Reliable and efficient data dissemination schemein VANET: a review

Vehicular ad-hoc network (VANET), identified as a mobile ad hoc network MANETs with several added constraints. Basically, in VANETs, the network is established on the fly based on the availability of vehicles on roads and supporting infrastructures along the roads, such as base stations. Vehicles and road-side infrastructures are required to provide communication facilities, particularly when enough vehicles are not available on the roads for effective communication. VANETs are crucial for providing a wide range of safety and non-safety applications to road users. However, the specific fundamental problem in VANET is the challenge of creating effective communication between two fast-moving vehicles. Therefore, message routing is an issue for many safety and non-safety of VANETs applications. The challenge in designing a robust but reliable message dissemination technique is primarily due to the stringent QoS requirements of the VANETs safety applications. This paper investigated various methods and conducted literature on an idea to develop a model for efficient and reliable message dissemination routing techniques in VANET

A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network

Vehicular ad-hoc network (VANET) is dynamic and it works on various noteworthy applications in intelligent transportation systems (ITS). In general, routing overhead is more in the VANETs due to their properties. Hence, need to handle this issue to improve the performance of the VANETs. Also due to its dynamic nature collision occurs. Up till now, we have had immense complexity in developing the multi-constrained network with high quality of forwarding (QoF). To solve the difficulties especially to control the congestion this paper introduces an enhanced genetic algorithmbased lion optimization for QoF-based routing protocol (EGA-LOQRP) in the VANET network. Lion optimization routing protocol (LORP) is an optimization-based routing protocol that can able to control the network with a huge number of vehicles. An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. This will result in low packet loss, delay, and energy consumption of the network. The exhaustive simulation tests demonstrate that the EGA-LOQRP routing protocol improves performance effectively in the face of congestion and QoS assaults compared to the previous routing protocols like Ad hoc on-demand distance vector (AODV), ant colony optimization-AODV (ACO-AODV) and traffic aware segmentAODV (TAS-AODV)

An LSTM-based network slicing classification future predictive framework for optimized resource allocation in C-V2X

With the advent of 5G communication networks, many novel areas of research have emerged and the spectrum of communicating objects has been diversified. Network Function Virtualization (NFV), and Software Defined Networking (SDN), are the two broader areas that are tremendously being explored to optimize the network performance parameters. Cellular Vehicle-to-Everything (C-V2X) is one such example of where end-to-end communication is developed with the aid of intervening network slices. Adoption of these technologies enables a shift towards Ultra-Reliable Low-Latency Communication (URLLC) across various domains including autonomous vehicles that demand a hundred percent Quality of Service (QoS) and extremely low latency rates. Due to the limitation of resources to ensure such communication requirements, telecom operators are profoundly researching software solutions for network resource allocation optimally. The concept of Network Slicing (NS) emerged from such end-to-end network resource allocation where connecting devices are routed toward the suitable resources to meet their requirements. Nevertheless, the bias, in terms of finding the best slice, observed in the network slices renders a non-optimal distribution of resources. To cater to such issues, a Deep Learning approach has been developed in this paper. The incoming traffic has been allocated network slices based on data-driven decisions as well as predictive network analysis for the future. A Long Short Term Memory (LSTM) time series prediction approach has been adopted that renders optimal resource utilization, lower latency rates, and high reliability across the network. The model will further ensure packet prioritization and will retain resource margin for crucial ones

Assessment of shear strength characteristics of the unsaturated gypseous soil at various saturation degrees

AbstractThe purpose of this study is to determine whether or not unsaturated gypseous soil can function well as a substrate for the foundations of carrying loads. A comprehensive program of testing was carried out with the objective of validating the geotechnical parameters and behavior of the unsaturated gypseous soils. The testing program included specific gravity, moisture content, classification tests, Proctor’s compaction, relative density, and the triaxial test. Additionally, chemical analysis was performed on the samples as well. This approach was employed in a granular soil suction process to eliminate gaps of air in the soil until the soil grains held together. The sample was prepared by using a pump of vacuum with a suction process (approximately −20.0 kPa), and this method was used in the granular soil suction process. As a consequence of this, the suction prevents a specimen from collapsing when it is removed from the apparatus. The next step consisted of conducting a consolidated-undrained triaxial test on the soil. Experiments were performed on materials with a relative density of 35% and several degrees of saturation, such as normal saturation (6%), unsaturated (30, 60, 80%), and 100% saturated. It was shown that there is a reduction in the internal friction angle for the effective and total stresses is caused by an increase in the water content of the soil at any saturation degree. This occurs in both the unsaturated and saturated states of the soil. The angle of friction decreased by 80% of the natural value for both stresses, effective and total. As gypseous soil moisture increases up to the saturation degree of 60%, the soil cohesion for the total and effective stresses rises, where it increased by (220% and 125%) of the natural value for both the effective stress and the total stress, respectively, leading to an increase in the soil’s shear strength (ϕ and c). After then, there was a steady weakening of the force when it reached saturation degrees of 80% and 100%, where it decreased by (44% and 47%) of the maximum value at 60% saturation degree for both the effective stress and the total stress, respectively

