Basic convergence theory for the network element method

A recent paper introduced the network element method (NEM) where the usual mesh was replaced by a discretization network. Using the associated network geometric coefficients and following the virtual element framework, a consistent and stable numerical scheme was proposed. The aim of the present paper is to derive a convergence theory for the NEM under mild assumptions on the exact problem. We also derive basic error estimates, which are sub-optimal in the sense that we have to assume more regularity than usual.

Distributed abstraction and verification of an installed optical fibre network

The management of wavelength routed optical mesh networks is complex with many potential light path routes and numerous physical layer impairments to transmission performance. This complexity can be reduced by applying the ideas of abstraction from computer science where different equipment is described in the same basic terms. The noise-to-signal ratio can be used as a metric to describe the quality of transmission performance of a signal propagated through a network element and accumulates additively through a sequence of such elements allowing the estimation of end-to-end performance. This study aims to explore the robustness of the noise-to-signal ratio metric in an installed fibre infrastructure. We show that the abstracted noise-to-signal ratio is independent of the observers and their location. We confirm that the abstracted noise-to-signal ratio can reasonably predict the performance of light-paths subsequently set in our network. Having a robust network element abstraction that can be incorporated into routeing engines allows the network management controller to make decisions on the most effective way to use the network resources in terms of the routeing and data coding format.

Descriptive model for distributed element synchronization digital radio networks of the IEEE 802.11s and IEEE 802.11p standards

Today, the basic radio communication standards for building self-organizing networks such as MANET, VANET and FANET are IEEE 802.11s and IEEE 802.11p. The link layer is responsible for establishing and conducting a communication session in these networks. It includes a variety of procedures, the main of which are synchronization procedures, random multiple media access, reserved media access and transmitter power control of network elements. Moreover, in digital radio communication networks of the IEEE 802.11 standards family, both centralized synchronization and distributed synchronization of such network elements are used. However, in digital radio networks of the IEEE 802.11s and IEEE 802.11p standards, the key procedure for establishing and conducting a communication session is the distributed synchronization of the network data elements. It should be noted that there is no descriptive model of distributed synchronization of the IEEE 802.11s and IEEE 802.11p standards digital radio communication network elements, taking into account these standards features. All elements of the IEEE 802.11s and IEEE 802.11p digital radio network send Beacons on a competitive basis. This occurs cyclically at the start of the repeating sync interval. In this regard, the occurrence of three events is possible: successful transmission of the synchronizing Beacon packet, its collision with a similar packet and a service or user data packet. To prevent (reduce) the number of collisions in a digital radio communication network, it is necessary to maintain a constant time difference between the internal time of all network elements. It is worth noting that maintaining a constant time difference for all digital radio communication network elements through guaranteed and timely sending of synchronizing Beacon packets is the main mechanism for distributed synchronization of such network elements. In the event that the calculated value of the time difference Toffsetni for one of the neighboring elements of the digital radio communication network does not coincide with the analogous value obtained in the past synchronization interval Toffsetni-1, then the correction of the own internal TTSF time of the IEEE 802.11s and IEEE 802.11p standards digital radio communication network element begins. The procedure for adjusting the network element internal time continues until the maximum value of this element internal time offset TMaxClockDrift is equal to zero. Also, to reduce or prevent collisions of synchronizing Beacon packets in the data transmission channel, each network element both initially, when entering the network, and immediately when collisions of synchronizing packets occur, Beacon selects and sets the timing parameters of synchronization so that they do not coincide with similar parameters of neighboring network elements. The developed descriptive model of the IEEE 802.11s and IEEE 802.11p standards digital radio communication network elements distributed synchronization includes algorithms for the such network elements functioning, adjusting the such elements intrinsic internal time, searching for an alternative value for the start time of a repeating synchronization interval and adjusting it. The presented model is applicable in the development of analytical and simulation models for assessing the IEEE 802.11s and IEEE 802.11p standards digital radio communication network performance, taking into account the distributed synchronization of such network elements.

