Network Monitoring System Research Articles

Nagios Core Optimization By Utilizing Telegram as Notification of Disturbance

Network Monitoring System (NMS) is a system that is highly demanded internet service provider industry in this fast-developing information technology era. The availability of NMS is the best option to restore the service level agreement as a means to compete with other internet service providers’ competitors. The occurrence of disturbance in the network is often unnoticed by the network administrator. This may lead to a crucial problem in decreasing network quality as the impact of time-consuming in solving the problem. Through the explanation, the writer tried to anticipate by classifying problems using Pareto and integrated Nagios with Telegram Messenger as a notification of disturbance. Nagios has many features such as reports, event handlers, monitoring resources (CPU load, memory usage, status up / down, uptime, data traffic, bandwidth), etc. One notable feature owned by Nagios is blast notification of disturbance. It is a feature that will function when one of the devices is in trouble. This feature will inform the network administrator or authorized person in certain divisions as regards the error network. In this case, the problematic device can be categorized according to the parameters made by the network administrator.

Construction of a Power Quality Monitoring System Based on the Wavelet Transform Change-Point Detection Algorithm on the Virtual Instrument Platform

It is aimed to carry out the investigation on power quality detection, promote the realization of efficient transmission of network data, and expand the application of wavelet transform change-point detection algorithm in the monitoring system. The voltage deviation is used as a starting point to explore the detection of power quality. First, it describes the harmonics of the public power grid and the limits of harmonic voltage. Second, based on the virtual instrument platform, the power quality monitoring system based on wavelet transform change-point detection algorithm is completed. Finally, by adding a monitoring terminal and a service terminal, the design of the monitoring system server is completed. Through the analysis of the experimental results, it is found that in the monitoring system, the current waveform and the three-phase voltage can be accurately displayed. The combined design of the networked monitoring system and the system server enables the system to complete the rapid transmission of data related to power quality, while having a good monitoring effect. For the optimization of networked monitoring experienceof the server, the application of wavelet transform in power quality measurement is realized. The power quality monitoring system proposed has a strong practicality in power quality monitoring.

Design and application of intelligent monitoring and management system for campus weak current pipeline network based on IoT+GIS technology

In view of the characteristics and problems in the process of information construction and operation of the campus weak current pipeline network, combined with the actual needs of the development of smart campus, an intelligent monitoring and management system of the weak current pipeline network based on IoT+GIS technology is designed and the campus geospatial information database as well as the weak current pipeline network database are established at the same time. The three-dimensional visual integration management of weak current communication resources, such as underground pipeline laying, optical fiber routing analysis, fiber-optic fusion relationship, integrated wiring in the building, off-motion monitoring of well cover, and so on, is realized, which greatly improves the campus weak current pipeline network resources management and maintenance efficiency, and provides scientific decision-making basis for rational and effective use of these resources.

Research on wireless sensor network system for structural damage monitoring

In recent years, the application of wireless sensor networks in the field of structural monitoring has been widely concerned by experts and scholars in various countries. The throughput and real-time performance of the wireless sensor network should be considered when the structure health monitoring wireless sensor network is deployed. According to the characteristics and requirements of wireless structure damage monitoring, this paper analyzes the system from three aspects: monitoring system process, node design and damage diagnosis algorithm.

Data Management and Visualization of Coastal Railway in Wireless Sensor Network Monitoring System

Ji, X.R., 2020. Data management and visualization of coastal railway in wireless sensor network monitoring system. In: Al-Tarawneh, O. and Megahed, A. (eds.), Recent Developments of Port, Marine, and Ocean Engineering. Journal of Coastal Research, Special Issue No. 110, pp. 219–222. Coconut Creek (Florida), ISSN 0749-0208.With the continuous progress of industrialization in our country, machinery and equipment are developing to higher frequency and larger scale. How to automate and monitor is the key parts which are widely distributed and in bad working environment in machinery and equipment. Therefore, the realization of scientific life prediction and fault diagnosis is an important issue, which is widely concerned by the industry at present. This paper studies the fusion method of equipment information data and geographic information data in the wireless sensor network (WSN), and realizes the fusion of WSN sensing data based on the proposed development environment. Then, we establish the database model and parses the data file. In addition, we realize data visualization in web environment based on the Silverlight module. Finally, the visual part of the coastal railway monitoring WSN system established in this paper is tested by function test and performance test.

