Network Operating Research Articles

Intraoperative Image-Guided Surgery for Gliomas in the Smart Cyber Operating Theater (SCOT): A Preliminary Clinical Application

Various devices exist for glioma image-guided surgery to improve tumor resection. These devices work as stand-alone units, making the flow of operative information complicated and disjointed. A novel networked operating room, the Smart Cyber Operating Theater (SCOT), has been developed, integrating stand-alone medical devices using the OPeLiNK communication interface. We report and evaluate the impact of SCOT for glioma surgery and our initial experiences. Patients with gliomas who underwent tumor resection in SCOT between July 2018 and June 2021 were retrospectively reviewed. Various types of intraoperative information were integrated, managed, and shared with the surgical strategy desk using OPeLiNK. Patients' demographics, tumor characteristics, treatment details, and outcomes were obtained. The impact of the SCOT system was evaluated. Twenty-seven patients, with a mean age of 48.6 years (range, 13-88 years), met the inclusion criteria. We successfully completed all the surgical procedures using SCOT. The mean operation time was 420.6 minutes (range, 225-667 minutes).Gross total resection was accomplished in 13 patients (48.1%), subtotal resection in 4 (14.8%), and partial resection in 10 (37.0%). The main surgeon in the operating room and other neurosurgeons at the strategy desk shared and discussed the information in real time during the procedures. The use of SCOT was shown to be safe and feasible in glioma surgery. This study suggests that SCOT may improve surgical outcomes and educational impact by sharing information in real time with the strategy desk.

The Impact of the Thermal Distribution Network's Operating Temperature and System Design on Different Communities' Energy Profiles

The Impact of the Thermal Distribution Network's Operating Temperature and System Design on Different Communities' Energy Profiles

Evaluation of the infocommunication network current state based on time series analysis

The management of infocommunication networks operating in various physical environments and external conditions is a very important problem both from the standpoint of developing a control system and from the standpoint of implementing control in the process of functioning of an infocommunication network. The vast majority of modern infocommunication networks are forced to function in conditions of various kinds of conflict interactions, when electronic reconnaissance is carried out, radio countermeasures are organized, radio masking and protection from deliberately organized interference and destructive force effects are applied. Destructive influences are aimed at destroying information flows circulating between network elements; decrease in the speed of information exchange between elements of the control system, which significantly increases the duration of the control cycle and, as a result, reduces the efficiency of network management; ensuring sufficiently massive and long-term failure of network technical means. The specified operating conditions require the network management system to make accurate and timely management decisions to prevent undesirable consequences. The publication considers the method of situational management of the infocommunication network as the most promising for ensuring effective management on a real-time scale in conditions of destructive influences. The essence of the method consists in the selection of control solutions from a defined set of permissible control influences based on the results of the assessment of the current state of the infocommunication network. Changes in the functional states of the network are achieved through purposeful control influences on functional elements specially designed for their perception and processing. The purpose of the publication is to develop a general approach to assessing the current state of the infocommunication network based on time series analysis. Elements of novelty of the presented solution are consideration of the well-known problem of ensuring interference resistance of the infocommunication network as a problem of managing situations in the conditions of interference, as well as the use of template sequences describing the conditions of network operation.

Dynamic Algorithm for Interference Mitigation Between Cells in Networks Operating in the 250 MHz Band

The growing demand for Internet of Things (IoT) applications in agribusiness increases the necessity of reliable and secure connectivity in rural areas. Thus, in the particular case of Brazil, some initiatives aim to take advantage of frequency bands dedicated to limited private services. For instance, cellular networks based on orthogonal frequency-division multiple access (OFDMA) in 250 MHz bands require specialized adaptations because the interference between cells increases when these systems operate in the Very High Frequency (VHF) band. This work presents an analysis based on a reliable simulation of interference mitigation in OFDMA systems at 250 MHz using a network simulator. The simulator is calibrated with data obtained in the field by an extensive and rigorous drive test. Therefore, the analysis is based on a comparison of traditional frequency reuse schemes with a machine learning approach based on deep reinforcement learning (DRL) to reduce inter-cell interference. The numerical results indicate that the DRL approach outperforms the traditional frequency reuse (FR) schemes in four different typical agribusiness scenarios.

