipates, the high mobility of the nodes poses quite a problem. Lack of an established infrastructure is a major issue and needs to be addressed in order to achieve maximum performance. We have designed a novel waterfall model focusing on a robust broadcasting method. The OLSR protocol is enhanced using a robust MPR technique, which helps in mitigating the circulation of duplicate packets within the network. The RMPR subset of the OLSR protocol is capable of handling transmission errors and the hidden and exposed terminal problems prevalent in the VANET environment. The inclusion of a waterfall model enables the proposed technique to maximize throughput and minimize the delay in the network. The waterfall model works in two major phases. The first phase incorporates the Cognitive radio scheme for effective channel allocation and utilization.The RMPR technique is implemented in the second phase which focuses on utilizing the neighbor nodes to transmit the packets successfully towards the destination. The RMPR scheme aims to categorize the neighboring nodes as either one hop or 2-hop neighboring nodes. Additionally, the uncategorized nodes are further probed to find a second subset of 2-hop nodes which would speed up the transmission. The implementation of these two important phases into the classic waterfall model helps to streamline the activities and helps in streamlining the network activities.The proposed waterfall model RMPR technique is analyzed with protocols like MMPR–OLSR and the OLSR protocols to determine the effectiveness of the proposed protocol. The performance analysis is carried out using the NS2 simulator. The techniques that are compared are evaluated using major network parameters like throughput, delay, PDR and channel utilization. It is evident that the proposed protocol is able to maximize the PDR than the existing techniques.

Tunable phase of elliptical axicon for controlled spectral switching

Recently, spectral switching has attracted worldwide interest due to its ever-growing optical information processing applications. Over the past few decades, various light beam profiles have been extensively studied for attaining complete control over these spectral modulations. This paper has studied the spectral modulation in the partially coherent intensity profiles obtained from radially symmetric and elliptical axicon phases, respectively. Theoretical findings have been confirmed with experimental results. The study's outcomes conclude that the eccentricity of axicon phase plays a significant role in controlling the spectral switching at any desired position in the beam profiles. We have also proposed a free space optical data transmission model based on controlled spectral switching by an elliptical axicon phase with tunable eccentricity. This study might find applications in developing a convenient setup for free space optical communication.