Performance Analysis Of Networks Research Articles

Performance analysis of P2P network based on differentiated service Geo/Geo/1 + 1 queue

Performance analysis of P2P network based on differentiated service Geo/Geo/1 + 1 queue

Latency and Residual Energy Analysis of MIMO Heterogeneous Wireless Sensor Networks

Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within WSNs. This approach operates effectively, especially in challenging and resource-constrained environments. By facilitating collaboration among sensor nodes, Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments. Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring, industrial automation, and healthcare applications. This research paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO using Network Simulator NS2.35 for analysis of End to End Delay for packet transmission and Residual energy of nodes. The research work shows application of MIMO in Wireless Sensor Networks with considerable improvements in Quality of Service parameters which is achieved through Spatial Multiplexing and Diversity Gain. MIMO enables multiple spatial streams, allowing several data streams to be transmitted simultaneously on the same channel. This increases the overall throughput as multiple sensors can transmit their data concurrently without interference. MIMO systems also provide diversity gain by transmitting multiple copies of the same data over different antennas which helps in mitigating the effects of fading and interference, resulting in a more reliable and higher-throughput communication link as compared to a SISO channel. Another advantage of employing MIMO in WSN is reduction in End-to-End delays in data transmission. Last but not the least, MIMO can be configured to optimize the power consumption of individual sensors by adjusting the number of antennas used and transmission power levels based on channel conditions. Hence, MIMO can help to extend the network's lifetime by conserving energy in resource-constrained sensor nodes by preservation of Residual Energy.

Performance Evaluation and Analysis of Urban-Suburban 5G Cellular Networks

5G is the fifth-generation technology standard for the new generation of cellular networks. Combining 5G and millimeter waves (mmWave) gives tremendous capacity and even lower latency, allowing you to fully enjoy the 5G experience. 5G is the successor to the fourth generation (4G) which provides high-speed networks to support traffic capacity, higher throughput, and network efficiency as well as supporting massive applications, especially internet-of-things (IoT) and machine-to-machine areas. Therefore, performance evaluation and analysis of such systems is a critical research task that needs to be conducted by researchers. In this paper, a new model structure of an urban-suburban environment in a 5G network formed of seven cells with a central urban cell (Hot spot) surrounded by six suburban cells is introduced. With the proposed model, the end-user can have continuous connectivity under different propagation environments. Based on the suggested model, the related capacity bounds are derived and the performance of 5G network is studied via a simulation considering different parameters that affect the performance such as the non-orthogonality factor, the load concentration in both urban and suburban areas, the height of the mobile, the height of the base station, the radius, and the distance between base stations. Blocking probability and bandwidth utilization are the main two performance measures that are studied, however, the effect of the above parameters on the system capacity is also introduced. The provided numerical results that are based on a network-level call admission control algorithm reveal the fact that the investigated parameters have a major influence on the network performance. Therefore, the outcome of this research can be a very useful tool to be considered by mobile operators in the network planning of 5G.

Uplink Performance Analysis of Wireless Energy Harvesting-Enabled NOMA-based Networks

Uplink Performance Analysis of Wireless Energy Harvesting-Enabled NOMA-based Networks

Performance Analysis of Grid Configuration Wireless Sensor Network using Different Packet Frequency for Oil and Gas Downstream Pipeline

Over the most recent few years, there has been a shift away from utilizing costly links to communicate information from different sensors, including those estimating wind, vibration, temperature, and stickiness, to observing locales. This progress has been worked with by the reception of Wireless sensor networks (WSNs), which proposition expanded adaptability and more extensive inclusion capacities. In different businesses, these organizations have acquired ubiquity because of their flexibility. In particular, with regards to observing oil and gas offices, framework-based WSNs demonstrate profoundly appropriate for covering broad regions, especially inside the downstream period of the oil and gas handling chain. The essential point of this examination is to research how different bundle frequencies, the quantity of nodes, and directing conventions influence a lattice-based WSN. The review presents two sorts of steering conventions: responsive (AODV) and proactive (OLSR), utilizing a lattice hub plan and trying different things with different bundle frequencies. The reenactment results uncover that as the bundle recurrence builds, there is a perceptible decrease in execution, no matter what the organization's size. This presentation decline is clear in measurements like the conveyance proportion, network reasonableness, and the presence of aloof nodes inside the organization, particularly while sending 80 nodes or more. Moreover, it's significant that the AODV steering convention outflanks the OLSR partner concerning throughput, conveyance proportion, and the presence of passive nodes.