Investigation of Existence of Steady States of a Solar Power Plant Operating in the Distribution Network of an Electric Power System

The paper presents the results of studies of the steady-state operating modes of solar photovoltaic stations. Using the data obtained, it is possible to significantly increase the efficiency of using solar power generating plants and significantly increase the service life of additional equipment. The relevance of this study is due to the increasing demand for low-power electric power systems, as well as for renewable energy technologies. For the research, materials were taken from relevant international departments and agencies, the Ministry of Energy of the Russian Federation. In addition, the sources of data are publications and studies of Russian and foreign scientists on the issues under study. The Federal Law No. 35-FZ “On Electricity”, adopted in December 2019 by the State Duma of the Russian Federation, introduces such a concept as “Micro-generation facility”, thereby simplifying the possibility of installing, connecting to the general network of an electrical system, for example, a small solar power plant (SPP) consumer. Small-scale electric power industry at this stage of its life is an energy-efficient tool in the restructuring of the energy sector of the Russian Federation, contributing to the abandonment of the traditional centralized system based on the use of large sources of electric power production, and the transition to alternative methods of generating electricity based on the use of energy sources, updated for specific natural conditions and requests of potential consumers. Reducing pollutants and emissions that are harmful to human health can reduce the level of the existing burden on the country's economy and give an impetus to the development of its potential due to the freed up resources. reduce the burden on the economy, thereby freeing up resources for its growth. Of course, the transition from traditional economic models to the model of 'green growth' can be realized only if significant efforts are made to expand international cooperation in this area. At the same time, there is a need for consistent implementation of events at various levels on the part of all states, as well as maintaining the chosen political course for many years.

Integrated Network and Security Operation Center: A Systematic Analysis

Traditionally, network and security operation center teams have worked in silos despite commonalities. The network operating center (NOC) team is to provide operationality and availability of information technology (IT) assets, while the security operation center (SOC) team is to ensure IT assets security and protect them from cyber-security attacks. The convergence in IT assets and exponential growth in cyber-security threats in the present digital-online scenario have created many challenges in maintaining network and IT assets effectively and protecting them. It is vital to break these silos and bring them under one integrated unit to effectively counter cyber-security attacks, threats, and vandalism at a reduced operational cost. Despite its necessity, the relevant literature lacks an opinion. It focuses mainly on conceptual segments instead of a holistic view of an integrated NOC and SOC architecture, limiting further innovations in the field. A systematic literature review and analysis is conducted to collate and understand current research ideas in this paper. The mapped relevant literature and our expertise have been then used to propose the implementable state-of-the-art architecture of an integrated NOC and SOC, its definition, the main building blocks and its usefulness for the organizations. Only explicit knowledge of people is considered while neglecting the tacit knowledge in automating and integrating the processes of NOC and SOC, which is the major limitation of the relevant literature. Taping people tacit knowledge is necessary for utilizing the entire caliber of the NOC and SOC integration in the future.

A Comparative and Analytical Study for Choosing the Best Suited SDN Network Operating System for Cloud Data Center

The growing deployment of Software Defined Network (SDN) paradigm in the academic and commercial sectors resulted in many different Network Operating Systems (NOS). As a result, adopting the right NOS requires an analytical study of the available alternatives according to the target use case. This study aims to determine the best NOS according to the requirements of Cloud Data Center (CDC). This paper evaluates the specifications of the most common open-source NOSs. The studied features have been classified into two groups, i.e., non-functional features such as availability, scalability, ease of use, maturity, security and interoperability, and functional features, such as virtualization, fault verification and troubleshooting, packet forwarding techniques and traffic protection solutions. A Decision support system, Analytical Hierarchy Process (AHP) has been applied for assessing specifications of the inspected NOSs, namely, ONOS, Opendaylight (ODL), Floodlight, Ryu, POX and Tungsten. Our investigation revealed that ODL is the most suitable NOS for CDC compared to the rest studied NOSs. However, ODL and ONOS have almost similar scores compared to the rest NOSs.

