Data Communication Model Research Articles

Secure Steganography Model over Cloud Environment using Adaptive ABC and Optimum Pixel Adjustment Algorithm

An effective security model with low computational complexity, minimal quality-compromised, and improved security robustness is essential due to the rapid expansion of multimedia data communication through different cloud services. An image steganography model has been proposed for the security of multimedia data in an unreliable cloud environment. This study's main goal is to provide efficient steganography with barely hidden information. A secure data communication model has been developed over a cloud environment using the Adaptive Artificial Bee Colony Algorithm and the Optimum Pixel Adjustment Algorithm Based Image Steganography Method. An adaptive ABC (artificial bee colony) technique is applied to select the optimal pixel positions in the cover image because the goal of this investigation is to increase PSNR. The Optimal Pixel Adjustment approach is used to minimise embedding errors while maintaining the stego image's appearance identical to the cover image after embedding. The MATLAB platform is used to implement the proposed method. The results show that the proposed AABC-based OPA is more efficient across all measures investigated during the embedding and extraction processes.

Multi-Threaded Data Communication in Java for Advanced Computing Environments

The performance of operating systems like computers requires the proper functioning of the computer language interpreter. This interpreter follows various types of programming languages that make the performing of computer programming easy and effective. The application of the programming language of Java helps in processing multiple tasks at once. This research analyzes the novelty of Java-based data communication models in advanced computing services. This performance makes the saving of the resources used for the development of the programming language. All these development includes the performing of the multiple threads communication data processing. These multiple threads help distribute the single processed input in the multi-channel language processing, thus helping the work competition in time. It also reduces the cost of maintaining the programming languages reduced. Thus, the implementing cost of resources required for programming performance is reduced. Therefore, this implementation impacts the programmer to become more indented to use the language transformation process of Java. Moreover, it creates a more effective representation of the audio or visual content represented by a multi-tasking operating system. In this process of development in the language transformation of the operating system, the ability of the operating system for data processing improves. The systematic process of this language transformation helps in systematically transforming multiple programs at once.

Role of Internet of Things and Deep Learning Techniques in Plant Disease Detection and Classification: A Focused Review.

The automatic detection, visualization, and classification of plant diseases through image datasets are key challenges for precision and smart farming. The technological solutions proposed so far highlight the supremacy of the Internet of Things in data collection, storage, and communication, and deep learning models in automatic feature extraction and feature selection. Therefore, the integration of these technologies is emerging as a key tool for the monitoring, data capturing, prediction, detection, visualization, and classification of plant diseases from crop images. This manuscript presents a rigorous review of the Internet of Things and deep learning models employed for plant disease monitoring and classification. The review encompasses the unique strengths and limitations of different architectures. It highlights the research gaps identified from the related works proposed in the literature. It also presents a comparison of the performance of different deep learning models on publicly available datasets. The comparison gives insights into the selection of the optimum deep learning models according to the size of the dataset, expected response time, and resources available for computation and storage. This review is important in terms of developing optimized and hybrid models for plant disease classification.

PERENCANAAN JARINGAN TRANSPORT DENSE WAVELENGTH DIVISION MULTIPLEXING (DWDM) MENGGUNAKAN APLIKASI CISCO PACKET TRACER

Communication and information technology plays a very important role in various activities. Data communication which is part of a technological development, provides enormous benefits great for its users to expedite activities. For example in activities shipping goods using sea transportation which integrates various components for the shipping process, has used data communication models both offline and online. Based on the data communication flow, one of which includes transmission, namely Dense Wavelength Division Multiplexing (DWDM) which is a network that is transmit by a single optical fiber in order to keep growing which serves to load several waves in various sizes. This article is made to find out more regarding DWDM, as well as understanding DWDM simulations using applications as planning from the DWDM network. The method used is to make a plan using Cisco Packet Tracer application, which is then analyzed from the results of reading the literature based on journals and books.
 

