Network Monitoring System Research Articles

Establishing a mechanism for international cooperation for Fukushima nuclear-contaminated water monitoring

The Japanese government’s unilateral decision to discharge the nuclear-contaminated water from the Fukushima nuclear power plant into the ocean has caused immense nuclear safety risks. Monitoring the unclear-contaminated water is a starting point to combat these risks and seek remedies for the rights and interests of all concerned parties. The establishment of a mechanism for international cooperation in this respect is necessary to handle the risks of the Fukushima nuclear-contaminated water and to lay the foundation of a framework for tackling any future disposal of nuclear-contaminated water following Japan’s example. At present, the international legal systems in the spheres of nuclear safety and security, marine environmental protection, and other areas, as well as the questioning of the monitoring reports of the International Atomic Energy Agency (IAEA) by the relevant parties, the monitoring practices of historical nuclear accidents, and numerous radioactivity monitoring mechanisms have provided the institutional and practical basis for constructing such a mechanism. The mechanism can be promoted by the IAEA through its existing mechanisms or be jointly initiated by China, the Russian Federation, the Republic of Korea, the Democratic People’s Republic of Korea, and the Pacific Island countries, among other stakeholders. Specifically, this mechanism should consist of three levels: first, the framework of the basic legal system, including the cooperative principles of national sovereignty, interest-relatedness, and procedural fairness, and the signing of the Framework Convention on the Monitoring of Fukushima’s nuclear-contaminated water and its Optional Protocol; second, the organizational structure and its responsibilities, which may include the Conference of Parties as the decision-making body, the Secretariat as the central coordinating body, and the monitoring committees in various fields as specific implementing agencies; and third, specific administrative arrangements, which involve the standardization of monitoring, the management system of monitoring networks and stations, the rules for monitoring procedures, and the rules for the utilization of the monitoring data, etc. With the urgent need for the scientific and fair monitoring of Fukushima’s nuclear-contaminated water, China, as a stakeholder country, can promote the establishment of such a mechanism for monitoring nuclear-contaminated water through the following paths: ① It is necessary to clarify the factors affecting the construction of an international cooperation mechanism for monitoring nuclear-contaminated water so as to ascertain the standpoints of the stakeholders, claims of their interests, contents of their cooperation, and the relevant international relations. ② On the basis of existing practices, China should consider improving the monitoring mechanism to cope with the risks of the discharge of Fukushima’s nuclear-contaminated water by formulating targeted policies and systems, setting up specialized monitoring institutions, and establishing a systematic monitoring network system. ③ This is an effective way for China to actively promote the participation of stakeholders in the construction of an international cooperation mechanism for monitoring nuclear-contaminated water in Fukushima by further innovating the dissemination mechanism to address the risk of Fukushima’s nuclear-contaminated water discharging into the sea and facilitating the identification of issues for international cooperation in monitoring Fukushima’s nuclear-contaminated water based on the concept of a community with a shared future for mankind.

The Power Quality of the distribution networks and its impact on the Telecommunication Next Generation Access Network

The paper deals with the Power Quality of the electrical distribution network and its impact on the new telecommunication networks. In particular, in the frame of the deployment of the Next Generation Access Network (NGAN) in the Fiber To The Cabinet (FTTCab) architecture, the impact of severe voltage dips and micro interruptions on the most important Information and Communications Technology (ICT) devices has been evaluated experimentally by Telecom Italia, defining in particular a sort of customized voltage dips immunity area for its telecommunications network equipment (TLC). On the base of these experimental results RSE has performed statistical analyses on voltage dips occurring outside this area which could be responsible in theory for the telecommunication devices reboot. The analyses are based on the data provided by the MV distribution network monitoring system QuEEN in the assumption that MV dips could be totally transferred to the LV network where the telecommunication cabinets are connected. A short analysis of voltage dips propagation from the medium voltage MV to the low voltage LV networks has been performed, on a few measurements sites at disposal in order to confirm this assumption.