Network Monitoring System

Traffic analysis and monitoring is needed to improve network service quality by using statistical analysis to obtain traffic characteristics. These statistics provide important signals about service quality and network throughput. Because of the heterogeneity of the bandwidth requirements of the traffic flow resulting from different applications, the resulting data can be used to determine the nature of IP traffic and to consider its characteristics. The first data type is data available from the Simple Network Management Protocol (SNMP) to the network nodes. The second is from IP current monitoring. The combination of these two data types provides a solid foundation for traffic analysis and monitoring. Which in this case we will apply to Mikrotik, dude applications, Internet of Things, Social Media, Website, SNMP, Probe, Zabbix, Security Information and Event Management (SIEM).Monitoring results are displayed in graphical form on the Network Monitoring System Web Application, so that users can find out more information. The network monitoring system developed is also very effective because the packet sent in one transaction is very small, which is 309 bytes when compared to the larger SNMP protocol. The results of the configuration of hardware and software with Zabbix NMS went well with the success of monitoring the service by detecting status changes on each host with 2 ownership statuses Ok and Warning. The availability value is influenced by the Uptime and Downtime of a device. The greater the Uptime value, the greater the availability value. The availability test results show that the application made has an error rate of 0% when compared with the calculation results. Using a network monitoring system using the SNMP protocol on the Mikrotik router and dude application, can help in network management

Analysis of loss levels in a single mode fiber optic cable for some fiber plants in Northern Nigeria

Increasing demand for transmission capacity due to digital revolution is causing an increasing demand for optical fiber systems. However, as bit-error-rate (BER) increases the fiber optic cable signal quality becomes degraded, causing signal delays, jitters, poor quality of service, packet loss, link outage, etc. In this study, the analysis of loss levels in a single mode fiber optic cable was carried out using the optical time domain reflectometer (OTDR), network monitoring system (NMS) and CACTI (V 1.1.38). Various OTDR traces were carried out to determine the loss levels in the fiber cores. Similarly, using the NMS, the actual link losses were calculated and compared with the loss budget to derive the link loss margin of the links; with a benchmark loss margin of 5 dB, high and low loss levels were determined. Lastly, bandwidth utilization was carried out using network graphical solution software (CACTI, V 1.1.38). The results show that, from the OTDR traces, 60% of the tested fiber cores had high losses at the spliced joints, whereas the analysis of the NMS shows 41.7% high losses. The bandwidth utilization analysis shows a reduction in fiber link availability by 8.3%. This work has revealed the different loss levels in the tested fiber cores with high loses leading to increase in BER which negatively impacts the optimum usability of a link. Therefore, maintaining a low and within-budget loss level is very essential for efficient signal transmission and optimization of the fiber optic cable for both manufacturers and the end users.

Comparative study of wireless sensors for measuring the energy consumption of human running

With the rapid development of technologies such as communications, embedded computing, and sensors, wireless sensor network technology has become more mature and its applications have become more and more extensive. The development of technology has brought great convenience to people's lives and work. At the same time, people's activity and exercise are greatly reduced, causing health problems such as physical weakness. In this regard, designing a research based on wireless sensors to measure human walking and running is of great significance to promote the development of people's physical health. This paper presents a design scheme for human exercise energy consumption detection, researches and designs the coordinator, router node and host computer monitoring system of wireless sensor network. In the human motion energy consumption detection system implemented in this paper, the communication effect between the coordinator and the router node is good, and there are fewer problems such as node loss and data loss. The host computer monitoring interface is simple and easy to operate, easy to use, and can run stably. This solution does not need wiring, reduces the point of failure, reduces the cost, and has good scalability, laying a foundation for the further development of the human motion detection system, and has a wide range of application prospects and practical values. This paper is based on two constant beam width algorithms to carry out the experimental research on the energy consumption of human walking and running, and analyze the results of the energy consumption experiment. Experimental results show that the two constant beamwidth beamforming algorithms have relatively good constant beamwidth effect, which basically verifies the correctness of the theoretical analysis results and can be applied to target noise measurement.