SIMULATION OF THE BEHAVIOR OF A COMPUTER SYSTEM USING ARTIFICIAL NEURAL NETWORKS

The design and the implementation of the simulation model of a computer system (CS) using artificial neural networks (ANNs) are considered. The purpose of the implementation is to create the easy-to-learn and easy-to-implement simulation model that allows to simulate both normal and anomalous processes in computer systems. The developed simulation model is the software, which consists of various modules combined using principles of the client-server architecture, allowing to run the model in both centralized and distributed modes of operation. The model allows to simulate the behavior of the CS with various topologies: a star, a tree, and a combination of these topologies. The main elements of the model are implemented in the form of four modules that fulfill their specific roles: an agent that generates data; a passive network element that transmits data with possible delays and losses; an active network element that processes and transmits data arriving at it, and the core – the central element of the model that receives data and sends it to additional modules for analysis. The modularity provides a high potential for further modifications of the simulation model by adding new modules. Using the generative adversarial network-based data generation module in the model makes it possible to generate data required for modeling the behavior of the studied CS. Based on the calculation of the Euclidean distance between matrices of transition probabilities of initial and generated data, it is shown that processes generated using the developed simulation model have a similar behavior with real ones. The designed model can be used to study the work of a real CS, including the imitation of an anomalous behavior.

FORMALIZATION OF THE DESCRIPTION OF MONO-VIRAL EPIDEMIC PROCESSES IN NETWORKS

Рассматривается процесс распространения вирусной инфекции (компьютерной, психологической) в сетевой структуре в корпоративной, социальной сети. Предлагается обобщенная модель вирусования элемента сети с учетом дискретности его состояний (статусы восприимчивого к вирусу элемента, распространителя инфекции, иммунизированного элемента). Шаг моделирования (дискретного) сопоставим с инкубационным периодом. В этой связи рассматривается риск появления (в эпидемическом процессе) множества элементов сети различных (из вышеупомянутых) статусов на основе веерного представления процесса. По их количественной оценке прогнозируется эпистойкость сети в отношении рассматриваемого вируса. The process of spreading a viral infection (computer, psychological) in a network structure in a corporate, social network is considered. A generalized model of network element viralization is proposed, taking into account the discreteness of its states (statuses of a virus-susceptible element, an infection propagator, an immunized element). The step of modeling (discrete) is comparable to the incubation period. in this regard, the risk of occurrence (in the epidemic process) is considered) multiple network elements of different (from the above) statuses based on a fan representation of the process. According to their quantitative assessment, the epistability of the network with respect to the virus in question is predicted.

Modeling of network communication instability based on K-means algorithm

In order to overcome the problems of invulnerability and low communication efficiency when analyzing network communication instability with current methods, this paper proposes a modeling method of network communication instability based on K-means algorithm. The network element nodes are generated by clustering idea, and the initial communication topology is constructed. K-means algorithm is used to optimize the initial communication model, build a comprehensive mathematical model of network communication, and solve the model to realize the optimization of communication model. The network efficiency function is used to further quantify the network invulnerability, and the function is used to find the most vulnerable nodes in the network, and strengthen them to achieve efficient control of network invulnerability. The experimental results show that the model has strong invulnerability, up to 99.9%, high communication efficiency and coverage, and the maximum communication delay is only 0.35 s. It is a feasible network communication model.

A Simulator for Reporting Performance Data from Network Element To Network Management System

Now a days, the biggest challenge for Mobile Network Operators is to provide broadband service with high performance.4G(VoLTE) has been developed to meet user requirement by offering high speed data transfer services using IMS network. The key performance indicators (KPI) are used to monitor and optimize mobile network performance in order to provide high quality services using counters. The indicators are standardized by third-generation partnership project(3GPP). Simulators are used in network element so that we can check the capacity of each VM and calculated using counters from element management system to network management system.

Modelling Resilience of the Transport Critical Infrastructure Using Influence Diagrams

The article discusses the possible impact of disasters on functionality of the transport critical infrastructure elements by overcoming their resilience. The aim of the article is to provide an appropriate approach to the resilience measurement through understanding of this close relationship. It was achieved by using combination of (1) a decisiontheoretical approach based on Influence Diagrams, which was used as a tool to model functionality disruption level of transportation network elements after disaster impact and (2) the time decomposition of the functionality disruption duration of these elements. Based on this approach, the transportation network element resilience assessment was conducted in form of the transportation element resilience loss. The proposed approach is intended to be applied to the critical infrastructure elements rather than to the transportation network as a whole.

Research of the optimum scale of standard sections of agricultural purpose lines

In the article, for the optimal development of networks, the parameter of the network element is selected from the existing standard scale of standard sizes and the scale of standard sections of lines (cables) is optimized or their optimality is checked.