Reliable Task Planning of Networked Devices as a Multi-Objective Problem Using NSGA-II and Reinforcement Learning

Tracking and detecting multiple objects is difficult for a single radar device, as it may not have the capacities such as anti-interference and anti-stealth. However, if radar devices of diverse capabilities can be combined to realize collaborative networked operation, the reliability and performance of a radar system in a complex environment can be significantly improved. This paper classify the networked radar-based multi-objective task planning as a combinatorial optimization problem with constraints and abstract a distributed multi-agent system (MAS) model from a networked radar system. A node-selection algorithm was designed based on a greedy policy to narrow down solution space for subsequent networked radar task planning, reduce the amount of calculation, and improve the efficiency of the proposed algorithm. Moreover, focusing on NSGA-II, the proposed algorithm was modified using self-adaptive operators and reinforcement learning. A dual-population strategy was introduced to allow exchanges of multiple individuals between populations during migration, and the number of individuals for the exchange was obtained through reinforcement learning. In this paper, five algorithms are compared and analyzed. In addition, statistical analyses are conducted from four perspectives: the average evaluation value of energy consumption and bandwidth in the Pareto front solutions, the time consumption of the algorithm, and the diversity of the population. The results indicate that among those algorithms, the reinforcement-learning-based RNSGA-II algorithm can produce the best outcomes for networked radar task planning.

Sensitivity and Robustness Issues of Operating Envelopes in Unbalanced Distribution Networks

The fast-growing uptake of distributed energy resources (DER), such as home photovoltaic (PV) and battery systems and electric vehicles, has introduced new challenges in the operation of low-voltage distribution networks (LVDNs). High levels of DER can produce large swings in power flow from the day (low-demand, high PV exports) to the night (high-demand) that can push the LVDN network to its operational limits. Network operating envelopes aim to maximise network capacity utilisation through the implementation of dynamic customer capacity limits, where DER exports or imports are constrained at times of network congestion and otherwise relaxed to potentially higher levels than those realisable through traditional static customer capacity limits. A common assumption underlying the implementation of operating envelopes is that operational constraint violations will be avoided if the realised demands of customers under dynamic connections all fall within their capacity envelopes. However, this assumption needs more careful consideration in the light of strong unbalance and mutual phase couplings common in LVDNs. This paper analyses phase voltage level sensitivities to customer demand levels and demonstrates that voltage violations can still occur when all customers are within their limits. These results, illustrated by experimental studies based on a two-bus example and a real representative Australian LVDN, underline the importance of incorporating uncertainty in the calculation of operating envelopes.

Cybersecurity: Identifying the Vulnerability Intensity Function (<i>VIF</i>) and Vulnerability Index Indicator (<i>VII</i>) of a Computer Operating System

The objective of the present study is to define two important aspects of the computer operating system concerning the number of its vulnerabilities behavior. We identify the Vulnerability Intensity Function (VIF), and the Vulnerability Index Indicator (VII) of a computer operating network. Both of these functions, VIF and VII are entities of the stochastic process that we have identified, which characterizes the probabilistic behavior of the number of vulnerabilities of a computer operating network. The VIF identifies the rate at which the number of vulnerabilities changes with respect to time. The VII is an important index indicator that conveys the following information about the number of vulnerabilities of Desktop Operating Systems: the numbers are increasing, decreasing, or remaining the same at a particular time of interest. This decision type of index indicator is crucial in every strategic planning and decision-making. The proposed VIF and VII illustrate their importance by using real data for Microsoft Windows Operating Systems 10, 8, 7, and Apple MacOS. The results of the actual data attest to the importance of VIF and VII in the cybersecurity problem we are currently facing.

Mitigating Faults and Revenue Losses Using Fault Detectors at Trans Amadi Industrial Layout, Port Harcourt Rivers State

