Data Communication Networks Research Articles

Improving QoS Using Mobility-Based Optimized Multipath Routing Protocol in MANET

Mobile Ad-hoc Networks (MANETs) connect numerous nodes to communicate data from the sender node to the target node. Due to the lack of an infrastructure network, mobile nodes communicate through wireless without an access point. MANET does not have a centralized controller and has a dynamic network topology, which increases link failure and energy consumption resulting in excessive path delay, loss of Quality of service (QoS), and reduced throughput during data communication. Congestion is a significant problem when the QoS of the link carrying the data is degraded. Routing is one of the vital challenges of MANET due to the very dynamic and distributed nature of MANET. This article introduces a Mobility-Based Optimized Multipath Routing Protocol (MBOMRP) and an Efficient Reliable Link-State Transmission (ERLST) algorithm to overcome these problems. The proposed Mobility-Based Optimized Multipath Routing Protocol (MBOMRP) is utilized for route discovery and maintenance to efficiently avoid traffic and sleeping nodes. ERLST algorithm is used for efficient data transmission to increase QoS measurement parameters like throughput, Packet Delivery Ratio (PDR), and minimize the latency performance. The proposed MBOMRP-ERLST algorithm improves data communication network lifetime, avoids link failures, and provides efficient results compared with previous algorithms.

Application of 5G Communication Technology Based on Intelligent Sensor Network in Coal Mining

Intelligent mining provides an indispensable, strong technical support for the construction of intelligent mines. Intelligent tunneling technology is an inevitable requirement for safe and efficient production of coal and a fundamental way to solve the imbalance of mining in order to improve the deficiency of data transmission in light of intelligent coal tunneling technology. Based on intelligent sensor and 5G technology, this paper puts forward a kind of intelligent tunneling support transportation integrated technology. According to the geological conditions of the surrounding rock in different coal seams, the anchor road header and 5G continuous intelligent tunneling mode are adopted. At the same time, the data communication network coverage suitable for underground unmanned driving is expounded, and the performance indexes that need to be met for accessing WLAN network are given based on the actual engineering experience. The breakthrough of underground unmanned driving application that 5G new communication network will bring is analyzed. And the construction mode of 5G platform of underground coal mine sensor network is given.

An Infrastructure of Battery Swapping and Charging Stations in Smart Cities to “Disrupt” the Current Ecosystem of Battery Usage: A Schematic Design

This article proposes a quintessential, down-to-earth schematic design of battery swapping and charging stations (BSCSs) typically in smart cities together with their necessary battery standardization, supportive information systems and data communication network for the implementation of a citywide and even worldwide infrastructure of BSCSs. At such BSCSs, users of mobile information communication technology (ICT) equipment like mobile phones, tablet computers, lap-tops, etc. and electric vehicles can swap and trade their standardized battery modules whenever depleted for fully charged ones almost in no time virtually anytime and everywhere without ever worrying about battery depletion of the equipment and the extended time and specialized chargers for recharging. Harnessing earlier technologies of the author, this design could be a game-changer to “disrupt” the current battery usage ecosystem consisting of an excessively large number of, sometimes costly, infrastructures and chargers to recharge individuals’ equipment, the cumbersome practice to recharge with specialized chargers at designated locations over extended time periods, and bulky secondary power banks being hand-carried. The key is that in this schema, disparity of battery modules’ estimated remnant energy storage capacities can be offset by monetary payments.

Large Integer Decomposition Encryption Algorithm for Computer Network Data Communication Combined with Double BP Neural Network Combination Model

Usually a complete computer network system has the following components: source of signals, signal host, cryptographic regime, attack, and interceptor. It is more vulnerable to attacks during the operation of the system, so the security of the system becomes more important. In this paper, by constructing a dual BP neural network combinatorial model and applying it to the computer data communication large integer decomposition encryption process, the constructed model is used to analyze the security against digital certificates, digital signatures, and the algorithms employed in the communication process of connected computer network.

