Transmission Capacity Of Networks Research Articles

Probabilistic Protection for Both Computing and Transmission Capacities of Virtual Networks Under Multiple Facility Node Failures

Probabilistic Protection for Both Computing and Transmission Capacities of Virtual Networks Under Multiple Facility Node Failures

Design of 1450-1500nm Bismuth-doped Fiber Laser

With the rapid development of information technology, people's demand for the transmission capacity of fiber optic communication networks is increasing. How to broaden the bandwidth of communication systems has become one of the key issues in the field of communication. Researchers have found that the operating bandwidth of amplifiers mainly limits the bandwidth of communication systems. Although multiple solutions have been proposed and implemented to address this issue, there are still many gaps in the design of full-band multi wavelength-related light sources. By studying the three-level system of bismuth ions, the rate equation and power transfer equation of a bismuth ion doped fiber laser are simulated, and the pump power threshold and output power are calculated. Using MATLAB for simulation experiments, the relationship between laser power and pump power, as well as their variation with propagation distance, were ultimately obtained. The simulation results show that under 830 pump lights, the pump light threshold power is 10W. After reaching the threshold power, the pump light power and laser power have a linear relationship, and as the propagation distance increases, the pump light power gradually decreases and the laser power gradually increases. The analysis shows that the power generated by the signal light in this band meets the theoretical standards, which verifies the correctness of the scheme.

Fractal Engineering Integration in Antenna Arrays: A Comparative-review for Advanced Transceiver Systems with 5G/IoT Connectivity

The growing demand for space-efficient antennas compatible with portable electronic gadgets inspired the integration of recursively iterated fractal geometries (characterized by self-similarity, space-filling, and multiband/wideband capabilities) in antenna designs. Therefore, this article conducts an extensive survey on fractal-based single-port and multi-port patch antenna designs with multiband and ultrawideband characteristics for their implementation in 5G/IoT (Internet of Things) devices. The survey begins with a basic overview of fractal geometries and the iterated function system (IFS) technique employed for their generation. Further, it highlights the limitation of multipath fading prevalent in single-port antenna arrays that can be overcome by adopting multiple-input multiple-output (MIMO) technology. The MIMO antenna systems are vital for 5G networks to enhance data transmission rate, network capacity, and system reliability. Apart from these admirable attributes, the closely packed antenna elements in the MIMO configuration result in a severe mutual coupling. To address this limitation, various isolation enhancement techniques developed by distinguished researchers are thoroughly discussed in this article, detailing their merits and demerits. At last, this article portrays diverse band-notch structures integrated into the antenna designs to eradicate the existing interfering narrow bands in the ultrawideband (UWB) spectrum. The underlying reason for conducting this survey is to aid antenna designers and academicians with a thorough knowledge of distinct fractal geometries, various isolation improvement approaches, and band-notch techniques on a single platform, desired for designing 5G/IoT-based antenna systems.

Net gain in C+L band from LED pumped broadband emission in Er3+-doped oxyhalide tellurite glass

Expanding gain bandwidth into the L-band for erbium-doped fiber amplifiers (EDFAs) is a crucial strategy to overcome limitations in prevalent C-band focused commercial silica-based EDFAs, significantly boosting optical network transmission capacity. Herein, we synthesized Er3+-doped broadband near-infrared emission tellurite glasses utilizing the melt quenching process, systematically exploring the impact of ZnCl2 on the glass structure and optical properties. The 82TeO2–3Nb2O5–15ZnCl2–3Er2O3 (TNZ15) glass emerged as a standout candidate for broadband amplifiers around wavelength at 1.55 μm. With escalating ZnCl2 concentration, a discernible red shift in the emission peak wave lines was observed, accompanied by an expansion of the full width at half maximum (FWHM) from 98 nm to 106 nm. Noteworthy characteristics of all samples included exceptional thermal stability and elevated near-infrared (NIR) transmittance. Application of the Judd-Ofelt (J-O) theory facilitated the calculation of J-O parameter intensity, providing deeper insights into the optical behavior of the materials. Finally, the evaluation of TNZ15 planar optical waveguides, employing the vertical top pumping mode of two 980 nm LEDs, encompassed both the C-band (1530–1565 nm) and the L-band (1565–1625 nm). The results underscore the potential of TNZ15 glass as a promising gain material for broadband optical amplifiers and lasers, offering valuable insights into the development of next-generation optical amplification technologies.

