Many engineering optimization problems may be rephrased in terms of equivalent binary problems, and these can be effectively tackled with evolutionary algorithms. Unfortunately, the fitness function computation may be extremely timeconsuming when dealing with antenna designs. Therefore, it is of paramount importance to speed up the convergency and to improve the performance of this kind of algorithm. The recent introduction and the increasing availability of quantum computing may be very effective in accelerating the design process, even though new approaches and algorithms are needed in order to exploit the specificity of these instruments. In this paper, a new version of a novel quantum crossover operator for binary Genetic Algorithm (bGA) has been introduced and compared with its previous version. They have been successfully tested on different mathematical benchmark functions and on a preliminary thinned array design.
In vehicular ad hoc network (VANETs), vehicles travel at high speed from one place to another that create certain issues like congestion, delay and high power consumption. Reducing the delay and power consumption is the primary task to achieve an effective performance among the vehicles. For that purpose in this article cluster head ($\mathbf{C H}$) selection and the data dissemination with multicast protocol (CHDMV) is concentrated. The subsections of this model are the vehicles clustering process, cluster maintenance and multicast protocol, with the presence of this processes the efficiency of the network is improved even if the vehicle travels at high speed with rapidly changing topology. The parameters which are measured to analyze the outcomes are packet delivery ratio, network throughput, average delay, energy efficiency and routing overhead. From the calculator result it is shown that the CHDMV achieves maximum performance in terms of the efficiency and delivery ratio.
Mainly to improve the efficiency to reduce the power utilization in earlier researches the clustering model is concentrated. It is the formation of clusters in the network which increases the connection degree fundamentally and with the leaders the network stability is also increased. With the presence of a huge number of devices even the earlier clustering models consists of certain drawbacks like data loss and delay. Overcome such drawbacks in this article a hybrid multiagent adaptive algorithm with whale optimization (HMACWO) is developed so that an optimal clustering is introduced which is able to increase the efficiency of the vehicular network. The core modules which are present in this article are an efficient clustering process and whale optimization with an improved clustering model. Experimental demonstration of this model is done in NS3 software and using certain parameters such as the cluster efficiency, CH lifetime, packet delivery ratio, network throughput, and average delay the performance of the network is analyzed. From the results, it is shown that the HMACWO attains a maximum cluster efficiency and $\mathbf{C H}$ lifetime when compared with the earlier methods.
In vehicular ad hoc networks (VANETs) due to high-speed vehicles several challenges occurred like vehicle integrity management, speed management and effective data collection with road traffic event management. To monitor the huge number of vehicles in an efficient way in a large-scale coverage area in recent times unmanned aerial vehicles (UAVs) are developed. This technology provides effective communication among the ground level and the air medium. To achieve highquality communication of the vehicles in this article dynamic mobility-based effective load balancing and QoS-aware network selection (DELQNU),UAVs are constructed. The core modules of this proposed DELQNU are UAV network model, mobility model and QoS model. Using these ideas monitoring a huge number of vehicles even at the densely populated and highspeed technology becomes possible and highly efficient. The implementation analysis are packet delivery ratio, throughput, delay, routing overhead and energy efficiency. From the final outcome it is proven that DELQNU attains maximum results in terms of delivery ratio and throughout when compared with the earlier baseline methodologies.
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.