The influence of network characteristics and environmental conditions on voltage dip performance in MV networks

The paper is focused on the possible influence that some network characteristics (i.e. network configuration, type of neutral operation, geographical area, lines and cable length…) and environmental phenomena (lighting) may have on voltage dip performance in Medium Voltage (MV) networks. The investigation has been performed by applying both correlation techniques and Multiple Linear Regression analysis (MLR) on the voltage dips collected along several years of monitoring by the Italian MV network monitoring system QuEEN. As to the network characteristics and environmental factors used in the performed analysis they are referred to the data supplied in the past for the monitoring system and to the lighting data provided by the Italian lightning location system SIRF1. The percentage contribution of each network and environmental factor to the voltage dips statistic, irrespective of the other parameters, have been evaluated by multiple linear regression methods. The results of these analysis confirm that the overhead line length has got a significant influence on the phenomena while cable lines length has, as expected, only a negligible effect. The influence of lightning seems to be not so critical as expected and this happen also with the neutral type of operation while voltage dips performances depend, in a non-negligible way, on the belonging to a geographical area.

Penerapan Bot Telegram untuk Sistem Monitoring Jaringan Intranet Daerah di Instansi Pemerintahan

Currently, the internet has become a basic need in the process of providing information and knowledge. Public, government and private services compete with each other in the use of information technology, which is expected to support employee performance and service. Therefore, human resources are needed who not only master material aspects, but also have adequate capacity and ability to apply and develop information in all fields. The use of this monitoring system is very necessary for the sidoarjo communicarions and information services departement and institutions that operate in the network sector and also have a fairly broad and complex customer coverage. Problems that often occur are slow internet connections, broken network cables, damaged network devices, etc. At that time, a network monitoring system was needed as a system that could detect when the network connection was lost. The research method used in this research is experimentation, namely a category of research that aims to find the cause and effect situation of a phenomenon. Therefore, this research is to investigate cause and effect, in accordance with previous conditions. From the results of the tests carried out, Mikrotik succeeded in sending notification messages in real time to the Telegram bot, with an average response time of 1 second in each condition. Router and Telegram will detect and send real-time message notifications to administrators if the internet connection status changes from off to active or vice versa

Taktik Komunikasi Efektif dalam Kampanye Lingkungan : Peran Humas dalam Kesadaran dan Aksi Bersama

In contemporary environmental discourse, the role of Integrated Marketing Communication (IMC) and collaborative efforts between Public Relations (PR) practitioners and environmental experts hold significant relevance. This study explores the pivotal role of communication strategies in environmental campaigns and the collaborative mechanisms between PR and environmental specialists within various organizational contexts. Estaswara (2000) underscores the strategic necessity of integrated communication in marketing, emphasizing its transformation from a mere promotional tool to a strategic business process. The findings highlight the insufficiency of environmental awareness alone in inciting tangible action. Discussions center around designing campaign messages to effectively drive concrete and sustainable behavioral changes. Collaboration between PR and environmental experts is articulated through several methods. Firstly, monitoring emissions involves joint efforts to develop and manage emission monitoring systems like Continuous Industrial Emission Monitoring Information System (CISPEK) and Continuous and Networked Effluent Water Quality Monitoring System (SPARING). Secondly, Performance Rating Program for Environmental Performance (PROPER) is used by PR to establish cooperation and enhance public trust in environmental management. Thirdly, effective communication and community engagement leverage social media and communal activities to disseminate information and amalgamate feedback from the public. The jurnal asserts the vital role of PR in fostering public participation, guiding communities on critical issues, and encouraging their contribution to sustainable development. By providing pertinent explanations, PR elevates societal awareness regarding crucial issues like environmental sustainability, climate change, and public health, stimulating active involvement in sustainable development endeavors..

Implementasi Sistem Monitoring Jaringan Menggunakan Libre Nms Pada Kecamatan Tarik

Network monitoring is needed to find out the various types of equipment and systems that are connected. LibreNMS is one of network monitoring system that can make it easier for administrators to monitor the network and if there are any problems it can be resolved immediately. The features provided are numerous, making it easier to monitor network performance available and ready to use. This study aims to build a network monitoring system in Kecamatan Tarik using LibreNMS. The test results show if LibreNMS can show the condition of the network system and the use of various equipment which is properly monitored.