Enhancement of power transfer capacity of transmission network using multilevel multifunction inverter

This article presents a multilevel multifunction inverter (MLMFI) with a novel controller for the grid-connection of a solar array. The aim of this work is to improve the technology of the power transfer capacity of existing transmission lines in order to alleviate the current energy crisis. An effective mathematical modelling of an MLMFI configuration having two series-connected H-bridges per phase with isolated solar arrays is presented. A novel closed-loop controller is proposed for reference signal generation using the PWM technique. With the proposed controller, the power flow in a transmission line is analysed for daytime and nighttime conditions. The proposed controller performance was tested on a realistic single-machine infinite-bus power system with midpoint MLMFI using MATLAB simulation software. The proposed MLMFI-based solar array enhanced the stable power transfer limit of a transmission line. A comparative analysis between conventional and proposed controllers for power flow and transient stability studies was also presented. The proposed MLMFI results were validated by developing an experimental model.

RESEARCH ON NODE NETWORK TRANSMISSION CAPACITY PREDICTION MODEL FOR LARGE SCALE REMOTE SENSING DATA COLLECTION

Abstract. In recent years, the use of remote sensing technology has grown exponentially in various industries such as agriculture, forestry, and urban planning. Remote sensing data collection systems rely on a network of nodes to collect and transmit data. The transmission capacity of these node networks is a critical factor in the performance and efficiency of the entire system. However, accurately predicting the transmission capacity of a node network can be a challenging task. To carry out large scale open remote sensing data collection, it is necessary to predict the network transmission capacity of nodes in the face of the difference in the execution speed of each node for various tasks. It is necessary to predict the network transmission capacity of nodes. In this research, we propose a node network transmission capacity prediction model for large scale remote sensing data collection using a combination of Particle Swarm Optimization (PSO) and Backpropagation (BP) algorithms. The proposed PSO-BP model aims to accurately predict the transmission capacity of a node network in a remote sensing data collection system. The model is tested and evaluated using a large-scale dataset and the results show that the proposed model outperforms existing models in terms of prediction accuracy. This work contributes to the field of remote sensing data collection by providing a reliable and efficient method for predicting the transmission capacity of node networks.

Simulating flexibility, variability and decentralisation with an integrated energy system model for Great Britain

Energy system models allow the development and assessment of ambitious transition pathways towards a sustainable energy system. However, current models lack adequate spatial and temporal resolution to capture the implications of a shift to decentralised energy supply and storage across multiple local energy vectors to meet spatially variable energy demand. There is also a lack of representation of interactions with the transport sector as well as national and local energy system operation. Here, we bridge these gaps with a high-resolution system-of-systems modelling framework which is applied to Great Britain to simulate differences between the performance of decarbonised energy systems in 2050 through two distinct strategies, an electric strategy and a multi-vector strategy prioritising a mix of fuels, including hydrogen. Within these strategies, we simulated the impacts of decentralised operation of the energy system given the variability of wind and across flexibility options including demand side management, battery storage and vehicle to grid services. Decentralised operation was shown to improve operational flexibility and maximise utilisation of renewables, whose electricity supplies can be cost-effectively converted to hydrogen or stored in batteries to meet peak electricity demands, therefore reducing carbon-intensive generation and the requirement for investment in expanding the electricity transmission network capacity.

The calculation and optimal allocation of transmission capacity in natural gas networks with MINLP models

The transmission capacity of gas pipeline networks should be calculated and allocated to deal with the capacity booking with shippers. Technical capacities, which depend on the gas flow distribution at routes or interchange points, are calculated with a multiobjective optimization model and form a Pareto solution set in the entry/exit or point-to-point regime. Then, the commercial capacities, which can be directly applied in capacity booking, are calculated with single-objective optimization models that are transformed from the above multiobjective model based on three allocation rules and the demand of shippers. Next, peak-shaving capacities, which are daily oversupply or overdelivery amounts at inlets or deliveries, are calculated with two-stage transient optimization models. Considering the hydraulic process of a pipeline network and operating schemes of compressor stations, all the above models are mixed-integer nonlinear programming problems. Finally, a case study is made to demonstrate the ability of the models.

Performance analysis of RSMA-based cognitive networks with random distribution of eavesdroppers

Due to the pace of various emerging wireless communication technologies and new application services innovation, network information security, and capacity requirements have become a hot issue of concern. In order to improve network security performance and transmission capacity, researchers have proposed cognitive wireless network and physical layer security as potential solution. Most of the current research work focuses on the assumption that the location of the eavesdropping node is fixed. Starting from the physical layer security and based on the random geometry theory, this paper studies the security performance of cognitive wireless networks under the scenario of random distribution of eavesdropping nodes based on rate splitting multiple access, proposes a system model, and deduces the closed form solutions of connection interruption probability and security interruption probability of secondary users in the cognitive wireless network. The results show that the security interruption probability is related to the density and security of eavesdropping nodes. Finally, the correctness of the formulas is verified by simulation analysis.