Network intrusion detection system using an optimized machine learning algorithm

The rapid growth of the data-communications network for real-world commercial applications requires security and robustness. Network intrusion is one of the most prominent network attacks. Moreover, the variants of network intrusion have also been extensively reported in the literature. Network Intrusion Detection Systems (NIDS) have already been devised and proposed in the literature to handle this issue. In the recent literature, Kitsune, NIDS, and its dataset have received approx. 500 citations so far in 2019. But, still, the comprehensive parametric evaluation of this dataset using a machine learning algorithm was missing in the literature that could submit the best algorithm for network intrusion attack detection and classification in Kitsune. In this connection, two previous studies were reported to investigate the best machine algorithm (these two studies were reported by us). Through these studies, it was concluded that the Tree algorithm and its variants are best suited to detect and classify all eight types of network attacks available in the Kitsune dataset. In this study, the hyper-parameter optimization of the optimized Tree algorithm is presented for all eight types of network attack. In this study, the optimizer functions Bayesian, Grid Search, and Random Search were chosen. The performance has been ranked based on training and testing accuracy, training and testing cost, and prediction speed for each optimizer. This study will submit the best point hyper-parameter for the respective epoch against each optimizer.

Comprehensive Review of Renewable Energy Communication Modeling for Smart Systems

Due to the rising trends in the adoption of smart systems such as smart grids, smart homes, and vehicle-to-grid, there has been a lot of research interest in these areas. To manage these complex systems effectively and intelligently, a reliable, high-speed, and secure data communication network is very essential. The key distinguishing feature between smart systems and traditional ones is that smart systems use a two-way communication system while traditional systems usually use one-way communication. The requirements and techniques needed to ensure safe, secure, and reliable communication in smart systems have been the focus of many researchers in recent times. This work is aimed at providing a comprehensive, all-encompassing, up-to-date review of smart systems communication to ascertain the research directions as well as challenges. This review will guide other researchers in delving into smart systems communication to identify potential research problems and future research directions or research gaps.

Implementation of Digital Filters for Real-Time PPG Signal Processing in VLC

Health care units depend on Wi-Fi or local area networks for biomedical data communication within their premises. The major hazard associated with biomedical data communication in healthcare units is radio frequency interference with medical devices. Visible light communication (VLC) is a developing technology that solves the issue of RF interference in healthcare units. Long-range communication is a great challenge in VLC as the transmitted data get corrupted by noise from ambient light and degrade with distance. Hence it is necessary to upgrade the signal condition and eradicate the noise due to ambient light interference. The proposed work addresses these issues and enables robust communication in healthcare units. The experimental validation of the proposed work has been executed by analyzing the VLC communication performance up to a distance of 5[Formula: see text]m. The proposed work focuses on implementation of digital filters like finite impulse response, infinite impulse response and least mean square adaptive filter for PPG signal processing. The least mean square filter showed a superior performance with a mean square error of 7.23e[Formula: see text] than the other filters, leading to an accurate diagnosis for patients without any RF interference inside healthcare units.

Optical scheme of developing Hamming code-based error detection and correction using Toffoli gates with frequency encoded data

Bit-error detection and correction is a very important part of a data communication network. In this article, we propose an optical approach to designing an error detection and correction circuit using Hamming code-based frequency encoded binary data and Toffoli gates. Here, the Toffoli gates are made of semiconductor optical amplifiers (SOAs) that work based on the nonlinear polarization rotation property. The characteristics of SOA, including very fast switching action (about 0.01 ns), low power consumption, frequency independent cross-polarization gain in the C-band, cascading property, etc., make the scheme attractive. The frequency encoded data-based proposed scheme will be effective for WDM communication networks. MATLAB simulation results testify to the feasibility of the proposed scheme.

