scholarly journals Blockchain Behavioral Traffic Model as a Tool to Influence Service IT Security

2020 ◽  
Vol 12 (4) ◽  
pp. 68 ◽  
Author(s):  
Vasiliy Elagin ◽  
Anastasia Spirkina ◽  
Andrei Levakov ◽  
Ilya Belozertsev
Keyword(s):  
Experimental Data ◽  
Present Article ◽  
Data Transmission ◽  
Behavioral Model ◽  
Traffic Model ◽  
It Security ◽  
Data Network ◽  
Network Characteristics

The present article describes the behavioral model of blockchain services; their reliability is confirmed on the basis of experimental data. The authors identify the main technical characteristics and features associated with data transmission through the network. The authors determine the network scheme, working with blockchain transactions and the dependence of network characteristics on application parameters. They analyze the application of this model for the detection of the blockchain service and the possibility of the existing security mechanisms of this technology being evaded. Furthermore, the article offers recommendations for hiding the blockchain traffic profile to significantly complicate its identification in the data network.

BEHAVIORAL MODEL OF A LINEAR VOLTAGE STABILIZER IN THE SPICE LANGUAGE

2019 ◽  
Author(s):  
Aleksey Malahanov
Keyword(s):  
Experimental Data ◽  
Behavioral Model ◽  
Voltage Stabilizer ◽  
Static Mode ◽  
Technical Description ◽  
Simulation Results ◽  
Chip Manufacturer ◽  
Linear Voltage

A variant of the implementation of the behavioral model of a linear voltage stabilizer in the Spice language is presented. The results of modeling in static mode are presented. The simulation results are compared with experimental data and technical description of the chip manufacturer.

THE CONCEPT OF MANAGING THE DATA NETWORK BASED ON SELF-LEARNING SYSTEMS

2020 ◽  
Author(s):  
С.Р. РОМАНОВ
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Data Transmission ◽  
Network Control ◽  
Learning Systems ◽  
Optimal Routing ◽  
Transmission Network ◽  
Data Traffic ◽  
Data Network ◽  
Self Learning

Рассмотрен принцип управления сетью передачи данных (СПД)с помощью искусственной нейронной сети. Предложена концепция проведения вычислений при решении задачи оптимальной маршрутизации трафика данных. Приведен алгоритм управления сетью СПД на базе нейронной сети Хэмминга. The principle of data transmission network control using an artificial neural network is considered. The concept of carrying out calculations when solving the problem of optimal routing of data traffic is proposed. The algorithm for controlling the data transmission network based on the Hamming neural network is presented.

scholarly journals Symmetric-in-Plane Compression of Polyamide Pantographic Fabrics—Modelling, Experiments and Numerical Exploration

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 693 ◽  
Author(s):  
Chuong Anthony Tran ◽  
Maciej Gołaszewski ◽  
Emilio Barchiesi
Keyword(s):  
Experimental Data ◽  
Present Article ◽  
Lattice Structure ◽  
Experimental Results ◽  
Fiber Density ◽  
Numerical Exploration ◽  
Peculiar Behaviour ◽  
Plane Compression ◽  
Pantographic Fabrics

Symmetric in-plane compression of a pantographic lattice structure is modelled and simulated, and the results are compared to previously available experimental data. Said experimental results had shown a peculiar behaviour: depending on the fiber density, the deformed shape could present either one or two swellings under compression. The present article is a preliminary modelling attempt aiming at capturing that behaviour numerically.

Control Method to Data Transmission for Different Structure Network

2011 ◽  
Vol 186 ◽  
pp. 581-585
Author(s):  
Ning Zhang ◽  
Mao Chang Ge
Keyword(s):  
Optical Fiber ◽  
Life Span ◽  
Data Transmission ◽  
Control Method ◽  
Optical Network ◽  
Network Control ◽  
Data Network ◽  
Transmission Properties ◽  
Data Rates ◽  
Long Life

There are many structure models in data network. To optical network, control method is important for different network. Optical fiber is the preferred medium for transmission for data rates larger than a few hundred megabits per second over distances more than tens of meters due to its near-perfect transmission properties, including low attenuation over a multi-terahertz bandwidth window, immunity from interference of most kinds, and requiring no maintenance over a very long life span. To date, no other technology has appeared on the horizon that can compete with these attributes. The transmission mode refers to the number of elementary units of information that can be simultaneously translated by the communications channel.

scholarly journals The Duals of Fusion Frames for Experimental Data Transmission Coding of High Energy Physics

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jinsong Leng ◽  
Qixun Guo ◽  
Tingzhu Huang
Keyword(s):  
Experimental Data ◽  
Data Transmission ◽  
High Energy Physics ◽  
Matrix Representation ◽  
High Energy ◽  
Fusion Frames ◽  
Fusion Frame ◽  
The Matrix ◽  
Frame System ◽  
Energy Physics

