Network Management System Research Articles

Automatic Sensing and Measuring Technique for Power Metering

The growing demand for electricity has set higher requirements for the sensing and measurement system of smart distribution network. Therefore, a new state monitoring technology for power metering is proposed based on automatic sensing and measuring technique to improve power metering. Firstly, the influence of various physical conditions and natural environment is analyzed on power metering equipment. Then, internal detection is used to detect the operation state of the equipment. Secondly, DC (direct current) magnetic bias is detected by self-excited fluxgate. Furthermore, the working condition of the secondary circuit is tested by the secondary circuit current measurement method. Finally, the narrowband Internet of Things technology is adopted to conduct data communication with the terminal platform. The research results show that compared with the traditional online operation state detection and management system of smart distribution network, the innovative state monitoring technology can additionally monitor the temperature, DC magnetic bias and secondary circuit of the distribution network. This shows that improved monitoring technology based on automatic sensing and measuring technique can monitor the important state of the distribution network to reduce the risks caused by the inability to detect potential problems and improve the performance of the distribution network. The optimized state metering technology makes an example for the improvement of automatic sensing and measuring technique of the metering equipment of smart distribution network nationwide.

Study on the Steps and Conditions of Computerization of Teaching Management in Colleges and Universities

With the rapid development of information technology, the educational administration of colleges and universities must set up a set of standardized computer network management and quality service system on the platform of network technology. This is the key to improve the efficiency of school management and ensure the quality of teaching. The operation center of colleges and universities is teaching management, which is directly related to the survival, development and status of a university in the competition of contemporary society. Teaching management, in the final analysis, is the management of comprehensive information resources such as students, teachers’ teaching plans, teaching materials and so on. Nowadays, the wide application of computer information processing technology provides a powerful means to improve the teaching management in colleges and universities. At the same time, traditional manual management methods are facing the fate of being eliminated. Therefore, teaching management must be modernized and scientific, and the key is to establish a computer management system to achieve computerization of management. How to conduct teaching management under network conditions, provide students with various relevant information in a timely and effective manner, and establish students and students. At present, in the teaching management of major colleges and universities, it is an urgent task to make good connections between teachers and students.

Telematics-Based Traffic Law Enforcement and Network Management System for Connected Vehicles

This article introduces a telematics-based traffic law enforcement and management system (SLEM), which leverages connected vehicle and telematics technologies. The system assigns each driver a real-time score that measures her/his driving performance. Using these driver scores, SLEM then adopts a personalized route guidance strategy that favors high-performing drivers by guiding them to less congested routes at the expense of low-performing drivers who are directed to alternative, slower routes. This routing strategy shifts the network traffic distribution pattern from the undesirable user equilibrium pattern to the system optimal pattern. Hence, SLEM not only incentivizes drivers to improve their driving performance but it also provides a mechanism to manage network congestion. A bilevel mathematical program and an efficient solution methodology were developed to derive SLEM's optimal routing strategy. A set of experiments that was conducted to evaluate the performance of SLEM under different operation scenarios showed that the adoption of SLEM's routing strategy reduced travel time during recurrent congestion situations by about 5%.

Online Blended Learning in Small Private Online Course

In this work, we studied the online blended learning model of computer network experimentation, focusing mainly on the problem of traditional network experiments being limited by location and time, and explore the applicability of the small private online course (SPOC) advanced teaching concepts to computer network online experiment teaching. Based on the structure of a combination of virtual and real, real and not virtual, an online network experiment platform and management system has been designed and constructed, enabling students to carry out remote online computer network hardware experiments anytime and anywhere, without being restricted by time, space, or content. Using the online network experiment platform, we can organize the experimental modules and knowledge points via the SPOC course concept, by developing online network experimental content, modularizing and fragmenting of the experiments, creating the pre-experimental explanation and experiment preview videos, and evaluating the assignments via peer grading to analyze students’ learning behavior. By exploring online network experimental teaching methods and management models, offering experimental guidance in an interactive manner, and highlighting the openness and sharing characteristics of online experimental teaching platforms, we can improve the utilization rate for teaching resources, and provide ideas for applied scientific research methods.

