Abstract
Many algorithms use clustering to improve vehicular ad hoc network performance. The expected points of many of these approaches support multiple rounds of data to the roadside unit and constantly include clustering in every round of single-hop data transmission towards the road side unit; however, the clustering in every round maximizes the number of control messages and there could be the possibility of collision and decreases in network energy. Multi-hop transmission prolongs the cluster head node’s lifetime and boosts the network’s efficiency. Accordingly, this article proposes a new fuzzy-clustering-based routing algorithm to benefit from multi-hop transmission clustering simultaneously. This research has analyzed the limitation of clustering in each round, different algorithms were used to perform the clustering, and multi-hop routing was used to transfer the data of every cluster to the road side unit. The fuzzy logic was used to choose the head node of each cluster. Three parameters, (1) distance of each node, (2) remaining energy, and (3) number of neighbors of every node, were considered as fuzzy criteria. The results of this research were compared to various other algorithms in relation to parameters like dead node in every round, first node expire, half node expire, last node expire, and the network lifetime. The simulation results show that the proposed approach outperforms other methods. On the other hand, the vehicular ad hoc network (VANET) environment is vulnerable at the time of data transmission. The NS-2 software tool was used to simulate and evaluate the proposed fuzzy logic opportunistic routing’s performance results concerning end-to-end delay, packet delivery, and network throughput. We compare to the existing protocols, such as fuzzy Internet of Things (IoT), two fuzzy, and Fuzzy-Based Driver Monitoring System (FDMS). The performance comparison also emphasizes an effective utilization of the resources. Simulations on the highway environment show that the suggested protocol has an improved Quality of Service (QoS) efficiency compared to the above published methods in the literature.
Highlights
Introduction distributed under the terms andThe collection of network’s physical items embedded with software, actuators, sensors, and other various connectivity modules that allow them to send and receive data is considered the Internet of Things (IoT)
We propose a method to compute the complexity of head cluster selection base on the following parameters: (i) direction of vehicle, (ii) degree of connectivity, (iii) an entropy threshold computed from the mobility of devices in network, and (iv) level of distrust calculated based on the node’s reliability, vehicles are allocated verifiers who are neighbors with having minimum distrust value
The further advancement of this paper is as follows: (i) We propose a new mechanism for broadcasting data in vehicular ad hoc network (VANET) based on few expectations, and it is very easy to implement in distributed approach
Summary
The collection of network’s physical items (nodes) embedded with software, actuators, sensors, and other various connectivity modules that allow them to send and receive data is considered the Internet of Things (IoT). Using the fuzzy system while considering measures like the grade of each device and its space (distance) to the road side unit leads to decreasing transmission delay, increasing network lifetime and decreasing energy consumption during cluster head selection and cluster formation [7,8]. In order to prevent multiplier broadcasting of the same packet, each node contains a list of delivered data packets and their lifetimes This protocol leads to the multi-broadcast storm issue and the performance of the network gradually deteriorates, in scenarios with a high density. We propose a method to compute the complexity of head cluster selection base on the following parameters: (i) direction of vehicle, (ii) degree of connectivity, (iii) an entropy threshold computed from the mobility of devices (nodes) in network, and (iv) level of distrust calculated based on the node’s reliability, vehicles are allocated verifiers who are neighbors with having minimum distrust value. Bodies, with name evolution as Energy-Efficient Fuzzy Management (EEFM) with IoT in VANET of proposed method is measured much better in terms of capability and to minimize the quantity of involved vehicle nodes
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