Flexible Sensing Enabled Nondestructive Detection on Viability/Quality of Live Edible Oyster.

Environmental and physiological fluctuations in the live oyster cold chain can result in reduced survival and quality. In this study, a flexible wireless sensor network (F-WSN) monitoring system combined with knowledge engineering was designed and developed to monitor environmental information and physiological fluctuations in the live oyster cold chain. Based on the Hazard Analysis and Critical Control Point (HACCP) plan to identify the critical control points (CCPs) in the live oyster cold chain, the F-WSN was utilized to conduct tracking and collection experiments in real scenarios from Yantai, Shandong Province, to Beijing. The knowledge model for shelf-life and quality prediction based on environmental information and physiological fluctuations was established, and the prediction accuracies of TVB-N, TVC, and pH were 96%, 85%, and 97%, respectively, and the prediction accuracy of viability was 96%. Relevant managers, workers, and experts were invited to participate in the efficiency and applicability assessment of the established system. The results indicated that combining F-WSN monitoring with knowledge-based HACCP modeling is an effective approach to improving the transparency of cold chain management, reducing quality and safety risks in the oyster industry, and promoting the sharing and reuse of HACCP knowledge in the oyster cold chain.

Enhancing Sniffing Detection in IoT Home Wi-Fi Networks: An Ensemble Learning Approach With Network Monitoring System (NMS)

Enhancing Sniffing Detection in IoT Home Wi-Fi Networks: An Ensemble Learning Approach With Network Monitoring System (NMS)

Wearable piezoelectrical muscle monitoring system for swimming analysis neural network

Wearable piezoelectrical muscle monitoring system for swimming analysis neural network

Self-Healing Networks AI-Based Approaches for Fault Detection and Recovery

The reliability and robustness of communication networks are critical for ensuring seamless connectivity in today's interconnected world. However, network faults and failures can disrupt services, leading to significant downtime and financial losses. [1]In response to these challenges, self-healing networks empowered by artificial intelligence (AI) have emerged as a promising solution for proactively detecting and autonomously recovering from network faults. This paper presents a comprehensive review and analysis of AI-based approaches for fault detection and recovery in self-healing networks, aiming to enhance network reliability and minimize service disruptions. It provides an overview of the key challenges associated with traditional fault detection and recovery methods in communication networks.[2] It discusses the limitations of reactive approaches that rely on manual intervention or predefined rules to identify and mitigate network faults, highlighting the need for more proactive and adaptive solutions. Subsequently, the paper explores the role of artificial intelligence, particularly machine learning and deep learning techniques, in enabling self-healing capabilities in communication networks. By leveraging vast amounts of network data, AI algorithms can learn complex patterns and anomalies indicative of network faults, enabling timely detection and response. The paper reviews various AI-based fault detection techniques, including anomaly detection, supervised learning, and reinforcement learning approaches. It examines their strengths and limitations in different network environments, considering factors such as data availability, scalability, and real-time processing requirements. Furthermore, the integration of AI-based fault detection with network monitoring systems and telemetry data sources is discussed, highlighting the importance of comprehensive data-driven approaches for accurate fault identification. In addition to fault detection, the paper investigates AI-driven recovery mechanisms for self-healing networks. It explores proactive recovery strategies, such as predictive maintenance and network reconfiguration, enabled by AI-based predictive analytics. By harnessing the power of machine learning and deep learning, communication networks can achieve greater resilience, adaptability, and autonomy in mitigating network faults and ensuring uninterrupted service delivery.