Bayesian bootstrapping in real-time probabilistic photovoltaic power forecasting

Modern distribution systems are characterized by increasing penetration of photovoltaic generation systems. Due to the uncertain nature of the solar primary source, photovoltaic power forecasting models must be developed in any energy management system for smart distribution networks. Although point forecasts can suit many scopes, probabilistic forecasts add further flexibility to any energy management system, and they are recommended to enable a wider range of decision making and optimization strategies. Real-time probabilistic photovoltaic power forecasting is performed in this paper by using an approach based on Bayesian bootstrap. Particularly, the Bayesian bootstrap is applied to three probabilistic forecasting models (i.e., linear quantile regression, gradient boosting regression tree and quantile regression neural network) to provide sample bootstrap distributions of the predictive quantiles of photovoltaic power. The heterogeneous nature of the selected models allows evaluating the performance of the Bayesian bootstrap within different forecasting frameworks. Several benchmarks and error indices and scores are used to assess the performance of Bayesian bootstrap in probabilistic photovoltaic power forecasting. Tests carried out on two actual photovoltaic power datasets for probabilistic forecasting demonstrates the effectiveness of the proposed approach.

Statistical Model for Mobile User Positioning Based on Social Information

In spite of the vast set of measurements provided by current mobile networks, cellular operators have problems pinpointing problematic locations because the origin of such measurements (i.e., user location) is usually not registered. At the same time, social networks generate a huge amount of data that can be used to infer population density. In this work, a data-driven model is proposed to deduce the statistical distribution of connections, exploiting the knowledge of network layout and population density in the scenario. Due to the absence of GPS measurements, the proposed method combines data from radio connection traces stored in the network management system and geolocated posts from social networks. This information is enriched with user context information inferred from data traffic attributes. The method is tested with a large trace dataset from a live Long Term Evolution (LTE) network and a database of geotagged posts from social networks collected in real-time.

Design and Implementation of Network Monitoring System for Campus Infrastructure Using Software Agents

In network management and monitoring systems, or Network Management Stations (NMS), the Simple Network monitoring Protocol (SNMP) is normally used, with which it is possible to obtain information on the behavior, the values of the variables, and the status of the network architecture. network. However, for large corporate networks, the protocol can present latency in data collection and processing, thus making real-time monitoring difficult. This article proposes a multi-agent system based on layers, with three types of agents. This includes the collector agent, which uses a Management Information Base (MIB) value to collect information from the network equipment, an input table of information from the network devices for the consolidator agent to process the collected data and leave it in a consumable format, and its subsequent representation by the application agent as a web service, in this case, as a heat map.

Implementation of End to End Automation for BTS commissioning using Python

Network Management Systems (NMSs) are the innovative products used by telecommunication companies to monitor, control, analyze and manage telecommunication networks. Base Transceiver Station (BTS) is a network element which facilitate wireless communication between user equipment and network. BTSs can be integrated with NMS and all related applications available in NMS can be used over BTS. One such application is software upgrade or downgrade in BTS which is termed here as BTS commissioning. This BTS commissioning process involves multiple steps to be performed for successful software upgrade or downgrade in BTS manually through NMS. In this paper methodology to implement end to end automation of BTS commissioning using python is discussed. GUI is developed using JavaScript, jQuery, Flask, Python, HTML and CSS. The reason for using Python for this website is because it is powerful, simple and has many libraries. Developed feature is tested by integrating a test BTS with Nokia’s NMS named NetAct.

Application RFID and Wi-FI Technology in Design of IOT Sensor Terminal

In this paper, the author studies on the design of picking robot using IOT sensor terminal based on RFID and Wi-Fi Technology. It provides comprehensive information for scientific research, this paper designs a precision agriculture information perception system based on automatic picking robot. The whole system consists of wireless sensing network, transmission node, GPRS and upper computer management system. The wireless sensing network is composed of sensing terminal and sensing module, and connected through standard interface. The system can sense the information of crop growth environment and crop physiology in real time. And the data is reliably transmitted to the upper computer management system. The upper computer management system first processes the data, writes the data into the database, and displays and publishes the data online through the web system. Long time running test shows that. The system performance is stable and reliable.