Experimental investigation of dynamic soil properties for modeling energy-absorbing layers

Modeling the propagation of waves in geomechanics is an essential part of dynamic analysis. In geotechnics, the study of the interaction between the soil and the foundation is particularly interesting. In order to mimic low-speed operating types (less than 1,500 rpm), this study details the creation of a dependable and efficient approach for designing and fabricating the steel box container. When employed as a boundary, an absorbing layer drastically reduces the amount of wave reflection that occurs inside the limited region. The present effort is split into two halves. The first step is to calculate the damping layer’s damping constants, subgrade response modulus, damping ratio, shear modulus, vibration amplitude, and resonant frequency. The second section focuses on the dynamic study of the circular foundation by measuring the vibration amplitude, acceleration, velocity, and displacement caused by harmonic vibration machines. The findings demonstrate that simple material borders prevent the wave from dissipating as a consequence of reflection. Attenuation of waves is possible when the absorbing layer of energy represents semi-infinite soil. When absorbing just one layer, the vertical displacements at positions located at the box side boundary and its base decreased by 65, 63, and 67%, respectively. However, it dropped by 97, 96, and 98%, respectively, when two absorbent layers were used. On the basis of these promising results, the model results were compared with and without the absorbing layer. It would appear that the modeling of the absorbing layer, which is designed as two layers, has been satisfied for low speeds of harmonic vibration

Effect of saturation on dynamic characteristics of collapsible gypseous soil using cyclic triaxial testing

Studying the unsaturated gypseous soils behavior may lead to more understanding of the gypseous soil problems associated with unsaturation under the effect of the vertical vibrations. The purpose of this paper is to assess the suitability of unsaturated gypseous soil as a machine foundation soil. Moreover, such a purpose is considered beneficial in assessing appropriate methods for studying the characteristics and the behavior of unsaturated gypseous soils such as soil elastic modulus parameters, compressibility parameter, waves velocities, and amplitude axial strain for cyclic loading parameters under different with degree of saturation. The tests were performed for conditions 35% and 70% relative density of natural gypseous soil under 1.0 Hz and 2.0 Hz cyclic frequency at degrees of saturation (30%, 60%, and 80%), and fully saturated gypseous soil to investigate the gypseous soil behavior. It was found the values of the elastic modulus and wave velocities at degree of saturation 60% for different number of cycles and frequency increased with decrease of the strain and compressibility. Then, it began to decrease gradually at the saturation degree 80% and 100%, respectively. The best results based on strength consideration were obtained at 60% saturation, and the lowest strength was found when the soil was 100% saturated, for both load frequencies 1, and 2 Hz. The load frequency 1 Hz gave higher values than cyclic frequency 2 Hz of elastic modulus and wave velocities, while the number of cycles was less at the same time and for different degrees of saturation

Vehicular Networks Performance Evaluation Based on Downlink Scheduling Algorithms for High-Speed Long Term Evolution – Vehicle

Moving is the key to modern life. Most things are in moving such as vehicles and user mobiles, so the need for high-speed wireless networks to serve the high demand of the wireless application becomes essential for any wireless network design. The use of web browsing, online gaming, and on-time data exchange like video calls as an example means that users need a high data rate and fewer error communication links. To satisfy this, increasing the bandwidth available for each network will enhance the throughput of the communication, but the bandwidth available is a limited resource which means that thinking about techniques to be used to increase the throughput of the network is very important. One of the techniques used is the spectrum sharing between the available networks, but the problem here is when there is no available channel to connect with. This encourages researchers to think about using scheduling as a technique to serve the high capacity on the network. Studying scheduling techniques depends on the Quality-of-Service (QoS) of the network, so the throughput performance is the metric of this paper. In this paper, an improved Best-CQI scheduling algorithm is proposed to enhance the throughput of the network. The proposed algorithm was compared with three user scheduling algorithms to evaluate the throughput performance which are Round Robin (RR), Proportional Fair (PF), and Best-CQI algorithms. The study is performed under Line-of-Sight (LoS) link at carrier frequency 2.6 GHz to satisfy the Vehicular Long Term Evolution (LTE-V) with the high-speed scenario. The simulation results show that the proposed algorithm outperforms the throughput performance of the other algorithms