NIDD: an intelligent network intrusion detection model for nursing homes

AbstractIn nursing homes using technologies such as IoT, big data, cloud computing, and machine learning, there is a constant risk of attacks such as Brute Force FTP, Brute Force SSH, Web Attack, Infiltration, and Botnet during data communication between individual terminals and the cloud server. Therefore, effectively identifying network communication data is essential to protect data communication security between individual terminals and the cloud server. Aiming at the data mentioned above regarding communication security issues, we propose an intelligent intrusion detection model NIDD (Network Intelligent Data Detection) model that combines deep convolution generation adversarial network (DCGAN) with Light Gradient Boosting Machine (LightGBM) and Shapley Additive exPlanations (SHAP). The NIDD model first generates new attack samples by learning the feature distribution of the existing attack sample data and effectively expands the rare attack samples. Secondly, we use the Light Gradient Boosting Machine (LightGBM) algorithm as the base classifier to train the dataset and start to build the intrusion detection model. Then use Shapley Additive exPlanations (SHAP) to analyze the contribution of the classification results, and adjust the model parameters according to the analysis results. Finally, we obtain the optimal model for the intelligent detection model of network intrusion. This paper conducts experimental tests on the NSL-KDD dataset. The experimental results show that the NIDD model built based on Light Gradient Boosting Machine can detect Brute Force FTP, Brute Force SSH, DoS, Heartbleed, Web Attack, Infiltration, Botnet, PROBE, R2L, and U2R attacks with an accuracy of 99.76%. Finally, we re-verified the NIDD model on the CIC-IDC-2018 dataset. The results once again proved that the NIDD model could solve the data communication security between the nursing robot and the cloud server and the data before the IoT terminal and the cloud server. Communication security provides a sufficient guarantee.

Design and QoS Optimization Model of Party Building Cloud Platform Based on FoRTAN

Using FoumNPowERsTAⅡoNv4. o to develop a simulation program is the core focus of this paper. It has a good wlND0ws interface, which can intuitively and conveniently carry out a man-to-machine dialogue, which is convenient for simulation racing. Its application example shows that the program has universality and practicability. The informatization work of party building in colleges and universities can be carried out according to different situations: confidential work can be combined with the campus informatization platform; collaborative work between units can introduce third-party questionnaires and cloud collaboration documents to connect the data communication network with information. Intranet integration and unified deployment. With the growth of communication data volume, higher requirements are put forward for the quality of service of converged network QoS and the resource consumption of base stations and users.

Accelerated IoT Anti-Jamming: A Game Theoretic Power Allocation Strategy

A jamming combating power allocation strategy is proposed to secure the data communication in IoT networks. The proposed strategy aims to minimize the worst case jamming effect on the intended transmission under multi channel fading and total power constraints by modelling the problem as a Colonel Blotto game Nash Equibrium (NE). Both Logistic Regression as well as a specifically designed algorithm are used to iteratively and rapidly obtain the equilibrium strategy. The conducted theoretical derivations and Monte Carlo simulations confirm that the proposed approach can secure the IoT network with a limited amount of power and with a number of iterations that is much reduced compared to state-of-the-art techniques.

Performance analysis and evaluation of distance vector and link state routing protocols over a large area networks

Routing protocols are extremely important incredibly significant in data communication and computer networks. The high performance, reliability, stability, and security of the networks depend primarily on choosing the best type of dynamic routing protocol. In this paper, we evaluate and investigate the network performance for routing information protocol (RIP), enhanced interior gateway routing protocol (EIGRP), open shortest path first (OSPF), and intermediate system-to-intermediate system (IS-IS) routing protocols with three different scenarios of routes failure using the optimized network engineering tools (OPNET) simulator to determine which of the protocols is the most appropriate and effective in achieving high network performance. The results show that for large area networks, the EIGRP routing protocol gives the best network performance when all network routers are working with no failing, but when some network routers were failing to work and path failure is happening, the IS-IS link-state routing protocol works efficiently and gives the best performance. The obtained results for IS-IS protocol when failing seven routers is as: the hypertext transfer protocol (HTTP) page response time is (247.8 msec), voice delay variation is (4.19 µsec) , video delay variation is (8.83 µsec) and ping request and response time is (115 msec).

Fault Detection for Semi-Markov Switching Systems in the Presence of Positivity Constraints.

The fault detection issue is investigated for complex stochastic delayed systems in the presence of positivity constraints and semi-Markov switching parameters. By choosing a mode-dependent fault detection filter (FDF) as a residual generator, the corresponding fault detection is formulated as a positive [Formula: see text] filter problem. Attention is focused on the design of a mode-dependent FDF to minimize the error between the residual signal and the fault signal. The designed FDF features good sensitivity of the faults and robustness against the external disturbances. Subsequently, by means of the linear copositive Lyapunov functional (LCLF), stochastic stability is proposed to satisfy an expected [Formula: see text]-gain performance. Some solvability conditions for the desired mode-dependent FDF are established with the help of a linear programming approach. Finally, an application example of a data communication network model is provided to demonstrate the effectiveness of the theoretical findings.