Monitoring and Analysis of Honeypot System Performance using Simple Network Management Protocol (SNMP)

Abstract – Installation of the honepot sensor on Raspberry Pi device integrated with Modern Honey Network(MHN) is a DSSDI UGM action to see the threats of existing public Network, so it can be preventive action. But theinstalled Honeypot sensors sometimes have problems in the form of overload on the System so that data attacks arenot recorded. It is necessary to develop a monitoring System on the Honeypot System to monitor and manage Systemresources and to analyze Honeypot data needs. System monitoring which is one of the Network Management System(NMS) functions can be implemented with Simple Network Management Protocol (SNMP) to monitor theperformance of Honeypot sensor devices. From monitoring the Honeypot System shows the Honeypot sensor deviceoverloaded in memory. In addition, from the monitoring is seen the influence of the number of attacks on Systemperformance.
 Keywords - Honeypot, Modern Honey Network (MHN), Network Management System (NMS), Simple NetworkManagement Protocol (SNMP)

DESIGN DECISIONS TO STRENGTHEN THE ECONOMIC SECURITY AT NETWORK STRUCTURES IN THE FOCUS OF MODERN CHALLENGES AND THREATS

Crisis processes in the development of enterprises of network structures are caused, first of all, by inefficiency of management. In this regard, in response to modern challenges of economic development, network management systems are being transformed, and innovative, non-traditional approaches to management are gaining popularity. One of them is the project approach. Its application in the management system of the organization leads to their transformation, which directly affects, including the management of economic security. Therefore, in modern conditions, this control subsystem also requires restructuring using the tools of the design approach. However, in practice this is difficult to do due to insufficient formation of the relevant scientific and methodological apparatus. The article examines the substantive characteristics of the concept economic security, as well as substantiates the application of project approach in the context of strengthening the economic security at network structures. On the basis of which the ratio the main components of economic security of enterprises at network structures and procedures of the project approach is offered. A comprehensive study of the types matrix structures. The algorithm of providing an effective combination of process and project activity of enterprises at network structures with the separation of certain stages is substantiated. Summarizing the above, we note that the proposed methodology allows to adapt the process of economic security taking into account all its components on the basis of traditional methodology (threat detection, assessment, response, monitoring) to the project approach (achieving the goal in limited resources), which allows you to take full advantage for the activities of the enterprise in the context of effective regulatory and legal functioning. The system of indicators allows monitoring of threats and countermeasures based on the applied organizational structure. Keywords: economic security of enterprises at network structures, project approach, process approach, structure of enterprises, matrix structures.

TRANSPORT INFRASTRUCTURE AS A FACTOR OF THE EU COUNTRIES' ECONOMIC DEVELOPMENT

Introduction. The driving force behind the economic development of the regions and the countries-members of the European Union is modern transport infrastructure. For this reason, to draw up the level with the countries of Western Europe, there is funding for the countries of the former socialist bloc in the construction and modernization of road routes. The purpose of the article is studying the condition of road infrastructure in the EU and, in particular, Poland as a factor in the economic development of countries and regions. Results. The article analyzes the current development of road infrastructure in Europe and, in particular, Poland and the implementing investments for this purpose. The Regulations of the General Director for National Roads and Motorways as well as legal acts concerning this issue were analyzed. The prospects for the development of Polish road engineering till 2030 were indicated. The types of roundabouts on motorways built in the EU countries are presented. Scientific articles on the situation of EU countries in the field of road infrastructure have proven to be important sources of information. However, the most important source when it comes to road infrastructure in Poland turned out to be materials of General Directorate for National Roads and Highways, in which all national road programs are described. Conclusions. The authors justify that each year Poland is getting closer to the Western countries of EU on the level of road infrastructure development. The main reason for the increase in the level of road infrastructure in Poland is the projects of the General Directorate for National Roads and Highways, as well as the National Road Construction Program for the years 2014-2023 (with a perspective till 2030) and the National Road Traffic Management System for TEN-T networks, which will have a significant impact on economic growth and the comfort of movement of the society. Keywords: road infrastructure, economic development, Trans-European Transport Network, sustainable transport development strategy.

Design and implementation of the data acquisition system of a large scale network based on four-in-one meters

For households, water supply, power supply, pipeline gas and centralized heating are necessaries to maintain the normal life of a family. For Chinese urban families, water, electricity, gas, warm services are often provided by different government utility companies. Aimed at the shortage of the manual measurement of the above mentioned services‘ consumptions, a new mechanism using network metering devices is proposed in this paper. Based on the general network measurement mechanism and through analysis, this paper proposes using meter communication network as the public communication network of various metering devices, forming wireless mesh network by metering devices, constituting a virtual private network by the power company's network, and accessing to metering network based on SCEP protocol and certificates of devices. Under this new network measurement mechanism, a network routing optimization strategy, a data acquisition protocol based on IPv6 and a mesh network management system are designed, and preliminary experiments have been carried on. Experimental results show that the proposed mechanism can realize functions through the network, including the control of multi-measuring devices, topology discovery, data acquisition, fulfilling the multi-meter data acquisition system via network.