Vehicular Networks Performance Evaluation Based on Downlink Scheduling Algorithms for High-Speed Long Term Evolution – Vehicle

Moving is the key to modern life. Most things are in moving such as vehicles and user mobiles, so the need for high-speed wireless networks to serve the high demand of the wireless application becomes essential for any wireless network design. The use of web browsing, online gaming, and on-time data exchange like video calls as an example means that users need a high data rate and fewer error communication links. To satisfy this, increasing the bandwidth available for each network will enhance the throughput of the communication, but the bandwidth available is a limited resource which means that thinking about techniques to be used to increase the throughput of the network is very important. One of the techniques used is the spectrum sharing between the available networks, but the problem here is when there is no available channel to connect with. This encourages researchers to think about using scheduling as a technique to serve the high capacity on the network. Studying scheduling techniques depends on the Quality-of-Service (QoS) of the network, so the throughput performance is the metric of this paper. In this paper, an improved Best-CQI scheduling algorithm is proposed to enhance the throughput of the network. The proposed algorithm was compared with three user scheduling algorithms to evaluate the throughput performance which are Round Robin (RR), Proportional Fair (PF), and Best-CQI algorithms. The study is performed under Line-of-Sight (LoS) link at carrier frequency 2.6 GHz to satisfy the Vehicular Long Term Evolution (LTE-V) with the high-speed scenario. The simulation results show that the proposed algorithm outperforms the throughput performance of the other algorithms

A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network

Vehicular ad-hoc network (VANET) is dynamic and it works on various noteworthy applications in intelligent transportation systems (ITS). In general, routing overhead is more in the VANETs due to their properties. Hence, need to handle this issue to improve the performance of the VANETs. Also due to its dynamic nature collision occurs. Up till now, we have had immense complexity in developing the multi-constrained network with high quality of forwarding (QoF). To solve the difficulties especially to control the congestion this paper introduces an enhanced genetic algorithm-based lion optimization for QoF-based routing protocol (EGA-LOQRP) in the VANET network. Lion optimization routing protocol (LORP) is an optimization-based routing protocol that can able to control the network with a huge number of vehicles. An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. This will result in low packet loss, delay, and energy consumption of the network. The exhaustive simulation tests demonstrate that the EGA-LOQRP routing protocol improves performance effectively in the face of congestion and QoS assaults compared to the previous routing protocols like Ad hoc on-demand distance vector (AODV), ant colony optimization-AODV (ACO-AODV) and traffic aware segment-AODV (TAS-AODV)

An LSTM-Based Network Slicing Classification Future Predictive Framework for Optimized Resource Allocation in C-V2X

With the advent of 5G communication networks, many novel areas of research have emerged and the spectrum of communicating objects has been diversified. Network Function Virtualization (NFV), and Software Defined Networking (SDN), are the two broader areas that are tremendously being explored to optimize the network performance parameters. Cellular Vehicle-to-Everything (C-V2X) is one such example of where end-to-end communication is developed with the aid of intervening network slices. Adoption of these technologies enables a shift towards Ultra-Reliable Low-Latency Communication (URLLC) across various domains including autonomous vehicles that demand a hundred percent Quality of Service (QoS) and extremely low latency rates. Due to the limitation of resources to ensure such communication requirements, telecom operators are profoundly researching software solutions for network resource allocation optimally. The concept of Network Slicing (NS) emerged from such end-to-end network resource allocation where connecting devices are routed toward the suitable resources to meet their requirements. Nevertheless, the bias, in terms of finding the best slice, observed in the network slices renders a non-optimal distribution of resources. To cater to such issues, a Deep Learning approach has been developed in this paper. The incoming traffic has been allocated network slices based on data-driven decisions as well as predictive network analysis for the future. A Long Short Term Memory (LSTM) time series prediction approach has been adopted that renders optimal resource utilization, lower latency rates, and high reliability across the network. The model will further ensure packet prioritization and will retain resource margin for crucial ones