РОЗВИТОК ЕЛЕКТРОННОЇ КОМЕРЦІЇ ТА ПОНЯТТЯ ЕЛЕКТРОННОГО ДОГОВОРУ

Article considers the concept of E-Commerce and E-Contract, their essence and content. Main types of E- Commerce and factors influencing the development of E-Commerce are presented. The conclusion of the contract in electronic form is defined by law, but still needs more circumstantiation, because legal framework is still quite cumbersome and is in the process of continuous improvement. Today, the development of E-Commerce promotes rapid access to information and resources, becomes highly profitable form of commodity-money relations, and therefore must be actively implemented and carry out a kind of revolution. Digital technologies and information communication networks are gradually becoming a part of everyday life and playing an important role in development of business and national economy overall. Electronic commerce is the most important component of electronic business. Emergence and fast growth of electronic business all over the world results from a variety of reasonable conditions and preconditions. Electronic form of information presentation is the documentation type that enables reproduction of the information in the visual form acceptable by the reader. One of the risk management means in course of any electronic commerce transactions is conclusion of contracts (agreements) by telecommunications. Upon adoption of the Law of Ukraine “On electronic commerce”, the legislation has coordinated the particular aspects governing conclusion of electronic contracts (individual issues have been coordinated by the Law of Ukraine “On electronic documents and document flow” and “On electronic signature.)” The article details the conditions of electronic contract conclusion, the procedure of use of the electronic signature for electronic contracts, identifies the ways to improve development of electronic commerce and electronic contracts and the procedure of use of the above. The special objective of the research has been to determine how electronic commerce and electronic business may be used to foster sustainable development and generally to facilitate the economic relations of Ukraine, as well as how electronic ecommerce affects the economic law of Ukraine.

Evaluation of Differentiated Services Policies in Multihomed Networks Based on an Interface-Selection Mechanism

Quality of service metrics and differentiated service mechanism policies are the most important criteria to deliver essential Internet requirements, especially during user handover, due to the rapid growth of users, multimedia applications, and traffic. DiffServ routers provide per-hop behaviors to manage traffic for services, whereas their policies have been applied to several types of Internet traffic, such as hypertext transfer protocol, file transfer protocol, and content-based routing. Multihoming aims to improve the reliability, scalability, and performance of data communications networks. This paper evaluated DiffServ various policies compared in a systematic manner (in two stages) over the multihomed networks to utilize and adopt the best policy for communicating packets, and enhanced the overall performance in terms of throughput, end-to-end latency, and processing time. Moreover, the paper introduced an interface-selection technique for multihomed nodes to select a proper interface, which provides the best services and links the behaviors that this interface yields. The overall results showed how the introduced multihoming-based interface-selection mechanism managed to maintain communication with the multihomed node. Furthermore, our results showed that the DiffServ time-sliding window with a three-color marking policy achieved the best system performance compared with the remaining policies.

Information security in intelligent mass transit management systems

Aim. The paper examines matters related to the definition of the architecture and requirements for data communication networks as part of intelligent mass transit management systems. Methods. The paper suggests a network architecture using multiprotocol label switching (MPLS) technology and traffic routing. If the core of a local area network is implemented using fully-connected topology, the use of flow labels allows predefining information exchange routes between servers and applications of an information and telecommunications network (ITS). Multiprotocol label switching (MPLS) is the foundation of control and information acquisition networks of ITS. That allows adopting common interfaces to the subsystems that perform various functions within an ITS, e.g., control and diagnostics, minimizing the time of information delivery to management servers and sending critical control commands, as well as using common Ethernet or 4G/5G wireless interfaces. Conclusions. The path installation/removal principle, when applied to critical facilities, significantly complicates attacks and collection of information on the network structure of ITS.

