In recent times, an increased number of vehicles create a traffic congestion problem in urban enrollment. In recent scientific research to normalize the communication issues of the vehicles, unmanned aerial vehicles (UAVs) are embedded with the vehicular communication mainly to control the traffic congestion and insufficient bandwidth utilization of the vehicles. The aerial vehicles are highly flexible and efficient so that they are able to control the vehicles in an efficient manner. But still certain drawbacks are present in the aerial vehicles such as improper localization and ineffective data transmission. To solve these flaws, in this article, reliable data transmission and efficient vehicle path planning in the cooperative communication model (RDTEVP) is developed. The core modules of this model are reliability base network modeling and path planning based routing. Through this process the efficiency of the network is maximized and the data transmission quality is improvised. This model is structured to analyses the device performance are packet delivery ratio, network throughput, energy efficiency, average delay and routing overhead. The term delay and routing overhead are greatly minimized in the RDTEVP when compared with the earlier schemes.
A novel energy consumption model and Grey Wolf optimization model (ECGWO) is developed in the vehicular network to attend high efficiency among the vehicles. Reduction of power utilization for each transmission among the vehicles from one place to another, helps to improvise the efficiency of the network. Providing optimization at the time of data transmission the information gets travelled in optimal path so that the network delay and overhead is greatly reduced. As a whole, this model provides a better communication standard for the vehicles in the network. The proposed model is the data success rate, data loss rate, average delay, network throughput and routing overhead. The simulation result shows that the ECGWO has better success rate and throughput than other related methods.
The integration of vehicular communication and unmanned aerial vehicle (UAV) technology has become a most trending topic and it occupies maximum of the attention of both the industrial and academic sectors. To achieve high-quality communication with the ground and the air medium, the aerial vehicles are connected to the cellular network so the year energy constraints are normalized. At the time of high speed data transmission the vehicles underwent certain drawbacks like delay during data uplink and high power consumption. To overcome these drawbacks in this article resource management and Generic Algorithm (GA) based scheduling (RMGAS-UAV) is developed for aerial networks based environments. The core modules of RMGAS-UAV are an efficient system model and GA based drone scheduling. This models the data transmission quality of the aerial vehicles are highly improved. This network model is designed in the software called NS3 and the parameters which are taken for result calculation are the data delivery ratio, network throughput, routing overhead, energy efficiency, and energy consumption. From the calculated results, it is shown that the RMGAS-UAV obtained better results in terms of the energy efficiency and data delivery when compared with the earlier methods.
The aerial vehicles are highly flexible and cost effective so that it is able to control the vehicles in a better manner. Currently the aerial vehicles are used to perform highly confidential data transmission in a collaborative way. Several challenges occurred in search works in terms of limited battery power and environmental condition. To overcome this in this article latency aware optimization for collaborative aerial vehicles (ELAOC-UAVs) are developed. The core modules of this process are traffic model and trajectory design creation and optimization among the unmanned aerial vehicles (UAVs) using glowworm swarm optimization (GSO) algorithm. With the presence of this process the delay occurrences among the aerial vehicles are greatly reduced and that helps to improve the overall performance of the network. The ELAOC-UAVs model is used to measure the performance of the network are data accuracy, data loss, routing overhead, network throughput and average delay. From the final result, it has been proven that the ELAOC-UAVs obtained better results in terms of throughput and data accuracy when compared with the earlier baseline methodology.
In recent times, unmanned aerial vehicles (UAVs) are constructed in the vehicular network. Through this technology the communication becomes more flexible and efficient but still it consists of certain drawbacks in terms of device deployment and data collection. For that purpose, in this article an efficient data collection system and effective relaying model (DCERM-UAV) is constructed in the aerial vehicles to improve the network stability. The core concentrations of these models are providing effective data aggregation, relaying among the vehicles and improving deployment of it. Through this process the stability of the vehicles is increased and that leads to high quality communication among them. The parameters which are used to analyses the performance of the network model are energy efficiency, energy consumption, network throughput, routing overhead and data delivery ratio. From the final results it gets proven that the DCERM-UAV achieves maximum efficiency when compared with the earlier research works.
Rectangular patch antennas are important components in modern wireless communication systems, including 5 G and emerging 6 G technologies. These antennas support highfrequency, high-capacity, and energy-efficient wireless communication. For beamforming, the dimensions of these antennas significantly influence their radiation patterns, and antenna gain. Beamforming technology is essential for 5G and 6G networks, enhancing coverage, capacity, and energy efficiency. Effective beamforming relies on array configurations of rectangular patch antennas, with precise control over antenna patterns to improve signal quality and minimize interference. This article explores the impact of the size of rectangular patch array antenna in the mmWave frequency band. The primary goal is to maximize channel capacity between transmitters and receivers. Our study involves simulations using discretized antenna patterns for various patch array antenna sizes, based on realistic room models and a ray-tracing approach. The results demonstrate that larger antenna arrays can significantly increase network capacity. However, selecting the optimal steering vectors for all antennas becomes more complex with increasing antenna size, but is essential for achieving the best configuration.
