Optimized Node Clustering based on Received Signal Strength with Particle Ordered-filter Routing Used in VANET

Abstract

VANET is a critical and demanding mission. Numerous methods exist, but none profits in a distributed fashion from physical layer parameters. This paper describes a method that enables individual nodes to estimate node density, independent of beacon messages, and other infrastructure-based information, of their surrounding network. In this paper, a discrete simulator of events was proposed to estimate the average number of simultaneously transmitting nodes, a functional channel model for the VANETs system, and a method of estimating node density. Proposed based on some equations to allow individual nodes to estimate their surrounding node density in real-time Optimized Node Cluster Algorithm with Network Density in which the composition of a cluster is triggered adjacent, these traffic signals is the same and has been predicated mostly on the position a vehicle might well take after crossing. Additional Ordered Tracking with Particle -Filter Routing in which receives simultaneous signal intensity versus node transmission and node density transmission. Conduct multiple location-related analyzes to test the plausibility of the neighboring single-hop nodes on mobility data. The system is designed to operate in the most complex situations where nodes have little knowledge of network topology and the results, therefore, indicate that the system is fairly robust and accurate.

A trust-based method for highest node degree clustering in multi-layer mobile networks

“…Therefore, the multilayer mobile network routing protocol is optimised in order to be able to better adapt to the problem of transmitting aggregated information. When the number of node neighbours in the network layer where the cluster head is located is higher, it can provide a better service to the other members of the cluster and has an advantage in the link of cluster head selection [5][6]. Based on the above description, the energy consumption threshold is improved and expressed as follows:…”

Received Signal Strength-Based Localization for Vehicle Distance Estimation in Vehicular Ad Hoc Networks (VANETs)

“…This is the actual sensible solution as the GPS receiver can be simply fixed in the vehicle which has been provided by this technology. But with the development of VANET networks in key areas and the increasing reliance on positioning systems, GPS along with further satellite positioning systems (such as Galileo and GLONASS) are beginning to encounter difficulties such as lack of availability and insufficient availability of critical applications [11]. Now, in order to use and correctly calculate your location, the GPS receiver must be able to access at minimum three satellite indications for 2D locating and at minimum four satellite signals to evaluate the 3D position.…”

Metaheuristics-based Clustering with Routing Technique for Lifetime Maximization in Vehicular Networks

“…The Vehicular Ad hoc Networks (VANETs) are regarded in the subsection of the conventional structure of the Mobile Adhoc Network system (MANETs) [1]. The important character of VANET indicates the telecommunication nodes mention the vehicles which were granted with critical 'on-board unit' apparatus, transportable in limited roads or lanes, and interacting with one another for swapping messages via the Vehicle to Vehicle (V2V) protocol of transmission, that describes the extent amongst the vehicles and standard roadside accessible points [2]. This extent explanation further inculcates the wireless network and mobile substructure, in those cases where V2V form of information transfer is done [3].…”

“…2 , the EMCMHR-LM methodology has obtained increased coverage of 28.74% whereas DACRS, CBCLR, AODV-CV, CBR, and DBR systems have obtained decreased coverage of 21.39%, 19.55%, 15.87%, 15.87%, and 8.52% correspondingly. Besides, with 75 vehicles per km 2 , the EMCMHR-LM algorithm has reached increased coverage of 93.43% whereas DACRS, CBCLR, AODV-CV, CBR, and DBR approaches have accomplished minimal coverage of 89.02%, 80.94%, 82.41%, 70.28%, and 60.72% correspondingly.…”