Designing A Computer Network Monitoring System With Sms Notifications Using The Dude

One system that can perform network monitoring with SMS notifications is using The Dude. This network monitoring system with SMS Notification aims to make network admins aware of network conditions wherever they are. In monitoring the network the dude can do based on the ip address entered, the dude is open source, which is one of the software or tools built into Mikrotik, in the process of installing the dude does not require large storage space. In monitoring the network the dude will display a green indicator, which is on and red, which is off, to monitor the network the dude does it based on the IP Address per each device connected to the network. The Dude can perform network monitoring on the SMA N 6 Bengkulu Selatan computer network in the form of notification of devices on or off. The results of the monitoring will be sent in the form of notifications to the admin cellphone in the form of SMS, in sending SMS notifications, the dude takes +/- 2 minutes, the time for sending SMS notifications is calculated based on the condition of the device on or off until the notification is received or received on the cellphone.

A streamflow regionalization method using hydrological data and geoprocessing tools—a Brazilian midwest analysis

The efficient management of water resources depends on knowledge of the flows of the entire hydrographic basin. However, in most cases, basins have an insufficient monitoring network and flow measurement system, which can compromise the application of the grant instrument and cause damage to the environment and users. Therefore, it is necessary to develop hydrological models that provide information on the minimum flows in all water courses of the planning unit. Thus, this study aimed to propose a method to regionalize flows in areas with limited monitoring using hydrological data and geoprocessing tools. The Ivinhema River Basin, located in Mato Grosso do Sul State, Brazil, was adopted as the study area. The models were developed based on the correlation of physical and environmental variables, which was evaluated by the relative error and the Nash–Sutcliffe efficiency coefficient. Finally, the flow Q95 was spatialized, generating an accumulated flow map with the application of the selected model, and the corresponding Q95 was obtained for each stretch of the watercourse. The developed method provides relevant results and can be applied to various hydrographic basins.

Deploying Nagios for Service Monitoring and Reporting

NAGIOS is Server Monitoring tool as an important criteria coming to a data center operation and service .Detects all type of network errors or server issues and allowed to monitor the server performance issues by using Nagios. This can be manually and physically monitoring the location of the server and mapping the network interface and network bridge server will be monitor. Count every 10 minutes once the application will be running properly or else store application related bugs in data center. Large organizations always require fast and efficient network monitoring system which reports to the network administrator as soon as a network problem arises. This paper presents an effective and automatic network monitoring system that continuously monitor all the network switches and inform the administrator by E-MAIL or SMS when any of the network switch goes down. An efficient and automatic network monitoring is always required for large organizations like universities, companies and other business sectors where the manual network monitoring is very difficult. Since large organizations have a big network topology, the manual network monitoring causes waste of time to point out problem location.

Fiber Optical Network Damage Detection Passive Splitter 1:8 in ODC uses IOT Technology as a means of Real Time Reporting

Fiber optic networks currently have a lot of interest, so a network monitoring system is needed that guarantees quality and speed of repair if mass disruption occurs. in research [1] regarding fiber network damage detection using IoT with the use of a 1:4 splitter and the use of a detector that can work at a wavelength of 650nm so that it can detect damaged cables with output in the software. So in connection with this, the author wants to develop the results of this research by using a 1:8 splitter and carrying out detection using the LDR sensor and NodeMCU ESP32 using IoT (Internet of Things) technology. The ESP32 NodeMCU will receive data in the form of light intensity values ??at each ODC from the LDR sensor. And then sent to a database that is connected directly to the Android application. The cable identification process occurs in three states: normal, warning, and error. The test and analysis results show that the hardware device can work well, with attenuation in the passive splitter cable of 10.28 dB and a light source with a wavelength of 650 nm. Cable detected as damaged is indicated by an output in the software with a delay of 4.56 s.