Campus Intelligence Mental Health Searching System Based on Face Recognition Technology

The phenomenon of teenage campus suicide has become the focus of attention of parents, schools and the society. The causes behind it are extremely complicated, and the root cause is psychological and spiritual problems. However, one's negative psychology is often hidden, and it is difficult to detect and effectively intervene before the tragedy. How to effectively identify students with suicidal tendencies in order to prevent tragedies has aroused extensive research and discussion among the government, academia and the public. Through investigation and research, it is found that the current popular computer cutting-edge technologies such as artificial intelligence and computer vision can be well used for human emotion recognition and behavior prediction, and put into use in schools as a mental health auxiliary diagnosis and treatment system, thus effectively reducing the suicide rate on campus. The scenario assumes that machine learning can be used to deduce the risk of psychological problems in human samples by analyzing the frequency of negative emotions in facial expressions. Based on this, this paper proposes an effective solution for campus suicide prediction, and designs a set of auxiliary diagnosis and treatment system based on campus monitoring network system for suicide behavior prediction and student mental health analysis. Through preliminary experimental analysis and verification, the suicide psychological auxiliary diagnosis and treatment system has achieved good results in face recognition success rate, emotion recognition success rate and behavior prediction success rate. With the input of more experimental data and the increase of self-training time, the prediction system will perform better.

Learn-ing-Based On-AP TCP Performance Enhancement

Data transmissions suffer from TCP’s poor performance since the introduction of the first commercial wireless services in the 1990s. Recent years have witnessed a surge of academia and industry activities in the field of TCP performance optimization. For a TCP flow whose last hop is a wireless link, congestions in the last hop dominate its performance. We implement an integral data sampling, network monitoring, and rate control software-defined wireless networking (SDWN) system. By analysing our sampled data, we find that there exist strong relationships between congestion packet loss behaviors and the instant cross-layer network metric measurements (states). We utilize these qualitative relationships to predict future congestions in wireless links and enhance TCP performance by launch necessary rate control locally on the access points (AP) before the congestions. We also implement modeling and rate control modules on this platform. Our platform senses the instant wireless dynamic and takes actions promptly to avoid future congestions. We conduct real-world experiments to evaluate its performance. The experiment results show that our methods outperform the bottleneck bandwidth and RTT (BBR) protocol and a recently proposed protocol Vivace on throughput, delay, and jitter performance at least 16.5%, 25%, and 12.6%, respectively.

SELECTING NETWORK MONITORING SYSTEM SOFTWARE WITH ANALYTICAL HIERARCHY PROCESS METHOD

Nowadays there are lots of Network Monitoring System (NMS) software that are reliable and easy to use, such as CiscoWork, HP-OpenView, and IBM-Tivoli. It is just that the software is quite expensive, because it has classified as a commercial product. Fortunately, availability of NMS products is not limited to commercial, but also many other alternatives, namely products that classified as Free and Open Source Software (FOSS). Unfortunately, most of these FOSS products are not only difficult to implementation both in term of installation and configuration, but also limitations in the number of nodes and types of monitored, including network devices, servers, and applications. The method of selecting FOSS-based NMS software based on the Oyku Alanbay and ISO 7498-4 research methods through the Analytical Hierarchy Process (AHP) approach using the Expert Choice tool. Among GroundWork, Hyperic, Nagios, OpenNMS, and Zenoss, based on the results of this study put Nagios as a fair reliable software for monitoring networks, servers, and applications.

Nagios Core Optimization by Utilizing Telegram as Notification of Disturbance

Network Monitoring System (NMS) is a system that is highly demanded internet service provider industry in this fast-developing information technology era. The availability of NMS is the best option to restore the service level agreement as a means to compete with other internet service providers’ competitors. The occurrence of disturbance in the network is often unnoticed by the network administrator. This may lead to a crucial problem in decreasing network quality as the impact of time-consuming in solving the problem. Through the explanation, the writer tried to anticipate by classifying problems using Pareto, and integrated Nagios with Telegram Messenger as a notification of disturbance. Nagios has many features such as reports, event handler, monitoring resource (CPU load, memory usage, status up / down, up time, data traffic, bandwidth), etc. One of notable feature owned by Nagios is blast notification of disturbance. It is a feature that will function when one of the devices is in trouble. This feature will inform the network administrator or authorized person in a certain divisions as regards the error network. In this case, the problematic device can be categorized according to the parameters made by the network administrator.

PTP‐based time synchronisation of smart meter data for state estimation in power distribution networks

This paper develops a novel approach for distribution system monitoring and state estimation, where time synchronisation of smart-meter measurements is carried out via the Precision Time Protocol (PTP). The approach is based on the concept of a Modified Smart Meter (MSM), a distribution system monitoring instrument that enables accurate time synchronisation of smart meter data. The design, application, communication technique and protocols of the MSM are described in detail. The proposed MSM device features PTP-based time synchronisation of smart meter measurements, and the concept of unbundling is applied to collect measurements utilising the existing smart meter sensors. This is expected to reduce the overall implementation cost of an MSM-based distribution network monitoring system compared to a system based on Phasor Measurement Units (PMUs). The problem of requiring open sky access for GPS links can potentially be solved by means of PTP synchronisation. Three-phase state estimation simulations using the IEEE-13 and 123 bus unbalanced test networks are employed to demonstrate the applicability of the MSM, and its performance is compared to standard PMU devices. The results indicate that the MSM may represent a workable monitoring solution for MV and LV distribution networks, with an acceptable trade-off between cost and performance.