A Routing Optimization Method for Software-Defined Optical Transport Networks Based on Ensembles and Reinforcement Learning

Optical transport networks (OTNs) are widely used in backbone- and metro-area transmission networks to increase network transmission capacity. In the OTN, it is particularly crucial to rationally allocate routes and maximize network capacities. By employing deep reinforcement learning (DRL)- and software-defined networking (SDN)-based solutions, the capacity of optical networks can be effectively increased. However, because most DRL-based routing optimization methods have low sample usage and difficulty in coping with sudden network connectivity changes, converging in software-defined OTN scenarios is challenging. Additionally, the generalization ability of these methods is weak. This paper proposes an ensembles- and message-passing neural-network-based Deep Q-Network (EMDQN) method for optical network routing optimization to address this problem. To effectively explore the environment and improve agent performance, the multiple EMDQN agents select actions based on the highest upper-confidence bounds. Furthermore, the EMDQN agent captures the network's spatial feature information using a message passing neural network (MPNN)-based DRL policy network, which enables the DRL agent to have generalization capability. The experimental results show that the EMDQN algorithm proposed in this paper performs better in terms of convergence. EMDQN effectively improves the throughput rate and link utilization of optical networks and has better generalization capabilities.

Space-mode compressor by using nano-pixel

Spatial-division-multiplexing, as a promising way to enhance the fiber transmission capacity of optical networks, has been widely researched, and still suffers from the problem of device size increasing along with the space-mode order increasing. In order to solve this problem, an optical mode field compression method is needed, however, it is difficult to realize for traditional optical waveguide. To achieve a highly dense photonic integrated circuit for the transmission of higher order space-mode, a space-mode compressor using nano-pixel structure was proposed and investigated in this work. A supervised machine learning model using a deep neural network was used to design and optimize the space-mode compressor based on nano-pixel structure. As a simulated result, we achieved possible nano-pixel configurations for the purpose of mode-compression and there is a more than 50% size compression for the 0th and 1st order modes, as well as a 39.3% size compression for the 2nd and 35% for 3rd order modes.

Multi-period optimal infrastructure planning of natural gas pipeline network system integrating flowrate allocation

The purpose of flow allocation is to give full play to the transmission capacity of the pipeline network system and complete the transportation task with less operation cost. When the flow allocation cannot balance the changes of upstream gas source and downstream demand, the pipeline network system needs to be planned and constructed. Therefore, this paper aims to propose an optimization method allowing the simultaneous optimization of infrastructure planning and the flowrate allocation in each decide cycle by explicit consideration of the corresponding operational constraints. The constraints include the limit of gas supply and user demand, the transmission capacity of pipeline network, the balance of node flowrate, and the capacity of gas storage. The injection, storage and production capacity of gas storage is considered. A case study including multi scene settings shows the feasibility of the proposed method. The results show that compared with the annual scale, the half-year scale can better consider the peak regulation effect of gas storage, and the utilization rate of gas storage is improved by 12.88%. Multiple options that allow for both expansion and new pipelines are more economical than a single option. Specifically, the total cost under multi-option planning is 8.24% lower than only expansion is allowed, and 8.32% lower than only new construction is allowed. In addition, the sensitivity analysis is carried out to study the impact of the unit pipeline transmission cost, unit construction cost and lead time of pipeline on the pipeline construction scheme. The improvement of gas storage utilization rate, gas storage operation and pipeline network transmission capacity verify that the proposed planning model has the ability to improve the system operation efficiency and reduce the total cost.

Survivable Routing, Spectrum, Core and Band Assignment in Multi-Band Space Division Multiplexing Elastic Optical Networks