Implementation of a decentralized real-time management system for electrical distribution networks using the internet of things in smart grids

Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.

The Automatic Observation Management System of the GWAC Network. I. System Architecture and Workflow

The Ground Wide Angle Camera Network (GWAC-N) is a network of robotic multi-aperture, multiple field-of-view (FoV) optical telescopes. The main contingent of GWAC-N instruments are provided by the Ground Wide Angle Cameras Array (GWAC-A), and additional, narrower FoV telescopes are utilized to provide fast multi-band follow-up capabilities. The primary scientific goal of the GWAC-N is to search for optical counterparts of gamma-ray bursts that will be detected by the Space Variable Object Monitor (SVOM) satellite. The GWAC-N performs many additional observing tasks including follow-up of Target of Opportunities (ToO) targets and the detection (and monitoring) of variable objects and optical transients. To handle these use cases (and to allow for extensibility), we have designed ten observation modes and 175 observation strategies, including a joint strategy with multiple GWAC-N telescopes for the follow-up of gravitational wave (GW) events. To perform these observations, we develop an Automatic Observation Management (AOM) system capable of performing object management, dynamic scheduling, automatic broadcasting across the network, and image handling. The AOM system combines the individual telescopes which comprise the GWAC-N into a network and smoothly organizes all associated operations, completely meeting the requirements dictated by GWAC-N. With its modular design, the AOM is scientifically and technically viable for other general-purpose telescope networks. As the GWAC-N extends and evolves, the AOM will greatly enhance its discovery potential. In this first paper of a series, we present the scientific goals of the GWAC-N and detail the hardware, software, and workflow developed to achieve these goals. The structure, technical design, implementation, and performance of the AOM system are also described in detail. We conclude with a summary of the current status of the GWAC-N and our near-future development plan.

БЕСПРОВОДНЫЕ СЕНСОРНЫЕ СЕТИ В ЗАЩИЩАЕМЫХ ЗОНАХ

For military purposes, wireless sensor networks allow you to "link autonomous systems" into acomplex that has the property of self-organization, when objects "know" how to find each other andform a network, and in the event of a failure of any of the nodes can establish new routes for transmittingmessages. It is possible to achieve the desired efficiency of such complexes, mainly by improvingthe intellectual component of their control system in general and individual node in particular.However, it should be noted that the vast majority of research in this area remains at the theoreticallevel. The goal is to: 1) the study and development of algorithms for network design with mobilenodes and their possible failures due to the combat mission; 2) the study and development of site usesensor network to collect, analyze, and transmit data about the situation and decision-making in thearea of responsibility; 3) to offer relatively simple algorithms for giving the network node the property of intelligent behavior under the conditions of restrictions on power consumption and speed.It is shown that the required algorithms can be developed if the classes of typical situations andsuccessful methods of action in real conditions are identified. On this basis, it becomes possible todevelop formal models (patterns) for implementation in the node management system. A two-levelstructure of an intelligent network management system is proposed. The upper level, implementedby the operator, corresponds to such properties as survival, security, fulfillment of mission obligations,accumulation and adjustment of the knowledge base in the form of effective behavior patterns.The object of control for it is the network, considered as a functional system.

A Two-Stage Protection Method for Detection and Mitigation of Coordinated EVSE Switching Attacks

The new surge of interest towards mass integration of Electric Vehicles (EVs) in distribution smart grids can expose the high-voltage grid to instability conditions, for instance, through cyber threats initiated from the residential or public EV Supply Equipment (EVSE). This paper (i) investigates the impact of switching attacks on EV charging infrastructure and their impacts on the inter-area stability of the transmission grid, and (ii) proposes a two-stage detection and mitigation technique for those attacks. Initially, we demonstrate that leveraging the existing vulnerabilities in charging stations' cyberspace and the topology of the grid, an adversary can switch the injected or absorbed power of EVs with inter-area frequency and cause a blackout by destabilizing the angular speed of the grid's generators. Then, a Back Propagation Neural Network (BPNN) scheme is designed and hosted at the central management system (CMS) of a public EVSE network. Using this BPNN scheme, the switching attacks are accurately detected by analyzing the features of charging/discharging requests. Moreover, the detected attacks are mitigated by delaying or discarding the request execution. Finally, to cope with the conditions where the residential chargers are under-attack, or when the BPNN fails to provide accurate detection, a wide area H <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sup> controller is designed to keep the angular speed of the synchronous generators within the acceptable limits. The effectiveness of the proposed techniques is evaluated using two-area Kundur and 5-area Australian grids.

