In VANETs various challenges are created because of the speed of the vehicles and its topological changes. To attend maximum reliability and scalability it becomes very essential to improve the communication standard of the vehicles mainly to attain maximum throughput and energy efficiency. For that purpose in this article a proactive collaborative scheme to attend maximum throughput and efficiency (PCVMTE) is developed. The core modules which are present in this article are effective system model, energy consumption model and location based routing protocol. Using these techniques the communication among the vehicles are standardized that greatly increase the throughput and efficiency of the devices. The parameters which are concentrated to analyze the network performance are network throughput, network delay, routing overhead, transmission accuracy and energy efficiency. From the obtained results it is shown that PCVMTE attains high quality communication when compared with the earlier works.
The Internet of things (IoT) is one of the most trending technologies which is used to monitor a huge number of devices worldwide. Device localization and optimal path selection is very essential in this technology to maintain the communication standard of the devices. To reduce the delay and power utilization of the devices and to attend high efficiency these parameters are needed to get concentrated. For that in this article distributed self-localization with an improved optimization model is developed using machine learning (DSLIOM) algorithms. The core modules of this article are efficient data processing analysis and improved optimization algorithm. The parameters which are calculated to analyses the performance are data success rate, network throughput, routing overhead, data loss rate and delay. From the result it is proven that this DSLIOM attends better performance than earlier works in terms of data success rate and the network throughput.
The major drawbacks of the vehicular network include reduction in the performance of the vehicles due to high speed and hence the reduction in energy utility. Sometimes, there is significant data loss during high-speed data transfer as a result of incorrect routing. To overcome such drawbacks in this article improved routing with multichannel clustering (IRMCV) is developed. The core concepts which are present in this model are effective data transmission between the automobiles and the cluster-based routing methodology. In the presence of this process, the routing issues are reduced and the energy utility is reduced with the presence of an effective clustering model and that enhances the cars’ overall performance when they participate in vehicular communication. The energy efficiency, energy consumption, vehicle longevity, cluster efficiency, and data delivery ratio are all measures of the cars’ performance. The ultimate outcome indicates that, in comparison to previous studies, the suggested IRMCV model outperformed the others in terms of cluster efficiency and vehicle longevity.
The feasibility in communication among the source to the destination is disturbed at the time of high-speed data transmission it increases the delay, overhead, and power utilization. Mainly to overcome such drawbacks in the network in this article overhead-aware resource allocation with clusterbased network construction is created. The core modules which are present in this article are vehicular network model creation and overhead-based resource allocation (ORACNC). With the presence of this process the efficiency and the reliability of the network is improved and that increases the lifespan of the vehicles. This network model is constructed in the software NS3 and the parameters which are taken into consideration for the result analysis are the packet delivery ratio, network throughput, average delay, energy efficiency, and routing overhead. The simulation result shows that the ORACNC increases the delivery ratio and it reduces the delay when compared with the previous works.
The vehicles are present in the network communicate with the adjacent vehicles and the roadside units through the routing model using the standard of IEEE 802.11p. To make the routing more flexible, the vehicles undergo certain challenges hence the mobility of the vehicles is so high and that result in the failure in communication link. Additionally due to irregular spectrum allocation the emergency data transmission is disturbed and that greatly reduces the communication quality. In order to overcome these drawbacks in this article effective spectrum allocation with priority function and multipoint relay (MPR)-based efficient routing model (ESPMRR) is developed in the vehicular communication. The core modules are network construction, channel model creation, priority-based data transmission and MPR-based routing. Through this process the earlier drawbacks are rectified and that leads to attend an effective communication among the vehicles. The ESPMRR is constructed the energy efficiency, routing overhead, packet delivery ratio, network throughput and average delay are measured. The simulation results prove that ESPMRR attends better results when compared with the previous works.
In this article, a hybrid traffic management in SDN-enabled multilayer Vehicular communication (HTMSMV) is developed. The core modules include SDN network construction, data generation model, mobility model and traffic management model. With the presence of these methods, communication constraints are received and it helps to manage the larger environment of the vehicles. The HTMSMV is implemented in the simulation software NS3 and the mobility of the vehicles are generated using the sumo model. Output parameters which are calculated are packet delivery ratio, network throughput, average delay, routing overhead and energy efficiency. From the results, it has been identified that the HTMSMV achieves a maximum efficiency than that of the previous methods.
In this article, trust-based relay node selection and efficient multi hop clustering model (TRSEMC) is developed. The core modules of this model are efficient network construction, multi hop clustering and vertical trust management. Even through this process the efficiency is greatly increased and that leads to expanding the life span of the devices. The proposed concept is constructed in the simulator called NS3 and he matrix which are taken to analyses the performance of the network are throughput, network delay, routing overhead, transmission accuracy and energy efficiency. This TRSEMC greatly fulfills the identified research gap and through an effective clustering mechanism the efficiency of the vehicles is increased than the SVCHT-UAV, FMMTC-UAV and GRTMI-UAV models.
In this article, an improved VANETs routing with particles swarm optimization to improve the quality-of-service parameters (IVRPSO) are developed. The core modules which are present in the article are RPL protocol-based routing and particles swarm optimization. Through these processes routing of the high-speed vehicles is standardized and the quality of communication is improvised. The implementation of this network is done in NS3 software and the parameters which are concentrated to analyze the performance are the data success rate, network throughput, routing overhead, data loss date and average delay. The simulation output states that from the execution of the varying number of vehicles the performance of the IVRPSO is better than the earlier works concerned with efficiency and data success rate.
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.
