A vehicular ad-hoc IoT network (VA-IoT) plays a key role in exchanging the constrained networked vehicle information through IPv6 enabled sensor nodes. It is noteworthy to understand that vehicular IoT is interconnection of vehicular ad-hoc networks with the support of constrained IoT devices. Routing protocols in VAN-IoT is designed to route the vehicular traffic in the distributed environments. In addition, VAN-IoT is designed to enhance the road safety by reducing the number of road accidents through reliable data transmission. Routing in VAN-IoT has a unique dynamic topology, frequent spectrum, and node handover with restricted versatility. Hence, it is very crucial to design the hybrid reactive routing protocols to ensure the network throughput and data reliability of the VAN-IoT networks. This paper aims to propose an AI based Reactive Routing protocol to enhance the performance of the network throughput, minimize the end-to-end delay with respect to node mobility, spectrum mobility, link traffic load and end-to-end network traffic load while transmitting the vehicular images. In addition, the performance of the proposed routing protocol in terms of image transmission time is being compared with the existing initiative-taking and reactive based routing protocols in Vehicular Adhoc IoT (VA-IoT) Networks.
The present study aimed to optimize the redundancy allocation problem based on sustainable maintenance. For this purpose, the goal is to design a complex system based on redundancy allocation by considering the weight and reliability criteria of the system and the maintenance and repair costs through the sustainability approach. In this regard, a mathematical model has been developed. This model minimizes system reliability and system weight simultaneously. There are also budget constraints on repair costs, environmental costs, purchase of spare parts, and energy risk costs. In order to optimize this model, a hybrid algorithm based on Whale Optimization Algorithm (WOA), Genetic Algorithm (GA), and Simulated Annealing (SA) is proposed. Accordingly, 81 test problems are provided and optimized by the proposed algorithm. The obtained numerical results indicate that, with increasing failure time of each component, the system’s reliability increases and the weight of the whole system increases. Moreover, changing the Weibull distribution parameters directly affects the total amount of system reliability, but does not have a definite and accurate effect on the total weight of the system. Moreover, increasing the budget for maintenance leads to finding solutions with more reliability and less weight.
A vehicular ad-hoc IoT network (VA-IoT) plays a key role in exchanging the constrained networked vehicle information through IPv6 enabled sensor nodes. It is noteworthy to understand that vehicular IoT is interconnection of vehicular ad-hoc networks with the support of constrained IoT devices. Routing protocols in VAN-IoT is designed to route the vehicular tra c in the distributed environments. In addition, VAN-IoT is designed to enhance the road safety by reducing the number of road accidents through reliable data transmission. Routing in VAN-IoT has a unique dynamic topology, frequent spectrum, and node handover with restricted versatility. Hence, it is very crucial to design the hybrid reactive routing protocols to ensure the network throughput and data reliability of the VAN-IoT networks. This paper aims to propose an AI based Reactive Routing protocol to enhance the performance of the network throughput, minimize the end-to-end delay with respect to node mobility, spectrum mobility, link tra c load and endto-end network tra c load while transmitting the vehicular images. In addition, the performance of the proposed routing protocol in terms of image transmission time is being compared with the existing initiative-taking and reactive based routing protocols in Vehicular Adhoc IoT (VA-IoT) Networks.communicate with other neighbors that are within the range of node signal transmissions. In other words, a multi-hop communication is needed when the source and destination is being connected to different networks. Due to this, the vehicular nodes(routers) within the VA-IoT network must cooperate with each other to forward the application data from the source to the destination [7]. To transmit the information from the source to the destination, the network must be connected. In other words, nodes within the network must be capable of nding other nodes within the communication range to forward the application data from source to destination that in different geographical locations. The physical communication through radio signals is transmitted through Dedicated Short-Range Communication (DSRC) operating at 5.9GHz through IEEE 802.15.4 standard. The Wireless Access in Vehicular Environments (WAVE) is built with the speci cations based on American DSRC that divides the spectrum into seven 10 MHz channels. Since the pattern is being proposed for vehicular adhoc communication, the node velocity, signal transmission radius and data transmission rate is being predetermined within the communication medium for application data transmission [8][9][10][11].Based on the WAVE characteristics, the maximum node velocity will be up to 190 Km/hr., transmission radius is up to 1 km in noise free environment and transmission speed could be up to 27 Mbps in VANETs. The network layer in the TCP/IP protocol stack is responsible for de ning the rules of packet routing in the public switched networks. The packet routing process is de ned as the service responsible
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