Signal Optimization of Electronic Communication Network Based on Internet of Things

In order to solve the problem that many people communicate at the same time, there are many external interference factors, and the signal is prone to instability in the process of electronic communication, the author proposes a signal optimization method for electronic communication network based on the Internet of Things. The method takes the cloud trust mechanism as the dynamic evolution trust relationship between various Internet of Things electronic communication services, performs explicit and implicit uncertainty conversion, calculates the objective function of data communication network performance, and confirms the control strategy. The positioning information of the network nodes in the communication is added to the communication data packet, and the most stable electronic communication path in the network is obtained to form the network topology structure. The Krasovsky method is adopted, and the working state of the nodes of the communication network is divided into the congested state and the normal state, the probability of the two is calculated, and the range of the transition balance is determined, so as to realize the optimization of the stability of the network topology. Experimental results show that the transmission rate of this method has been maintained at about 180 Kb/s; although there is fluctuation, the fluctuation value is small and the transmission rate is very stable. Conclusion. It can improve the accuracy of electronic communication of the Internet of Things and is less affected by external interference factors, and the communication transmission rate is faster.

Rank and Wormhole Attack Detection Model for RPL-Based Internet of Things Using Machine Learning.

The proliferation of the internet of things (IoT) technology has led to numerous challenges in various life domains, such as healthcare, smart systems, and mission-critical applications. The most critical issue is the security of IoT nodes, networks, and infrastructures. IoT uses the routing protocol for low-power and lossy networks (RPL) for data communication among the devices. RPL comprises a lightweight core and thus does not support high computation and resource-consuming methods for security implementation. Therefore, both IoT and RPL are vulnerable to security attacks, which are broadly categorized into RPL-specific and sensor-network-inherited attacks. Among the most concerning protocol-specific attacks are rank attacks and wormhole attacks in sensor-network-inherited attack types. They target the RPL resources and components including control messages, repair mechanisms, routing topologies, and sensor network resources by consuming. This leads to the collapse of IoT infrastructure. In this paper, a lightweight multiclass classification-based RPL-specific and sensor-network-inherited attack detection model called MC-MLGBM is proposed. A novel dataset was generated through the construction of various network models to address the unavailability of the required dataset, optimal feature selection to improve model performance, and a light gradient boosting machine-based algorithm optimized for a multiclass classification-based attack detection. The results of extensive experiments are demonstrated through several metrics including confusion matrix, accuracy, precision, and recall. For further performance evaluation and to remove any bias, the multiclass-specific metrics were also used to evaluate the model, including cross-entropy, Cohn’s kappa, and Matthews correlation coefficient, and then compared with benchmark research.

Performance Adjustable Event-Triggered Synchronization Policies to Nonlinear Multiagent Systems

This article designs performance adjustable event- and self-triggered policies for nonlinear multiagent systems with controller output fluctuations. In the provided event-triggered mechanism, a performance adjustable function is introduced, which can freely adjust the system sampling frequencies and state convergence rates. In the proposed self-triggered policy, continuous measurement error monitoring and neighbors’ event listening are avoided, thereby further saving system sensor resources. Furthermore, under a unified framework, the controllers’ inherent nonlinearities and the influence of data quantization in digital communication networks are studied. In comparison with the previous event-triggered sampling schemes, the developed policies do not only study the multiagent coordinated control in terms of system sampling performance and state convergence performance but are also suitable for the scenarios with controller output fluctuations. Numerical simulation results verify the effectiveness and superiority of the proposed policies.

Secure framework for IoT technology based on RSA and DNA cryptography

BackgroundThe Internet of things (IoT) is the network of different objects or “things” containing sensors, software, and other technologies used to exchange data between devices and systems over the cloud. Such systems and networks should be provided with a proper cryptographic methodology to block unauthorized data transmission access. This issue is considered an essential challenge of resources that are shared on the data communication network, that is its security. So, in this study, a cryptosystem is proposed to maintain the security level of such systems with a new idea depending on DNA cryptography and DNA mixing.ResultsIn this study, the proposed cryptosystem is based on the RSA algorithm and DNA cryptography concepts with a novel idea for mixing DNA strands obtained from encoding medical image and report to enhance the security level through the IoT networks. This system achieved a proper result in reconstructing images with high quality. The similarity between the original data and the restored one reached 92% through 18 s.ConclusionsSuch a proposed cryptosystem provided the feasibility of data security in network security, especially for E-health care through IoT system to help medical teamwork in handling medical data between hospitals safely. The result showed that RSA is a fast, efficient algorithm that can be utilized safely in cryptography schemes.