Feasibility study of using various optical filters in conjunction with indoor visible light communication system

In modern telecommunication engineering, visible light communication (VLC) is developing a competitive advantage over the traditional RF data communication model since it uses light to transmit data. Optical filters play an important role in optical communication systems to enhance the transmission rate of bit-error rate (BER), especially as a result of noisy environments. We investigate the VLC signal performance induced by four types of filters, including Bessel, Gaussian, rectangular, and trapezoidal filters. The BER is considered an important aspect of improving optical system performance, as it indicates less crosstalk and fewer interferences within the system and is analyzed using eye diagram opening penalties. In our simulation results, the Gaussian filter performs best among these four types of filters. In this paper, a VLC indoor model is developed and simulated using an eye diagram, a bit error rate, and a transmission distance for the proposed model. The results from this study show significant improvements of Gaussian filter over other optical filters for next-generation optical networking systems, the overall BER of a Gaussian filter-based indoor VLC system is less than 9.6 × 10–15, when the bandwidth of the optical filter is 5 nm at the quality factor of 14 dB.

Multi-Channel Configuration for improving received signal strength in non-line-of-sight environments of indoor visible light communication localization

In modern engineering technologies, energy conservation is a factor of primary concern. A feature of Light-emitting diode (LED) light sources is the ability to transmit information in addition to illumination at no additional cost. VLC (Visible Light Communication) is gaining an upper hand over the traditional RF data communication model, as it utilizes a technology by which light can be used to transmit data. It is commonly seen that dealing with non-line of sight (NLOS) is a major challenge for VLC systems as the light intensity is reflected in a variety of directions. To overcome this drawback, a new technique based on multichannel configuration is utilized to enhance the overall system performance. An indoor VLC model is designed and simulated on the basis of the eye-diagram, bit error rate, and received power of the proposed model. We also investigated the model under the influence of ambient light noise. The corresponding results are compared with the conventional NLOS system and an inference made shows the significant improvement for the next-generation optical communication system.

Research on the Relationship between Motion Performance and User Experience of Golf Virtual Simulation Putting Simulator

This paper designs and develops a virtual golf simulation putting simulator based on the existing computer technology and conducts in-depth research and analysis on the relationship between its motion performance and user experience. The network architecture of the distributed virtual golf simulation system and the scene data management model are established, based on which the server-side system design and the client-side network communication module design of the distributed virtual golf simulation system are carried out. In the requirement analysis, the functional requirements such as building VR scenes, data communication and recognition models, and the non-functional requirements such as system security and ease of use are analyzed; in the outline design, the hardware equipment and logical architecture of the automatic user experience optimization system are described; in the detailed design, the functional modules of the system are designed in detail, including VR induction experience, physiological signal dataset user experience identification, data communication, optimization strategy, and so on, and important class diagrams and flowcharts are given. The intervention effects of positive thinking training on sports performance and improving athletes’ attention and receptivity have been verified and recognized by coaches and athletes. The putting simulator in the experimental class had higher hole-in-hole parameters than the control class, a highly significant difference; the putting simulator in the experimental class had higher hole-in-hole parameters than the control class, with a highly significant difference. These 3D models may contain more detailed information. In a virtual scene, the more detailed information a model contains, the more polygons the model needs, so that the computer needs to draw many polygons per frame, which has a great impact on the real-time performance of scene drawing. The parameters of the 5-yard chip-and-shoot in the experimental class were higher than those in the control class, and there was a very significant difference between the parameters of the 15-yard chip-and-shoot in the experimental class and those in the control class. The experimental results show that the model optimization processing method and rendering acceleration technology proposed in this paper can largely improve the rendering efficiency of 3D virtual scenes.

IoV-SDCM: An IoV Secure Data Communication Model Based on Network Encoding and Relay Collaboration

Internet of Vehicles (IoV) is a significant 5G application scenario. As it developed rapidly, more and more vehicles are connected to Internet of Vehicles. The data security and privacy are the premises to ensure its service quality in an open communication network. This paper proposes IoV-SDCM, a secure data communication model in IoV. It includes a self-organizing relay forwarding network and an assured delivery mechanism. The relay forwarding network is used for constructing a dynamic collaboration network with the vehicle as the node. The security delivery mechanism is that network coding is used for data fragmentation and re-encoding to improve network communication reliability. Homomorphic encryption is used to encrypt and protect the encoding vector, improving information leakage and anticollusion attacks. The theoretical proof proves that the model has the ability of data transmission confidentiality and better antiattack capabilities, while it has privacy protection capabilities. Furthermore, the experiment verifies that the model also has the advantage of high and stable data delivery efficiency.