The rapid growth in Internet traffic has contributed to the need to expand network transmission capacity. Multi-band (MB) using existing standard single-mode fibers (SMFs) in the free band is an ideal way to increase the capacity of the fiber. However, the introduction of MB has transferred space division multiplexing - elastic optical networks (SDM-EONs) to multi band-SDM-EONs (MB-SDM <strike xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</strike> EONs), and changed routing, spectrum and core assignment (RSCA) problem to the routing, spectrum, core and band assignment (RSCBA) problem. At the same time, it introduces a new issue named stimulated Raman scattering (SRS), which affects transmission quality. Although an expanded fiber can carry more services, a large number of services will be interrupted if a link fails, which will bring huge losses. Therefore, it is necessary to propose a reasonable protection strategy to ensure reliable transmission quality. In this paper, the survivable RSCBA problem in MB-SDM-EONs is studied, which copes with link failures and considers SRS in signal-to-noise ratio (SNR) analysis. In order to solve the problem, we propose a band partition protection scheme: working and protection resources are allocated in different frequency bands for increasing SNR in a fault-free network. We formulate this problem and band partition protection scheme as an integer linear programming (ILP) model, which takes into account inter-core crosstalk and SNR analysis. Furthermore, a heuristic algorithm based on genetic algorithm is proposed for large-scale networks. We evaluate the performance of the proposed approaches through experimental simulation. The results demonstrate that both proposed approaches are effective in finding the optimal solutions.

Optimal Deployment of Mobile MSSSC in Transmission System

With the rapid development of the renewable energy source (RES), network congestion management is increasingly important for transmission system operators (TSOs). The limited transmission network capacity and traditional intervention methods result in high RES curtailment. The near-term, powerful, and flexible solutions, such as advanced flexible AC transmission systems (FACTS), are considered to mitigate the risks. The mobile modular static synchronous series compensator (MSSSC) is one of the grid-enhancing solutions. The mobility of the solution allows it to offer fast deployment and seasonal redeployability with limited cost. The demonstration of the mobile MSSSC solution has shown significant benefits for RES curtailment reduction, network congestion alleviation, and facilitating the demand and RES connection. For unlocking the true value of the mobile solution, they should be optimally allocated in the transmission networks. This paper develops a security-constrained DCOPF-based optimisation tool to investigate the optimal allocation of the mobile MSSSC solution in transmission networks. A linear mobile MSSSC model with the operation dead-band was introduced that can be used in large-scale realistic power system planning. The proposed model was implemented in the IEEE 118-bus system to assess the performance of the mobile MSSSC.

SECURING TEXT MESSAGE WITHIN A VIDEO USING LSB STEGANOGRAPHY AND RSA ALGORITHM

The Internet is the media because of which it is feasible to move information from one spot to somewhere else with exceptionally rapid. Be that as it may, it is exceptionally unsafe to move information over the web. Thus to keep up with protection and to keep an unapproved individual from extricating data steganography procedure is utilized. Steganography is the study of hiding restricted data. The restricted data is as text, picture, sound and video. This restricted data can be hiding in the text, picture, sound and video. Hiding privileged intel in a video document is called video steganography. In this task, one of the most outstanding secure steganography procedures (LSB) is introduced. With the development in advanced correspondence advances and the fast development of network transmission capacity, the Internet has ended up being an ordinarily involved channel for sending many reports for example, sound, video, picture, and message in advanced structure. Many practices have been offered and produced for giving the protected transmission of information. The focal point of the ebb and flow research is on the plan of data hiding procedures utilized for sending restricted information where computerized pictures are chosen as the cover-media. This part has distinguished the issues in the present picture steganography plans.

Optical-Fiber Cable Employing 200-μm-Coated Four-Core Multicore Fibers

Combining small-diameter optical-fiber technology and space-division multiplexing employing multicore fiber (MCF) is a promising method for further increasing the transmission capacity of optical networks. In this work, four-core MCFs with a 200-&#x03BC;m coating diameter (200-4CFs), reduced from 250 &#x03BC;m, were fabricated. The 200-4CFs had featured almost the same characteristics as the 4CFs with a 250-m cladding diameter. The 200-4CFs were ribbonized and cabled. This cabling represents the first time approach employing an MCF with a 200-&#x03BC;m coating. The attenuation increase caused by the cabling was compared with that of 4CFs with 250-&#x03BC;m coating diameter and SMFs. The effective bending radius of the 4CFs in a cable employing partially bonded ribbons was investigated and determined to be smaller than the cable-drum radius. Mechanical and environmental tests based on IEC standards were performed on the cable employing 200-4CFs, and the cable exhibited excellent performance. The scalability of high-fiber-count cables employing 200-4CFs was also demonstrated. Finally, the applicability of an automatic splice with core identification via side-view alignment is presented.