Abstract: Transmission line fault detection is an important aspect of monitoring the health of a power plant since it indicates when suspected faults could lead to catastrophic equipment failure. This research looks at how to detect generator and transmission line failures early and investigates fault detection methods using Artificial Neural Network approaches. Monitoring generator voltages and currents, as well as transmission line performance metrics, is a key monitoring criterion in big power systems. Failures result in system downtime, equipment damage, and a high danger to the power system's integrity, as well as a negative impact on the network's operability and dependability. As a result, from a simulation standpoint, this study looks at fault detection on the Trans Amadi Industrial Layout lines. In the proposed approach, one end's three phase currents and voltages are used as inputs. For the examination of each of the three stages involved in the process, a feed forward neural network with a back propagation algorithm has been used for defect detection and classification. To validate the neural network selection, a detailed analysis with varied numbers of hidden layers was carried out. Between transmission lines and power customers, electrical breakdowns have always been a source of contention. This dissertation discusses the use of Artificial Neural Networks to detect defects in transmission lines. The ANN is used to model and anticipate the occurrence of transmission line faults, as well as classify them based on their transient characteristics. The results revealed that, with proper issue setup and training, the ANN can properly discover and classify defects. The method's adaptability is tested by simulating various defects with various parameters. The proposed method can be applied to the power system's transmission and distribution networks. The MATLAB environment is used for numerous simulations and signal analysis. The study's main contribution is the use of artificial neural networks to detect transmission line faults. Keywords: Faults and Revenue Losses

Linux-Based Server Operating System Installation Training for Yapdi Bandar Pulau Vocational High School Students

This community service activity aims to provide training to students of SMK Yapdi Bandar Pulau on Installing a Linux Server Operating System based on CentOS 7. Submission of material is carried out theoretically and directly in practice in installing a Linux server operating system. Several important points were conveyed theoretically and practically in this activity, such as an explanation of a Linux-based server or network operating system. Then in practice, the participants were guided directly to perform the installation and basic configuration for this server operating system. Materials given to participants up to 90% of the knowledge about the Linux server operating system and how to install it. Based on the results of the discussions carried out in the form of question and answer discussions and direct practice, the understanding of the participants reached 92% for the level of understanding of the material provided.

Search for the optimal means for modelling the electric field of insulators

The article analyses software tools for simulation of electric field of insulators. The necessity of solving this problem is dictated by the fact that inaccuracy of simulation software allows stating that the simulation model cannot be improved correctly due to calculation errors in the program itself. Design features of different types of insulators, first of all, the most widespread and used - porcelain and glass insulators, are considered. The change of electric field in a glass and porcelain insulator operating in an AC network without contamination is described. Numerous calculation methods such as boundary element method, finite element method, integral equation method and others have been analysed. It is revealed, that from the point of view of functionality and expediency of application for solution of field problems relevant to electric power industry the finite difference method and finite element method are the most universal ones. The results of insulator electric field modelling using Ansoft Maxwell, CST EM Studio and Elcut software are given. Among Ansys, FEMLAB, Ansoft Maxwell, CST EM Studio, IES Coulomb and Elcut that were analyzed, the software Ansoft Maxwell and CST EM, where the finite element method is implemented, were chosen to solve the given problem. It was found out, which one of the software complies better with the given requirements as to accuracy (by calculation of error of deviation of mathematical modelling and experimental data) and in terms of the method incorporated in the algorithms of the software. Experimental data are compared with simulation results. The possibility of diagnosing insulators by electric field tension parameters has been revealed.

Design and Implementation of SDN IP Based on Open Network Operating System and Border Gateway Protocol

The development of computer network technology in the form of Software Defined Networking (SDN), provides many facilities for users to be able to develop network control applications, which can separate the data plane function from the control plane. The existence of this separation on routers and switches makes it easy for developers to centrally develop software and devices according to what is needed by users. However, there were obstacles to implementing SDN on IP networks in a short time. For this reason, it is necessary to implement SDN in stages by adding SDN to the existing IP network in the form of SDN IP, so that SDN can be connected and exchange routing information autonomously. This study focuses on the design and implementation of SDN IP using the Open Network Operating System (ONOS) on the Border Gateway Protocol (BGP). The results show that the design and implementation of SDN IP based on ONOS and BGP can be done well, where SDN can connect and exchange routing information with the Autonomous System (AS) native BGP-based network.
 