Design and implement a real-time network traffic management system using SNMP protocol

The research focuses on designing and implementing a system for managing incoming server traffic using the Simple Network Management Protocol (SNMP). The essence of the method is to provide a real-time monitoring system that empowers network managers to oversee all network activities efficiently. The key difference of the developed system lies in using the SNMP protocol to monitor and control the network without needing a third-party tool. The proposed approach addresses administrators' common network challenges, including inefficient bandwidth utilization and complex network resource monitoring. Upon implementation, the system gathered essential network equipment information from the Management Information Base (MIB). The research results indicate that the SNMP-based network management system prevents network devices from reaching their allotted bandwidth limits. The system notably reduces CPU utilization from 28 % to 8 % and decreases bandwidth usage from 1.7 MiB/s to 260 bytes/s. Additionally, the system's alerting capability enhances the network's resilience against incoming traffic anomalies that may otherwise interrupt server operations. An example of using the proposed system to manage incoming server traffic in small networks. It has several practical uses in managing and maintaining network infrastructure in different fields. Also, it enables real-time monitoring of network devices, resource management, fault detection, and performance optimization. The system can be used in small organizations to monitor network performance, track faults, and manage network resources efficiently. In addition, SNMP-based network monitoring systems can find applications in almost any field where networked devices and infrastructure require monitoring, management, and optimization

Deep Adversarial Tensor Completion for Accurate Network Traffic Measurement

Network trouble shooting, failure location, and anomaly detection rely heavily on network traffic measurement data. Due to the lack of measurement infrastructure, the high measurement cost, and the unavoidable transmission loss, network monitoring systems suffer from the problem that the network traffic data are incomplete. This article models the traffic data as a tensor to exploit its strong ability of feature extraction to recover the missing data. Different from traditional tensor completion which relies on tensor factorization, we design a novel Deep Adversarial Tensor Completion (DATC) scheme based on Deep Learning (DL) techniques. DATC is the first scheme that exploits the data reconstruction ability of autoencoder and the power of adversarial training from Generative Adversarial Networks to infer the missing data. Despite that DL techniques achieve great success in the image field, designing an algorithm based on DL techniques to recover the traffic data with missing entries faces additional challenges due to the skewed distribution and the sparsity of traffic data. To conquer these challenges, we propose the use of two techniques, adversarial training and missing data aware convolution. These techniques help DATC to learn the complex features of the traffic data and infer the missing data following the data distribution of traffic data. Our extensive experimental results using two public real-world network traffic datasets and running both offline and online demonstrate that DATC can achieve significantly better recovery accuracy while capturing the data distribution of the traffic data even when the sampling ratio is very low.

Choice of the Parameters of an EMI Monitoring System for an AC Traction Network

The problem of ensuring the electromagnetic compatibility of the traction network with railway signaling lines is of practical interest, since electromagnetic interference from the traction network can cause malfunctions in the signaling systems. In order to ensure the electromagnetic compatibility of traction current with track circuits, which are widely used as track vacancy sensors in front of a moving train, electromagnetic interference in rails is periodically monitored in accordance with their maintenance schedule, which makes it possible to detect excessive increases in the level of interference in the rails in a timely manner and prevent possible failures in signaling systems. The problem of developing embedded systems for continuous monitoring of harmonics in the traction network lies in the need to ensure the necessary measurement accuracy of the interference monitoring system for a traction network in accordance with the strict requirements of standards. The correct choice of control system parameters is difficult because the traction current is a non-stationary random process, and the alternating traction current, in addition, has a large dynamic range of harmonic values, their proximity to each other and to a powerful fundamental harmonic, as well as the limitations inherent in the discrete Fourier transform, associated with the impossibility of simultaneously improving the accuracy of measurements in the time and frequency domains, which leads to the need for compromises when choosing the parameters of the monitoring system. The work is devoted to the practice of applying the theory of analog-to-digital conversion and the windowed Fourier transform to develop a technique for correctly choosing the parameters of an electromagnetic interference monitoring system for traction lines.

Energy-Saving Adaptive Routing for High-Speed Railway Monitoring Network Based on Improved Q Learning.