Fully Integrated Data Communication Framework by Using Visualization Augmented Reality for Internet of Things Networks.

The new and integrated area called Internet of Things (IoT) has gained popularity due to its smart, objects, services and affordability. These networks are based on data communication, augmented reality (AR), and wired and wireless infrastructures. The basic objective of these network is data communication, environment monitoring, tracking, and sensing by using smart devices and sensor nodes. The dAR is one of the attractive and advanced areas that is integrated in IoT networks in smart homes and smart industries to convert the objects into 3D to visualize information and provide interactive reality-based control. With attraction, this idea has suffered with complex and heavy processes, computation complexities, network communication degradation, and network delay. This article presents a detailed overview of these technologies and proposes a more convenient and fast data communication model by using edge computing and Fifth-Generation platforms. The article also introduces a Visualization Augmented Reality framework for IoT (VAR-IoT) networks fully integrated by communication, sensing, and actuating features with a better interface to control the objects. The proposed network model is evaluated in simulation in terms of applications response time and network delay and it observes the better performance of the proposed framework.

A vibration-based multi-user concurrent communication system with commercial devices

Multi-user concurrent communication has become an increasingly important issue in mobile computing. Emerging vibration-based communication provides a new multi-to-single (M2S) data communication model for face-to-face tasks as opposed to most existing device-to-device (D2D) communication technologies. However, the transmission of multiple concurrent vibration signals often results in a highly coupled received signal, which makes it very difficult to reconstruct the source signals. This paper proposes ViCom, a vibration-based communication system that performs parallel decoding to achieve M2S transmission between mobile devices. The core of ViCom is a Decomposition Transformation Diagonal Algorithm (DTDA) that decomposes the received signal and constructs an estimated set of source signals, which are first decoupled by an autocorrelation function and then diagonalized to further improve the signal reconstruction accuracy. We implement ViCom using vibration motors and accelerometers embedded in existing smart phones and wearable devices, and evaluate its performance over different distances through disparate transmission media. Experimental results show that ViCom achieves effective data transmission of eight users with an accuracy of 98.6% and exhibits a superior overall performance over existing methods.

Optimization of vehicular ADHOC network performance using cloud computing model over mobility model

Vehicular ad hoc networks (VANET) is more dynamic in nature and rapidly changing the topology structure as the vehicles are always on the move. Due to this nature of Vehicular ad hoc networks, Security is a major concern for the network resources. Traffic jam detection and safest route finding is a prior goal for the Vehicular ad hoc networks protocol design. Objective of this paper is to provide an Effective Data Communication Model for Vehicular ad hoc networks with Cloud Computing. Processing Units of Vehicles are provided with a flexible interface system with Cloud servers for communicating between the vehicles. This model assures to give low cost, fast computing and extended storage for the nodes without requiring any additional infrastructures with in the network. The services include data aggregation, resource management and privacy. The results obtained from the simulation are tabulated and compared with the existing mobility model. The graph clearly shows the improvement in the performance in terms of reduced packet loss compared with the existing approach. Thus the Cloud based Vehicular ad hoc networks model out performs the Mobility model by certain level of performance attainment.

A deep learning- based frechet and dirichlet model for intrusion detection in IWSN

Industrial Wireless Sensor Network (IWSN) includes numerous sensor nodes that collect data about target objects and transmit to sink nodes (SN). During data transmission among nodes, intrusion detection is carried to improve data security and privacy. Intrusion detection system (IDS) examines the network for intrusions based on user activities. Several works have been done in the field of intrusion detection and different measures are carried out to increase data security from the issues related to black hole, Sybil attack, Worm hole, identity replication attack and etc. In various existing approaches, secure data transmission is not achieved, therefore resulted in compromising the security and privacy of IWSNs. Accurate intrusion detection is still challenging task in terms of improving security and intrusion detection rate. In order to improve intrusion detection rate (IDR) with minimum time, generalized Frechet Hyperbolic Deep and Dirichlet Secured (FHD-DS) data communication model is introduced. At first, Frechet Hyperbolic Deep Traffic (FHDT) feature extraction method is designed to extract more relevant network activities and inherent traffic features. With the help of extracted features, anomalous or normal data is predicted. Followed by Statistical Dirichlet Anomaly-based Intrusion Detection model is applied to discover intrusion. Here, Dirichlet distribution is evaluated to attain secure data transmission and significantly detect intrusions in WSNs. Experimental evaluation is carried out with KDD cup 99 dataset on factors such as IDR, intrusion detection time (IDT) and data delivery rate (DDR). The observed results show that the generalized FHD-DS data communication method achieves higher IDR with minimum time.