 Key word(s):
 Autonomous System (AS)
 Border Gateway Protocol (BGP)
 Open Network Operating System (ONOS)
 Software-Defined Networking (SDN)
 SDN IP

Load Balancing and Detection of Distributed Denial of Service Attacks Using Entropy Detection

Software Defined Network (SDN) is a modern network architecture that has a centralized controller. It is more flexible, and programmable due to the separation of the control plane from the data plane. However, Distributed Denial of Service (DDoS) attacks is one of the dangers that the SDN network is facing. It could attack and stop the controller from working, causing the whole system to be down. Moreover, DDoS attacks can target the hosts and the switches to stop the services for a long time as they could cause more damage to the network or datacenter. In this work, a proposed approach is utilized to protect datacenter networks and servers from DDoS attacks using entropy and real SDN-controller Python Network Operating system (POX) by redirect traffic to the edge of the datacenter to minimize the damage. The results of this experiment show how to detect abnormal traffics in an early stage and isolate them in a server outside the datacenter to distribute the huge amount of traffic in more than one server and avoid congestion on switches. Also, the throughput of the server was increased by about %16 during the suspected attack, this means maintaining the service until further analysis to be done on the traffic. These results are compared with the direct block mitigation method which was mostly used with the entropy detection method in previous researches. Moreover, this work is done to confirm whether the suspected traffic is an actual attack or not. Therefore, this method will decrease the false positives of detection. IndexTerms— Software-Defined Networking (SDN), Distributed Denial of Service (DDoS) attacks, OpenFlow, Python Network Operating system (POX).

Reconfigurable Intelligent Surfaces for 5G and beyond Wireless Communications: A Comprehensive Survey

With possible new use cases and demanding requirements of future 5th generation (5G) and beyond cellular networks, the future of mobile communications sounds promising. However, the propagation medium has been considered a randomly acting agent between the transmitter and the receiver. With the advent of the digital age of wireless communications, the received signal quality is degrading due to the uncontrollable interactions of the transmitted radio waves with the surrounding artifacts. This paper presents a comprehensive literature review on reconfigurable intelligent surfaces (RISs) and assisted application areas. With the RIS, the network operators can control radio waves’ scattering, reflection, and refraction characteristics by resolving the harmful properties of environmental wireless propagation. Further, the RIS can effectively control the wavefront, such as amplitude, phase, frequency, and even polarization, without requiring complex encoding, decoding, or radio wave processing techniques. Motivated by technological advances, the metasurfaces, reflectarrays, phase shift, and liquid crystals are potential candidates for implementing RIS. Thus, they can be considered the front runner for realizing the 5G and beyond network. Furthermore, the current research activities in the evolving field of wireless networks operated by RIS are reviewed and discussed thoroughly. Finally, to fully explore the potential of RISs in wireless networks, the fundamental research issues to be addressed have been discussed.

Reliability-oriented operation of distribution networks with multi-microgrids considering peer-to-peer energy sharing

This paper aims to propose a comprehensive energy management system (CEMS) to simultaneously enhance the resilience of microgrids (MGs) and distribution network (DN) in a multi-microgrid (MMG) system against unexpected events. It also develops a reliability evaluation framework for the reliability evaluation of MMG distribution systems. In this regard, the proposed CEMS includes two main strategies: (1) networked operation mode (NOM), attributed to the cooperation of independent sub-sections (MGs/DN) in fault-affected portions. Here, each MG must exchange power with the DN and other MGs (may be islanded simultaneously) by participating in peer-to-peer (P2P) energy sharing to enhance resilience and reliability of the whole network, and (2) individual operation mode (IOM), comprising the grid-connected, optional islanding, fully forced islanding, and partial islanding modes for different operational requirements of MGs. Thus, the required information of an outage is identified. A suitable decentralized strategy based on the proposed CEMS and the novel adaptive problem formulation are initially used to operate such systems under different operating conditions. The NOM and IOM together assure the survivability of the whole system during the emergency periods and maintain reliable electric power supply for consumers while guaranteeing system stability indicators and ensuring operating costs of MGs. To substantiate these claims, we use different case studies to demonstrate the efficiency of the proposed CEMS based on a modified reliability test system. • A comprehensive energy management system is proposed for multi-microgrids. • An adaptive problem formulation is used for different operational requirements of microgrids. • The proposed method includes: networked operation mode and individual operation mode. • P2P energy sharing is proposed to enhance the resilience of system in networked operation mode. • Various case studies are conducted to study the system under normal and faulted operation modes.