Monitoring and diagnostic technologies using deep neural networks for predictive optical network maintenance [Invited

In recent years, optical networks have become more complex due to traffic increase and service diversification, and it has become increasingly difficult for network operators to monitor large-scale networks and keep track of communication status at all times, as well as to control and operate the various services running on the networks. This issue is motivating the need for autonomous optical network diagnosis, and expectations are growing for the use of machine learning and deep learning. Another trend is the active movement toward reducing capital expenditure (CAPEX)/operational expenditure (OPEX) of optical transport equipment by employing whitebox hardware, open source software, and open interfaces. In this paper, we describe in detail the concept of a series of workflows for the whitebox transponder, including getting optical performance data from the coherent optical transceiver, diagnosing optical transmission line conditions by applying deep neural networks (DNNs) to the collected data, and notifying the remote network management system (NMS) of the diagnosis results. In addition, as one of the use cases, we demonstrate fiber bending detection based on the diagnosis workflow. Offline and online demonstrations show the deployed diagnosis system can identify the fiber bend with up to 99% accuracy in our evaluation environment.

Risk Constrained Energy Efficient Optimal Operation of a Converter Governed AC/DC Hybrid Distribution Network With Distributed Energy Resources and Volt-VAR Controlling Devices

Increasing penetration of direct current (dc) based distributed energy resources and dc loads in the conventional alternating current (ac) network necessitate the deployment of ac/dc hybrid distribution networks (HDNs). In view with the development of advanced energy management policy for ac/dc HDNs, unlike previous literatures, this article proposes a risk constrained energy efficient management algorithm by merging load shifting (LS) and conservation voltage reduction (CVR) techniques. The optimization framework aims to simultaneously minimize both true and conditional risk or conditional value at risk values of the expected energy cost under uncertain solar power generation, load demand, and upper grid energy price. In contrast with the available stochastic optimization process, in this article, two-point estimation strategy is employed in place of Monte Carlo simulation for scenario generation from the probability density functions of the uncertain parameters to reduce computational exertion. The proposed centralized optimization framework is initially developed as mixed integer nonconvex programming but to avoid computation complexity, the nonlinear components are replaced by their linear counterparts. Later, a new solution process named successive mixed integer linear programming (s-MILP) is proposed to obtain the optimal decisions for deployment of LS and CVR through smart inverters and volt-VAR controlling devices. Efficacy of the proposed technique is demonstrated on modified IEEE 33 bus ac/dc HDN and the most energy efficient operation is found by merging LS and CVR. Simulation outcomes prove fast and near optimal convergence of the s-MILP compared to conventional second-order conic programming relaxed mixed integer convex programming and piecewise linearization based MILP. Further, to assess the impact of network size on the solution time and optimality, the proposed advanced distribution network management systems strategy is employed on 132 bus ac/dc HDN.

Edge-centric trust management in vehicular networks

A major objective of vehicular networking is to improve road safety and reduce traffic congestion. The experience of individual vehicles on traffic conditions and travel situations can be shared with other vehicles for improving their route planning and driving decisions. Nevertheless, the frequent occurrence of adversary vehicles in the network may affect the overall network performance and safety. These vehicles may behave intelligently to avoid detection. To effectively control and monitor such security threats, an efficient Trust Management system should be employed to identify the trustworthiness of individual vehicles and detect malicious drivers which is the major focus of this work. We propose a hybrid solution, which integrates Edge Computing and Multi-agent modeling in a Trust Management system for vehicular networks. The proposed solution also aims to overcome the limitations of the two commonly utilized approaches in this context: cloud computing and Peer-to-Peer (P2P) networking. Our framework has a set of features that make it an efficient platform to address the major security challenges in vehicular networks including latency, scalability, uncertainty, data accessibility, and malicious behavior detection. Performance of the approach is evaluated by simulating a realistic environment. Experimental results show that the proposed approach outperforms similar approaches from literature for various performance indicators.