Reliable Data Communication Model for Fog Computing

To maintain data privacy and control who has access to what in the cloud, attribute-based encryption might be utilized. Attribute security is violated when apparent qualities are introduced to the encrypted message to assist people to identify necessary details in vast systems. To offer an effective attribute-based access control with an authorized search strategy, this research expands the anonymous key-policy attribute-based encryption (AKP-ABE) to provide fine-grained data retrieval while safeguarding attribute privacy (EACAS). In EACAS, data users may generate the trapdoor using the secret key supplied by data owners and conduct searches based on access restrictions to get the relevant data. Cryptographic protocols and trapdoor generation use a synthetic property devoid of syntactic significance to provide an attribute-based search on the exported encoded information in the fog. Data owners may implement granular access control on their outsourced data by establishing the search criteria that will be used by data consumers to locate relevant content based on protected attributes. We show that compared to the state-of-the-art methods, EACAS requires less time and space to process and store data.

Design and Evaluation of Visible Light Wireless Data Communication Models

The technologies based on the radio frequency used for wireless transmission indoor are more congested than ever these days, therefore several wireless communication alternatives are intensively searched. Some most promising technologies are based on the optical part of the electromagnetic spectrum. The benefits and drawbacks in optical wireless data communication models design are presented in this work. The key characteristics of the VLC systems are briefly discussed, as well. Some models developed for wireless data transfer in visible light communication and infrared are presented, and their operation related to the data rate and the length of the optical link, are briefly compared.

Enhanced data communication models for real‐time power system monitoring in a distributed platform

ABSTRACTThe novelty behind this research is to develop enhanced models for real‐time power system monitoring in a platform‐independent and distributed platform. Distributed models for power system applications have been implemented using Remote Method Invocation (RMI), Common object Request Broker Architecture and. NET remoting technologies. The interoperability among the heterogeneous power system clients in a distributed platform has been achieved through XMLization of power system data which provides meaningful solution to the legacy issues associated with power systems. A RMI‐based model for real‐time power system monitoring in a distributed platform had been implemented and discussed in detail. A component model for real‐time power system monitoring has also been proposed and implemented to increase the reusability and scalability of the system. A location transparent model has been developed using Common object Request Broker Architecture with RMI‐Internet Inter‐Orb Protocol for load flow monitoring and the idea is extended to solve real‐time economic load dispatch and dynamic security monitoring. The detailed monitoring on performance of the proposed models has been done with load flow monitoring, dynamic security monitoring and economic load dispatch problems. A. NET remoting architectural model has been developed for real‐time economic load dispatch in a distributed platform. This research paper explores various issues in deploying power system applications in a distributed platform. It will serve the purpose of stimulating interest among power engineers and also will be extremely useful for electric power utilities.

A NEW AND ADAPTIVE SECURITY MODEL FOR PUBLIC COMMUNICATION BASED ON CORRELATION OF DATA FRAMES

Recent developments in communication and information technologies, plus the emerging of the Internet of Things (IoT) and machine to machine (M2M) principles, create the need to protect data from multiple types of attacks. In this paper, a secure and high capacity data communication model is proposed to protect the transmitted data based on identical frames between a secret and cover data. In this model, the cover data does not convey any embedded data (as in normal steganography system) or modify the secret message (as in traditional cryptography techniques). Alternatively, the proposed model sends the positions of the cover frames that are identical with the secret frames to the receiver side in order to recover the secret message. One of the significant advantages of the proposed model is the size of the secret key message which is considerably larger than the cover size, it may be even hundred times larger. Accordingly, the experimental results demonstrate a superior performance in terms of the capacity rate as compared to the traditional steganography techniques. Moreover, it has an advantage in terms of the required bandwidth to send the data or the required memory for saving when compared to the steganography methods, which need a bandwidth or memory up to 3-5 times of the original secret message. Where the length of the secret key (positions of the identical frames) that should be sent to the receiver increases by only 25% from the original secret message. This model is suitable for applications with a high level of security, high capacity rate and less bandwidth of communication or low storage devices.