In high-speed railway operational monitoring network systems targeting railway infrastructure as its monitoring objective, there is a wide variety of sensor types with diverse operational requirements. These systems have varying demands on data transmission latency and network lifespan. Most of the previous research focuses only on prolonging network lifetime or reducing data transmission delays when designing or optimizing routing protocols, without co-designing the two. In addition, due to the harsh operating environment of high-speed railways, when the network changes dynamically, the traditional routing algorithm generates unnecessary redesigns and leads to high overhead. Based on the actual needs of high-speed railway operation environment monitoring, this paper proposes a novel Double Q-values adaptive model combined with the existing reinforcement learning method, which considers the energy balance of the network and real-time data transmission, and constructs energy saving and delay. The two-dimensional reward avoids the extra overhead of maintaining a global routing table while capturing network dynamics. In addition, the adaptive weight coefficient is used to ensure the adaptability of the model to each business of the high-speed railway operation environment monitoring system. Finally, simulations and performance evaluations are carried out and compared with previous studies. The results show that the proposed routing algorithm extends the network lifecycle by 33% compared to the comparison algorithm and achieves good real-time data performance. It also saves energy and has fewer delays than the other three routing protocols in different situations.

Smart-Systems for Precision Agriculture, Environmental Protection and Healthcare

Appearance of innovative tools of informatics in the world is determined by development of information-communication technology, microelectronics, sensor and biosensor technologies. Spreading of these technologies on precision agriculture, environmental protection and health care gives opportunity to create smart fields, gardens, greenhouses, forests and parks, and also smart health monitors, which estimate the health state of person as in rehabilitation, so in emergency situations. Results of research of authors in the development of new information technologies and creation of main components of the smart systems for different purposes on this base are shows in this paper. Main requirements for knowledge bank for precision agriculture and ecological monitoring are defined. Main principles of creating knowledge bank on base of requirements are proposed. The typical smart system models and their development stages are considered. Structure of wireless multilevel networks for the estimation of state of biological objects of different origin and their nodes are described. Developed sensor networks and smart systems for agriculture are considered. Structure of proposed smart system for agriculture and ecological monitoring is given. Approaches for chlorophyll fluorescence induction curves analysis are studied. Results of network testing for the estimation of the autonomous work time of network nodes and possible errors are given. Wireless sensor network and smart system for remote medical monitoring are described. Diagnostic smart systems for estimation of quality of life are considered. Medical communicator, computer device on base of tablet computer, was used for their development. The short form of Survey Instrument (SF-36) for life quality estimation and abnormal uterine bleeding questionnaire, which was developed in State Scientific Institution "Center for Innovative Medical Technologies of the National Academy of Sciences of Ukraine", were embedded in communicator. STEPS questionnaire which was designed for epidemiological monitoring of the prevalence of noncommunicable diseases and their risk factors in the target subpopulations could be added to communicator. Development of smart systems for estimation of quality of life and prevalence of noncommunicable diseases was made in cooperation with R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology NAS of Ukraine (department of research management and innovation), Chebotarev Institute of Gerontology of the National Academy of Medical Sciences of Ukraine, Center for Innovative Medical Technologies of the National Academy of Sciences of the Ukraine. Keywords: wireless sensor network, precision agriculture, chlorophyll fluorescence induction, express-diagnostics of plant state, quality of life, SF-36.

Risk assessment for the optimization of the grid of a telemetric network monitoring system

The goal of this work was to develop a methodology for risk assessment in case of an accident originating from a nuclear power plant, and consequently, to improve the relevant radiation monitoring network. In specific, the study involved risk estimation in Greece from a transboundary nuclear power plant accident. The tool employed was JRODOS (Java-based Real-time Decision Support), which is a system for off-site emergency management of radioactive material in the environment. This tool, widely used to generate and study scenarios for nuclear accidents worldwide, provides valuable insight to facilitate emergency preparedness and response. The probability of the plume arriving at numerous regions within the country was calculated, along with the maximum dose rates in case of transport. A risk assessment was performed, and geographical regions were prioritized in terms of risk-based environmental radioactivity burden. A total of 29 administrative districts were identified as low to medium-risk regions. Acquired results were used to determine the optimal spatial distribution of detectors for upgrading the existing monitoring network of environmental radioactivity.