Collision-free optimal packet scheduling algorithm for multi-hop wireless IoT networks

One of the key challenges for the IoT (Internet of Things) evolution is the network connectivity provision to a large number of resource-limited low-cost IoT devices. To meet this challenge, various efforts have been made in today’s wireless network technologies, such as LTE eMTC, 5G NB-IoT, IEEE 802.11ah, BLE, etc. Meanwhile, most of these technologies consider multi-hop wireless relaying to extend the wireless coverage and to enhance the network transmission capacity. Despite the benefits, however, the usage of multi-hop relaying has been limited in the real world, because of the performance degradation caused by the self-interference between adjacent wireless links. In this paper, we tackle the problem of alleviating the performance degradation in the multi-hop wireless network for IoT devices. In particular, we target low cost IoT devices that are equipped with inexpensive wireless links such as WiFi, IEEE 802.15.4, and Bluetooth. Our approach is to avoid self-interference by controlling the transmission timing at each hop. More specifically, our design goal is to minimize the data delivery delay for fast IoT sensing by preventing packet collisions (i.e., collision-free transmission). Since the retransmission at the IoT devices is eliminated, buffering at the intermediate nodes is not necessary so that no extra storage is consumed at the IoT devices to store the data being relayed. We present an algorithm to produce the packet transmission schedule at each hop. We prove that our algorithm is optimal in terms of data delivery delay (i.e., minimal delay is guaranteed) while collision between transmissions is completely avoided.

Toward a neurophysiological measure of image quality perception based on algebraic topology analysis

The bandwidth of internet connections is still a bottleneck when transmitting large amounts of images, making the image quality assessment essential. Neurophysiological assessment of image quality has highlight advantages for it does not interfere with natural viewing behavior. However, in JPEG compression, the previous study is hard to tell the difference between the electroencephalogram (EEG) evoked by different quality images. In this paper, we propose an EEG analysis approach based on algebraic topology analysis, and the result shows that the difference between Euler characteristics of EEG evoked by different distortion images is striking both in the alpha and beta band. Moreover, we further discuss the relationship between the images and the EEG signals, and the results implied that the algebraic topological properties of images are consistent with that of brain perception, which is possible to give birth to brain-inspired image compression based on algebraic topological features. In general, an algebraic topology-based approach was proposed in this paper to analyze the perceptual characteristics of image quality, which will be beneficial to provide a reliable score for data compression in the network and improve the network transmission capacity.

Electromagnetic Transients in Multi-Voltage Transmission Lines during Non-Simultaneous Faults

It is vitally important that a transmission network provides a continuity of electricity to end users and that the transmission system operator prioritizes its safety and reliability. This article presents the possibilities of using multi-track overhead lines with varying levels of rated voltage, run on a common support structure. This solution would ensure safe operation of the system, reduce the area used for the construction of new overhead lines, and, at the same time increase the transmission network capacity. This article focuses on the method of modeling overhead lines for the analysis of electromagnetic transient states that occur during non-simultaneous disturbance phenomena. This article presents the idea of multi-circuit, multi-voltage lines and their validity of use in power systems. An analysis of electromagnetic transient states for non-simultaneous disturbances in multi-path, multi-voltage lines is presented. This analysis has been made on the basis of a network model, using ATP-EMTP (Alternative Transients Program-Electromagnetic Transients Program) software for solutions, for a Polish power system. Particular attention was paid to the most unfavorable phenomena appearing in the modeled system. The impact of the emerging electromagetic transients in multi-path, multi-voltage lines was evaluated. It was shown that the specificity and rapid changeability of the emerging electromagnetic transients and lack of a universal model of the overhead power line make the analyses of electromagnetic transients highly labor-intensive and time-consuming. Each change is connected with the necessity to create new line models for the study of electromagnetic transient states dependent on many factors.

Multi-wavelength 128 Gbit s−1 λ −1 PAM4 optical transmission enabled by a 100 GHz quantum dot mode-locked optical frequency comb

Semiconductor mode-locked lasers (MLLs) with extremely high repetition rates are promising optical frequency comb (OFC) sources for their usage as compact, high-efficiency, and low-cost light sources in high-speed dense wavelength-division multiplexing transmissions. The fully exploited conventional C- and L- bands require the research on O-band to fulfil the transmission capacity of the current photonic networks. In this work, we present a passive two-section InAs/InGaAs quantum-dot (QD) MLL-based OFC with a fundamental repetition rate of ∼100 GHz operating at O-band wavelength range. The specially designed device favours the generation of nearly Fourier-transform-limited pulses in the entire test range by only pumping the gain section while with the absorber unbiased. The typical integrated relative intensity noise of the whole spectrum and a single tone are −152 and −137 dB Hz−1 in the range of 100 MHz–10 GHz, respectively. Back-to-back data transmissions for seven selected tones have been realised by employing a 64 Gbaud four-level pulse amplitude modulation format. The demonstrated performance shows the feasibility of the InAs QD MLLs as a simple structure, easy operation, and low power consumption OFC sources for high-speed fibre-optic communications.