The challenge of optimal optical signal transmission in optical fiber networks is crucial for enhancing the network’s reliability, performance, and service quality. Traditional pathfinding methods, such as Dijkstra’s algorithm, focus on finding the shortest path but fail to account for critical factors like optical signal loss and wavelength continuity. This paper proposes a novel algorithm that integrates traditional pathfinding methods with multi-constraint checks to effectively overcome these challenges. Inspired by the similarity between multi-constrained pathfinding in optical networks and vehicle charging path planning model, our approach aims to identify the optimal path in large-scale optical networks quickly. The simulation results demonstrate that our approach successfully addresses the complex requirements of optical signal routing and relay under multiple constraints, achieving promising outcomes.
The response time of Artificial Neural Network (ANN)-inference is of utmost importance in embedded applications, particularly continual stream-processing. Predictive maintenance applications require timely predictions of state changes. This study serves to enable the reader to estimate the response time of a given model based on the underlying platform, and emphasizes the relevance of benchmarking generic ANN applications on edge devices. We analyze the influence of net parameters, activation functions as well as single-and multithreading on execution times. Potential side effects such as tact rate variances or other hardware-related influences are being outlined and accounted for. The results underline the complexity of task-partitioning and scheduling strategies while emphasizing the necessity of precise concertation of the parameters to achieve optimal performance on any platform. This study shows that cutting-edge frameworks don’t necessarily perform the required concertations automatically for all configurations, which may negatively impact performance.
Health risks associated with milk contamination can take many forms. There is currently little data on the trends in microbial contamination and the mapping of its distribution. This study aims to map the spread of microbial contamination in cattle milk throughout ASEAN and assess trends in this area. A database originating from Scopus is collected using Boolean operators. This research used 19,967 papers as references with topics or themes of bacteria, milk, microbes, and antibiotics with loci in the ASEAN region. The analysis results show that 2021 is the peak of article production with 49 articles, followed by 2022 with 40 articles. The most productive institution is Khon Kaen University. Key research topics include antimicrobial resistance, lactic acid bacteria, bovine health issues, and fermentation in milk production. Research on antimicrobial resistance, the use of lactic acid bacteria in dairy products, cow health, and the milk fermentation process needs to be explored further. Collaboration between countries, especially Thailand and Malaysia, must also be improved to produce higher-quality research.
Ultra-light block cipher (ULBC) is a SPN-based block cipher, operates 64 bit state and use 128 bits key. Here, we present meet-in-the-middle (MITM) attack on ULBC. MITM attack strategy proposed by Demirci and Selcuk. In this paper, we partition cipher ULBC in two halves and separate key space by two independent set and observe matching between encryption of first half with decryption of second half. By this method, called MITM attack, we can reduce the key space for exhaustive search. Basic fault analysis of ULBC requires 192 faulty ciphertext to detect full key register. Also, we provide another fault analysis method of ULBC, which requires only average 57 faulty ciphertext to retrieve master key. Here we assume that we can induce nibble fault in after or before substitution layer to any rounds. MITM and differential fault attack particularly exploits weakness like dependency, linearity of designing key schedule.
This work studies performance comparison on radio frequency ($\mathbf{R F}$) energy harvesting ($\mathbf{E H}$) in power splitting (PS) and time-switching (TS) modes in reconfigurable intelligent surfaces (RIS)-aided cooperative spectrum sensing (CSS). CSS model considers multiple primary user (PU) nodes and a single PU emulation attacker (PUEA) node. A distant dependent model of reflected channel gain in RIS antenna is developed for calculating the harvested residual energy (RE). The primary objective is to maximize the total RE while meeting a predefined detection and false alarm probabilities of PU along with the individual secondary user’s (SU’s) energy causality constraint. Simulation results show the efficacy of the proposed work due to the involvement of RIS antenna on total RE, as gain of about 45% and 38.97% for PS and TS modes compared to the existing works while maintaining the above mentioned constraints. Performance of RE with the change in the placement of RIS antenna near/far to PU is analyzed for both PS and TS modes.
Radiofrequency identification (RFID) technology has revolutionized various industries, including transportation systems. This paper explores the implementation of RFID technology in highway toll systems in Malaysia. It focuses on the technical aspects, benefits, challenges, and future prospects of RFID highway sensing. The deployment by PLUS Malaysia Berhad, which integrates automated number plate recognition (ANPR) and aims to achieve a barrier-less, multilane free flow (MLFF) system, is highlighted. This initiative is part of a broader strategy to enhance traffic management and reduce congestion on Malaysian highways.