Cluster based architecture and network maintenance protocol for medical priority aware cognitive radio based hospital.

Due to the rapid growth of wireless medical devices in near future, wireless healthcare services may face some inescapable issue such as medical spectrum scarcity, electromagnetic interference (EMI), bandwidth constraint, security and finally medical data communication model. To mitigate these issues, cognitive radio (CR) or opportunistic radio network enabled wireless technology is suitable for the upcoming wireless healthcare system. The up-to-date research on CR based healthcare has exposed some developments on EMI and spectrum problems. However, the investigation recommendation on system design and network model for CR enabled hospital is rare. Thus, this research designs a hierarchy based hybrid network architecture and network maintenance protocols for previously proposed CR hospital system, known as CogMed. In the previous study, the detail architecture of CogMed and its maintenance protocols were not present. The proposed architecture includes clustering concepts for cognitive base stations and non-medical devices. Two cluster head (CH selector equations are formulated based on priority of location, device, mobility rate of devices and number of accessible channels. In order to maintain the integrity of the proposed network model, node joining and node leaving protocols are also proposed. Finally, the simulation results show that the proposed network maintenance time is very low for emergency medical devices (average maintenance period 9.5 ms) and the re-clustering effects for different mobility enabled non-medical devices are also balanced.

On the Performance of MIMO-ARQ Systems with Channel State Information at the Receiver

This paper investigates the performance of multiple-input-multiple-output (MIMO) systems in the presence of automatic repeat request (ARQ) feedback. We show that, for a large range of performance metrics, the data transmission efficiency of the ARQ schemes is determined by a set of parameters which are scheme-dependent and not metric-dependent. Then, the results are used to study different aspects of MIMO-ARQ such as the effect of nonlinear power amplifiers, large-scale MIMO-ARQ, adaptive power allocation and different data communication models. The results, which are valid for various forward and feedback channel models, show the efficiency of the MIMO-ARQ techniques in different conditions.

Design and Application of Queue-Buffer Communication Model in Pneumatic Conveying

In order to communicate with a PLC (Programmable Logic Controller) flexibly and freely, a data communication model based on the PLC's free port is designed. In the structure of the model, a distributed data communication environment is constructed by using Ethernet and serial adapters. In the communication algorithm, a method of queue-buffer for multi-threaded is used to improve the real-time of the control. This communication model has good scalability and portability because the realization of it is not restricted by the number of PLC slave stations and the type of operating system of the host computer. A corresponding communication algorithm is applied to data collection and devices monitoring for a pipe pneumatic conveying system. The practice shows that not only the stability and reliability of the model can meet the needs of automatic control but also the communication performance and efficiency of the model is outstanding.

Mitigating first respondent challenges via enhancing health record access

Most e-health record systems developed to date are meant to enhance the efficiency and effectiveness of operations performed within the hospital setup. This study is one of the first that extends the applications of health information technology beyond the hospital vicinity to the site of an emergency. Also, it presents an integrated health database system, a client signalling and tracking system, and a data communication model that allows for paramedics to access medical records remotely. Results from the conducted survey illustrate that 100% of responders agreed that the demand for emergency services is on an increase; 45.45% asserted that they had difficulties in ascertaining the medical history of emergency victims; 83.33% concurred that knowledge of a victim’s medical history will expedite pre-hospital care; 83.33% desired to have more sophisticated data communication system and 66.67% preferred obtaining the medical record of an emergency victim electronically. Based on the aforementioned challenges and concerns, this study presents an integrated health database and data communication system that will enable paramedics to efficiently and effectively address some of their current concerns and challenges.