Supervised Machine Learning Classification Algorithmic Approach for Finding Anomaly Type of Intrusion Detection in Wireless Sensor Network

From the last decade, the use of internet and its growth is continuously increasing. Similarly, numbers of services are coming out along with the internet and it is being used for providing facilities to human beings. Wireless sensor have been used for various application such as fire safety, military application, petroleum industry, security system, monitoring and environmental condition and many more. WSN node exposes itself to various security related attacks due to low battery power supply, low bandwidth support, data transmission over multi hop node, dependency on intermediate or other nodes, distributed in nature and self-organization. The WSN attacks observe in all layers of OSI model. Wireless sensor nodes has various issues because of that, it experiences number problem related to its functionalities and some malfunction due to attacks. It is require to build defence and network monitoring system for identifying attacks and prevent them. Intrusion detection system (IDS) plays an important role to detect threads inside the system and generate the alert related to the attack. In this work, supervised classification models for intrusion detection are built using such as Random Forest classifier, Support Vector Machine, Decision Tree Classifier, LGBM Classifier, Extra Tree Classifier, Gradient Boosting Classifier, Ada Boost Classifier, K Nearest Neighbour Classifier, MLP Classifier, Gaussian Naive Bayes Classifier and Logistic Regression Classifier. The NSLKDD, i.e. Modified version of the KDD99 Data Set on which we checks these algorithms. Experimental results how the highest accuracy relative to other classification systems in the support vector machine.

Analysis of groundwater and river stage fluctuations and their relationship with water use and climate variation effects on Alto Grande watershed, Northeastern Brazil

Sustainable use of water resources on the behavior of groundwater table and surface water level variations, especially in phreatic sedimentary aquifers, where a strong interaction between stream flow and groundwater normally takes place. In the present study, precipitation, water level fluctuation, river flow and pivot installation data from an important agricultural frontier with an increasing water use for irrigated agriculture and a downward precipitation trend were compared with surface and water level fluctuation monitoring data. The main purpose was to assess possible impacts on the aquifers and to analyze the variation in groundwater table and surface water levels due to long-term downward precipitation trend (climate variation effects) and increasing water demand (irrigation). A growing number of central pivots installed for irrigation are withdrawing water from the Urucuia Aquifer System (UAS) in western Bahia State, Northeastern Brazil, one of the leading agricultural frontiers of the world. Field surveys provided hydrogeological aspects that led to the construction of a hydrogeological conceptual model. Monitoring groundwater and surface water through Brazilian Geological Survey's Integrated Groundwater Monitoring Network (RIMAS-CPRM), satellite images and Hydrological Information System (HidroWeb-ANA) network formed the databases for the study. This data was compared with rainfall data and evolution of irrigated areas captured by satellite image analysis. Results indicate that reduction of rainfall volumes from 1990 to 2018 in the headwaters of Alto Grande basin, due to cyclic droughts, and an increase in surface and groundwater exploitation due to flourishing agribusiness activity has caused a considerable groundwater level drawdown. The drawdown of up to 6.63 m points to the need of strong management actions, which should provide a long-term sustainable use of water resources (superficial and underground) within Alto Grande watershed. This study is part of the actions undertaken to provide the scientific and technical basis to secure the availability of water and a sustainable agricultural activity, since an important part of the Cerrado, the Brazilian savanna ecosystem, and considerable proportion of São Francisco river flow, lies in the study area.