The experimental data transmission is an important part of high energy physics experiment. In this paper, we connect fusion frames with the experimental data transmission implement of high energy physics. And we research the utilization of fusion frames for data transmission coding which can enhance the transmission efficiency, robust against erasures, and so forth. For this application, we first characterize a class of alternate fusion frames which are duals of a given fusion frame in a Hilbert space. Then, we obtain the matrix representation of the fusion frame operator of a given fusion frame system in a finite-dimensional Hilbert space. By using the matrix representation, we provide an algorithm for constructing the dual fusion frame system with its local dual frames which can be used as data transmission coder in the high energy physics experiments. Finally, we present a simulation example of data coding to show the practicability and validity of our results.

Comparison and Inspiration of Bank Computer System and Power Dispatching Automation System in China

2013 ◽  
Vol 411-414 ◽  
pp. 1821-1825
Author(s):  
Mi Fang Yan ◽  
Mao Hua Shan ◽  
Chun Hua Yan ◽  
Zhi Yuan Gao ◽  
Wei Tian
Keyword(s):  
Computer System ◽  
Network Topology ◽  
Data Transmission ◽  
Banking Industry ◽  
Automation System ◽  
Data Network ◽  
Ip Over Atm ◽  
Power Dispatching Automation ◽  
Power Dispatching ◽  
Selection Of

The informatization development of banking industry and power dispatching automation system in China was introduced. The data transmission, the network level, the network topology and the selection of technical system for both were compared. The banking network more single tends to choose IP over ATM networking. The power dispatching data network includes two levels and every level is subdivided into three. IP over SDH networking is more suitable for it.

scholarly journals The influence of dependence on data network models

2008 ◽  
Vol 40 (1) ◽  
pp. 60-94 ◽  
Author(s):  
Bernardo D'Auria ◽  
Sidney I. Resnick
Keyword(s):  
Transmission Rate ◽  
Network Models ◽  
Dependence Structure ◽  
End User ◽  
Independence Assumption ◽  
Data Network ◽  
Network Characteristics ◽  
Network Applications ◽  
Peer To Peer Networks ◽  
Consecutive Time

Consider an infinite-source marked Poisson process to model end user inputs to a data network. At Poisson times, connections are initated. The connection is characterized by a triple (F, L, R) denoting the total quantity of transmitted data in a connection, the length or duration of the connection, and the transmission rate; the three quantities are related by F = LR. How critical is the dependence structure of the mark for network characteristics such as burstiness, distribution tails of cumulative input, and long-range dependence properties of traffic measured in consecutive time slots? In a previous publication (D'Auria and Resnick (2006)) we assumed that F and R were independent. Here we assume that L and R are independent. The change in dependence assumptions means that the model properties change dramatically: tails of cumulative input per time slot are dramatically heavier, traffic cannot be approximated by a Gaussian distribution, and the decay of dependence cannot be measured in the traditional way using correlation functions. Different network applications are likely to have different mark dependence structure. We argue that the present independence assumption on L and R is likely to be appropriate for network applications such as streaming media or peer-to-peer networks. Our conclusion is that it is desirable to separate network traffic by application and to model each application with its own appropriate dependence structure.

scholarly journals Fog-Cloud Computing Traffic Model Affecting the Occurrence of Latency on the Ubiquitous Sensor Network

2021 ◽  
Author(s):  
Chonnikan Sangmek ◽  
Nathaphon Boonnam
Keyword(s):  
Cloud Computing ◽  
Data Transmission ◽  
Fog Computing ◽  
Transmission Efficiency ◽  
Traffic Model ◽  
Packet Size ◽  
Internet Connection ◽  
Ubiquitous Sensor Networks ◽  
Different Characteristics ◽  
Main Factor

Abstract The fog-cloud computing traffic model overviews working elements in forming fog-cloud computing with three main layers: Ubiquitous Sensor Networks, Fog Computing, and Cloud Computing. We present a possible method of data transmission that focuses on either measuring or manipulating or both in the system divided into 7 USNs and using latency measurement to demonstrate transmission efficiency. This paper considers the latency test into four prominent cases: internet connection, traffic model, number of devices, and packet by equipment used for testing consisting of microcontroller board, sensor, actuator, and uses fog node two types: pocket Wi-Fi and router. In the latency test, we found that the factor causing the higher latency in the system was the packet size. The main factor consists of the different characteristics of working, fog nodes, and the number of connected devices. Therefore, the packet has correlated directly with the latency depending on the size of the packet increases. The resulting latency is the main factor affecting the work of the system.

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