Optimal Design and Operation of Multi-Period Water Supply Network with Multiple Water Sources

A water supply network is an essential part of industrial and urban water systems. The water intake in a conventional water supply network varies periodically over time, depending on the amount of available water resources and the demand at water sinks or water-using units. This paper establishes a super-structural mathematical model for the optimal design and operation of a multi-period water supply network with multiple water sources. It considers the flow rate fluctuation of raw water availability and the demand of water sinks during different periods. The influence of multi-period demand variation on technology and the capacity selection of desalination water stations is examined, which affects the overall cost of the water supply network. The operating cost penalty factor is introduced, which quantitatively clarifies how the network operating status influences the operating costs. The comparison results of three scenarios considering with and without multi-period variation of water demand verify the validity of the proposed model, i.e., for a municipal water price of 4 CNY·t−1 and penalty factor of 0.3, one reverse osmosis desalination unit of capacity 800 t·h−1 is selected. However, in the multi-period case, two reverse osmosis desalination units with capacities of 500 t·h−1 and 300 t·h−1 are selected. In both cases, the operating costs are different because of the different operating status of the network. The work can guide the design and operation of industrial and urban water supply networks.

Prospects of Wireless Energy-Aware Sensors for Smart Factories in the Industry 4.0 Era

Advanced sensors are becoming essential for modern factories, as they contribute by gathering comprehensive data about machines, processes, and human-machine interaction. They play an important role in improving manufacturing performance, in-factory logistics, predictive maintenance, supply chains, and digitalization in general. Wireless sensors and wireless sensor networks (WSNs) provide, in this context, significant advantages as they are flexible and easily deployable. They have reduced installation and maintenance costs and contributed by reducing cables and preinstalled infrastructure, leading to improved reliability. WSNs can be retrofitted in machines to provide direct information from inside the processes. Recent developments have revealed exciting possibilities to enhance energy harvesting (EH) and wireless energy transmission, enabling a reliable use of wireless sensors in smart factories. This review provides an overview of the potential of energy aware WSNs for industrial applications and shows relevant techniques for realizing a sustainable energy supply based on energy harvesting and energy transfer. The focus is on high-performance converter solutions and improvement of frequency, bandwidth, hybridization of the converters, and the newest trends towards flexible converters. We report on possibilities to reduce the energy consumption in wireless communication on the node level and on the network level, enabling boosting network efficiency and operability. Based on the existing technologies, energy aware WSNs can nowadays be realized for many applications in smart factories. It can be expected that they will play a great role in the future as an enabler for digitalization in this decisive economic sector.

Impact of the SARS-CoV-2 (COVID19) pandemic on the morbidity and mortality of high risk patients undergoing surgery: a non-inferiority retrospective observational study

BackgroundDuring the COVID-19 crisis it was necessary to generate a specific care network and reconvert operating rooms to attend emergency and high-acuity patients undergoing complex surgery. The aim of this study is to classify postoperative complications and mortality and to assess the impact that the COVID-19 pandemic may have had on the results.Methodsthis is a non-inferiority retrospective observational study. Two different groups of surgical patients were created: Pre-pandemic COVID and Pandemic COVID. Severity of illness was rated according to the Diagnosis-related Groups (DRG) score. Comparisons were made between groups and between DRG severity score-matched samples. Non-inferiority was set at up to 10 % difference for grade III to V complications according to the Clavien-Dindo classification, and up to 2 % difference in mortality.ResultsA total of 1649 patients in the PreCOVID group and 763 patients in the COVID group were analysed; 371 patients were matched for DRG severity score 3-4 (236 preCOVID and 135 COVID). No differences were found in relation to re-operation (22.5 % vs. 21.5 %) or late admission to critical care unit (5.1 % vs. 4.5 %). Clavien grade III to V complications occurred in 107 patients (45.3 %) in the PreCOVID group and in 56 patients (41.5 %) in the COVID group, and mortality was 12.7 % and 12.6 %, respectively. During the pandemic, 3 % of patients tested positive for Covid-19 on PCR: 12 patients undergoing elective surgery and 11 emergency surgery; there were 5 deaths, 3 of which were due to respiratory failure following Covid-19-induced pneumonia.ConclusionsAlthough this study has some limitations, it has shown the non-inferiority of surgical outcomes during the COVID pandemic, and indicates that resuming elective surgery is safe.Trial registrationClinicaltrials.gov identifier: NCT04780594.