ANALISIS SIMULASI PROTOKOL ROUTING DINAMIS OSPF UNTUK PENINGKATAN EFISIENSI JARINGAN HYBRID KAMPUS UNUD DENPASAR

UNUD GDLN building located in UNUD Sudirman campus acts as an information and communication technology service center as an internet access service provider, radio broadcast and online learning. The UNUD Campus network currently uses a static hybrid routing protocol, where the static routing protocol has the disadvantage that the network administrator must always reconfigure the network if there is a topology change. The Open Shortest Path First (OSPF) dynamic routing protocol can be used as a solution to overcome the weaknesses of static routing protocols because it is more suitable for larger networks and has the advantage of automatically determining the best route. This research aims to analyze the application of OSPF routing protocol in UNUD Denpasar Campus with GNS3 simulation. This research uses Quality of Service (QoS) parameters to analyze network performance, and test scenarios by PING with large data transmission that imitates YouTube video streaming. The results showed that OSPF dynamic routing protocol has better performance and has met the TIPHON standard with very good results for packet loss, throughput, and delay parameters and good results for jitter parameters. Tests on static routing protocol simulations and OSPF routing protocols are carried out by comparing the transmission process based on the resolution on YouTube video streaming imitation, starting with 360p, 480p, 720p and 1080p resolutions. Based on the results of the study, it can be concluded that OSPF routing is more suitable and produces better parameter values when transmitting streaming video with a resolution of 480p, 720p and 1080p, while the transmission of streaming video with a resolution of 360p is more suitable for static routing which is more suitable for transmission with lower resolutions.

Performance Analysis of Underwater Acoustic Sensor Networks With Buffer Constraint

Performance Analysis of Underwater Acoustic Sensor Networks With Buffer Constraint

Performance Analysis and Comparison of Nonideal Wireless PBFT and RAFT Consensus Networks in 6G Communications

Performance Analysis and Comparison of Nonideal Wireless PBFT and RAFT Consensus Networks in 6G Communications

Performance Analysis of LEO Satellite-Based IoT Networks in the Presence of Interference

Performance Analysis of LEO Satellite-Based IoT Networks in the Presence of Interference

Performance analysis of multi-hop low earth orbit satellite network over mixed RF/FSO links

Low earth orbit satellite (LEOS) communication has emerged as a promising technology to achieve global coverage, while further reducing the end-to-end latency by establishing communication link between LEOSs. In this paper, we analyze the performance of multi-hop LEOS network in terms of bit error rate (BER) and outage probability over mixed radio frequency (RF)/free space optical (FSO) links where RF link is used for the link between ground terminal and LEOS and FSO link is used for establishing inter-satellite links (ISLs). The derived closed-form results are confirmed via Monte Carlo simulations and we show the effect of the number of satellite hops on outage probability and average BER performance by comparing scenarios both with and without ISLs.

A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT network

The exploitation of unmanned aerial vehicles (UAVs) in enhancing network performance in the context of beyond-fifth-generation (5G) communications has shown a variety of benefits compared to terrestrial counterparts. In addition, they have been largely conceived to play a central role in data dissemination to Internet of Things (IoT) devices. In the proposed work, a novel stochastic geometry unified framework is proposed to study the downlink performance in a UAV-assisted IoT network that integrates both UAV-base stations (UAV-BSs) and terrestrial IoT receiving devices. The framework builds upon the concept of the aerial UAV corridor, which is modeled as a finite line above the IoT network, and the one-dimensional (1D) binomial point process (BPP) is employed for modeling the spatial locations of the UAV-BSs in the aerial corridor. Subsequently, a comprehensive SNR-based performance analysis in terms of coverage probability, average rate, and energy efficiency is conducted under three association strategies, namely, the nth nearest-selection scheme, the random selection scheme, and the joint transmission coordinated multi-point (JT-CoMP) scheme. The numerical results reveal valuable system-level insights and trade-offs and provide a firm foundation for the design of UAV-assisted IoT networks.

Performance analysis of successive di-state full-duplex cooperative wireless cellular networks

This paper examined uplink and downlink di-state (primary and secondary) situations to build the theoretical and practical realization of a bidirectional cooperative wireless cellular network. In the primary scenario, full-duplex (FD) base stations support two sets of half-duplex (HD) users, where the transmitter (uplink) and receiver (downlink) respectively. Each uplink transmitted signal is rotated in a variant phase through a set of scalars known to the base stations before transmission. The signal from the transmitter ensures the reconfigurable receiver antennas at the base stations can configure the received signal as decoded signals. The proposed work exposed strong self and inter-user interference from the transmitter during demonstrating FD wireless communication mode that destroyed network functionality at the base stations. The occurred self-interference signals from the transmitter are neutralized using precoding and beam-forming technique. During the secondary scenario, decoded base station signals are independently encoded and transmitted to the downlink users. Base stations aid the inter-user interference management by precoding the uplink transmission data and forwarding it to the downlink users. Consequently, the inter-user interference signals are aligned using the span interference alignment technique. A proposed cooperative additional receiver (listener U1) can decode the desired signals and helps in recovering and reconstructing the interference signals. This proposed work completely characterized and evaluated the degree of freedom (DoF) for unknown channel state information at the transmitter (CSIT); whereas achievable lower and upper bound DoF are demonstrated for the partial CSIT. At last, the analytical and simulation results reveal the sum of DoF improvement for unknown and partial CSIT.