Campus Intelligence Mental Health Searching System Based on Face Recognition Technology

The phenomenon of teenage campus suicide has become the focus of attention of parents, schools and the society. The causes behind it are extremely complicated, and the root cause is psychological and spiritual problems. However, one's negative psychology is often hidden, and it is difficult to detect and effectively intervene before the tragedy. How to effectively identify students with suicidal tendencies in order to prevent tragedies has aroused extensive research and discussion among the government, academia and the public. Through investigation and research, it is found that the current popular computer cutting-edge technologies such as artificial intelligence and computer vision can be well used for human emotion recognition and behavior prediction, and put into use in schools as a mental health auxiliary diagnosis and treatment system, thus effectively reducing the suicide rate on campus. The scenario assumes that machine learning can be used to deduce the risk of psychological problems in human samples by analyzing the frequency of negative emotions in facial expressions. Based on this, this paper proposes an effective solution for campus suicide prediction, and designs a set of auxiliary diagnosis and treatment system based on campus monitoring network system for suicide behavior prediction and student mental health analysis. Through preliminary experimental analysis and verification, the suicide psychological auxiliary diagnosis and treatment system has achieved good results in face recognition success rate, emotion recognition success rate and behavior prediction success rate. With the input of more experimental data and the increase of self-training time, the prediction system will perform better.

IMPLEMENTASI SISTEM PEMANTAUAN JARINGAN MENGGUNAKAN LIBRENMS PADA JARINGAN KAMPUS UNIVERSITAS UDAYANA

Udayana University is education institutions that has implemented an online learningsystem. The system requires fast and reliable access to internet so students can access themefficiently. In order to meet the need for internet access, it requires to provide infrastructure thatis able to keep internet services running smoothly. Network Monitoring requires an applicationcalled Network Monitoring System. There are many network monitoring applications availablefor free, which provides many option for network operators to carry out monitoring functions.LibreNMS is a popular application because LibreNMS has many features, such as: autodiscovering,flexible and diverse alerting system, comfortable user interface with a dashboardthat can be adjusted to user needs and has wide community support. LibreNMS allows networkadministrators to monitor performance on the network so that it is always available. This studyaims to build a network monitoring system on the Sudirman Campus of Udayana Universityusing LibreNMS. The test results show that LibreNMS is able to display traffic conditions andresource usage on every network device that is monitored.

Multi-Domain Network Monitoring System for End-to-End Connectivity

With the growing scale size of networks and the complexities that follow, there is an increasing need for an end-to-end network management system for efficient monitoring of the system and having the best-in-class security, performance, and management features. This paper proposes an integrated network monitoring system that provides a single-window operation for end-to-end network management. The system is operated as a web application for stand-alone functioning. This eliminates most the dependencies, chances of failure and additional requirements that may lead to increased cost and decreased performance. The proposed system uses JavaScript for frontend and DHTMLx3.0 for the User Interface. Backend works on Java, Ajax, Hibernate, Apache Tomcat (webserver), Apache ActiveMQ (message queue), MTOSI (Multi-Technology Operations System Interface), CORBA TMF 814 and WebSwing. The different network technologies used and supported by the system for functioning are RADIUS (Remote Authentication Dial-In User Service), MPLS-TP, SDH, SONET, ONT, and GPON.

Development and Application of a Networked Automatic Deformation Monitoring System

Automatic deformation monitoring systems based on different types of sensors have been extensively studied in recent years. However, the existing systems cannot be applied to deformation monitoring projects in which monitoring points are distributed discretely and navigation satellite signals are occluded severely. Therefore, this study proposes a networked automatic deformation monitoring system (NADMS) to solve these problems. The NADMS uses different types of robotic total stations (RTSs) as sensors. The proposed system uses wireless networks and a MySQL database to realize the remote control of multiple RTSs and remote transmission and network query of observational data. Furthermore, the system realizes the station-moving-without-learning (SMWL) function using a free-station method. That is, if an RTS moves after the first learning cycle, re-orientation and the previous monitoring work can be continued without learning again. The RTS can correct its coordinates and azimuth automatically, and different types of RTSs can collect and transmit observational data collaboratively and independently in the NADMS. The precision and practicability of the NADMS are analyzed by simulation tests and a field test, and the results show that the system is effective and feasible and can meet the required monitoring precision of millimeter level.

Fault Analysis of Electric Power System using PLC and Wireless Communication System

In present scenario electricity theft is the major hurdle in front of government. This paper comprises of functions and architecture of the smart metering and monitoring network system which works on real time data communication and have its own network. Our main motive is to design and develop such a wireless metering system which will prevent power theft and provide us a reliable and accurate metering monitoring system by using modern technology. The design comprises of wireless power metering and monitoring network which will work on principle of real time data communication(which is not available in existing wireless GSM metering system) and will use its own reliable network with the help of Programmable Logic Controller. Programmable Logic Controller, smart meters, wireless communication modules and profinet cable are the key components of the system. To provide a better and easy human interface with the smart meter we are using simplify S CADA and programming which is very user affable.