Performance Analysis of RF-Powered Multi-device Diamond Relay IoT Network Using Adaptive NOMA

Performance Analysis of RF-Powered Multi-device Diamond Relay IoT Network Using Adaptive NOMA

Secured Performance Analysis of Double Scattering MIMO Network

Secured Performance Analysis of Double Scattering MIMO Network

Empirical performance analysis and ML-based modeling of 5G non-standalone networks

Fifth Generation (5G) networks are becoming the norm in the global telecommunications industry, and Mobile Network Operators (MNOs) are currently deploying 5G alongside their existing Fourth Generation (4G) networks. In this paper, we present results and insights from our large-scale measurement study on commercial 5G Non Standalone (NSA) deployments in a European country. We leverage the collected dataset, which covers two MNOs in Rome, Italy, to study network deployment and radio coverage aspects, and explore the performance of two use cases related to enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communication (URLLC). We further leverage a machine learning (ML)-based approach to model the Dual Connectivity (DC) feature enabled by 5G NSA. Our data-driven analysis shows that 5G NSA can provide higher downlink throughput and slightly lower latency compared to 4G. However, performance is influenced by several factors, including propagation conditions, system configurations, and handovers, ultimately highlighting the need for further system optimization. Moreover, by casting the DC modeling problem into a classification problem, we compare four supervised ML algorithms and show that a high model accuracy (up to 99%) can be achieved, in particular, when several radio coverage indicators from both access networks are used as input. Finally, we conduct analyses towards aiding the explainability of the ML models.

A Modular IoT-Based Architecture for Logistics Service Performance Assessment and Real-Time Scheduling towards a Synchromodal Transport System

Logistics is significantly impacted by quality/quantity issues associated with data collection and data sharing restrictions. Nonetheless, public data from national entities and internet-of-things (IoT) solutions enable the development of integrated tools for performance analysis and real-time optimization of logistics networks. This study proposes a three-module data-driven system architecture that covers (a) logistics data collection tools, (b) logistics services performance evaluation, and (c) the transition to synchromodal systems. Module 1 integrates multisource data from national logistics platforms and embedded devices placed within intermodal containers. A multigraph representation of the problem is conceived. Environmental, economic, and operational data are generated and injected into a digital twin. Thus, key performance indicators (KPIs) are computed by simulation or direct transformation of the collected data. Module 2 uses Multi-directional Efficiency Analysis, an optimization algorithm that benchmarks multimodal transportation routes of containers using prior KPIs. Outputs are a technical performance index relevant to logistics clients and improvement measures for logistics service providers. A real case study application of the solution proposed for Module 2 is presented. Module 3 provides real-time scheduling and assignment models using CP-sat solvers, accommodating varying system dynamics and resource availability, minimizing makespan and operational costs.

Localization over distributed mobile adaptive networks based on coarsely quantized data

The localization is a very important task in many internet of things (IoT) based applications. Due to high requirements of communication cost and power consumption, however, existing localization methods are hard to apply for practical IoT applications with low power and narrow frequency. To answer this problem, in this paper, we propose a fully distributed low energy localization method by incorporating the distributed quantization aware least mean square (DQA-LMS) algorithm in a mobile diffusion narrowband IoT (NB-IoT) network. Each mobile network node in this case is assumed to use a low-power and low-resolution analog to digital converter (ADC). First, we address the performance analysis of the mobile networks in the presence of the quantized data. Second, we evaluate the localization performance of the proposed method with differently leveled quantization data and confirm that it can perform suitably even in the one-bit data case. Finally, we collate the localization performance of the Mobile DQA-LMS with the mobile distributed LMS (Mobile DLMS) and show that for all the quantized data cases, the performance of the mobile DQA-LMS is better than the conventional DLMS in terms of mean square deviation (MSD).

Reputation-based Raft-Poa layered consensus protocol converging UAV network

Integration of blockchain technology offers a robust solution for ensuring reliable data transmission within unmanned aerial vehicle (UAV) networks. Nevertheless, it is crucial to address challenges associated with UAV networks, including their dynamic nature, high latency, limited scalability, and algorithmic inefficiencies. Hence, our proposal involves integrating UAV networks with blockchain technology to enhance their performance by optimizing the consensus algorithm based on network efficiency. We first propose a comprehensive framework for optimizing network performance based on network tomography, incorporating a systematic analysis of network performance and fault avoidance strategies. To improve analysis of the core network’s real-time performance, we also propose a topology prediction method based on an effective probability matrix. Additionally, we establish a calculation method for optimally placing network monitoring points in the core network for enhanced efficiency. We then introduce an adjustable reputation-based Raft-Poa layered consensus protocol that improves consensus protocol scalability and efficiency. To tackle data and node security concerns, we further propose a trust management mechanism based on group signatures. This mechanism verifies the authenticity of node data and identifies malicious nodes. Finally, we validate the protocol’s effectiveness and compare the algorithm’s effectiveness with MMP, Raft, Poa, etc. The simulation results of this protocol show remarkable improvements in network communications and consensus process efficiency, and reductions in communication latency and node utilization rates.

Proposal of a regional grid cluster model for analysis of electrical power network performance

Proposal of a regional grid cluster model for analysis of electrical power network performance

Performance Analysis of Satellite-Vehicle Networks With a Non-Terrestrial Vehicle

Performance Analysis of Satellite-Vehicle Networks With a Non-Terrestrial Vehicle