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

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.

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A novel clustering technique to stop congestion occur vehicular ad-hoc networks using node density based on received signal strength

Peer-to-Peer Networking and Applications ◽

10.1007/s12083-020-00958-7 ◽

2020 ◽

Author(s):

R. Regin ◽

T. Menakadevi

Keyword(s):

Ad Hoc Networks ◽

Vehicular Ad Hoc Networks ◽

Ad Hoc ◽

Signal Strength ◽

Received Signal Strength ◽

Node Density ◽

Clustering Technique ◽

Hoc Networks

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Mobility data anonymization by obfuscating the cellular network topology graph

2013 IEEE International Conference on Communications (ICC) ◽

10.1109/icc.2013.6654824 ◽

2013 ◽

Author(s):

Eduardo Baena Martinez ◽

Michal Ficek ◽

Lukas Kencl

Keyword(s):

Network Topology ◽

Cellular Network ◽

Data Anonymization ◽

Mobility Data ◽

Topology Graph

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Received signal strength–based indoor localization using a robust interacting multiple model–extended Kalman filter algorithm

International Journal of Distributed Sensor Networks ◽

10.1177/1550147717722158 ◽

2017 ◽

Vol 13 (8) ◽

pp. 155014771772215 ◽

Cited By ~ 5

Author(s):

Juan Manuel Castro-Arvizu ◽

Jordi Vilà-Valls ◽

Ana Moragrega ◽

Pau Closas ◽

Juan A Fernandez-Rubio

Keyword(s):

Indoor Localization ◽

Channel Model ◽

Real Life ◽

Signal Strength ◽

Received Signal Strength ◽

Location Based Services ◽

Model Parameters ◽

Interacting Multiple Model ◽

Multiple Model ◽

Shadow Fading

Due to the vast increase in location-based services, currently there exists an actual need of robust and reliable indoor localization solutions. Received signal strength localization is widely used due to its simplicity and availability in most mobile devices. The received signal strength channel model is defined by the propagation losses and the shadow fading. In real-life applications, these parameters might vary over time because of changes in the environment. Thus, to obtain a reliable localization solution, they have to be sequentially estimated. In this article, the problem of tracking a mobile node by received signal strength measurements is addressed, simultaneously estimating the model parameters. Particularly, a two-slope path loss model is assumed for the received signal strength observations, which provides a more realistic representation of the propagation channel. The proposed methodology considers a parallel interacting multiple model–based architecture for distance estimation, which is coupled with the on-line estimation of the model parameters and the final position determination via Kalman filtering. Numerical simulation results in realistic scenarios are provided to support the theoretical discussion and to show the enhanced performance of the new robust indoor localization approach. Additionally, experimental results using real data are reported to validate the technique.

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Optimized Node Clustering in VANETs by Using Meta-Heuristic Algorithms

Electronics ◽

10.3390/electronics9030394 ◽

2020 ◽

Vol 9 (3) ◽

pp. 394 ◽

Cited By ~ 2

Author(s):

Waleed Ahsan ◽

Muhammad Fahad Khan ◽

Farhan Aadil ◽

Muazzam Maqsood ◽

Staish Ashraf ◽

...

Keyword(s):

Ad Hoc Network ◽

Clustering Algorithm ◽

Ad Hoc ◽

Heuristic Algorithms ◽

Dynamic Change ◽

Grey Wolf Optimizer ◽

Node Density ◽

Dragonfly Algorithm ◽

Node Clustering ◽

On The Road

In a vehicular ad-hoc network (VANET), the vehicles are the nodes, and these nodes communicate with each other. On the road, vehicles are continuously in motion, and it causes a dynamic change in the network topology. It is more challenging when there is a higher node density. These conditions create many difficulties for network scalability and optimal route-finding in VANETs. Clustering protocols are being used frequently to solve such type of problems. In this paper, we proposed the grasshoppers’ optimization-based node clustering algorithm for VANETs (GOA) for optimal cluster head selection. The proposed algorithm reduced network overhead in unpredictable node density scenarios. To do so, different experiments were performed for comparative analysis of GOA with other state-of-the-art techniques like dragonfly algorithm, grey wolf optimizer (GWO), and ant colony optimization (ACO). Plentiful parameters, such as the number of clusters, network area, node density, and transmission range, were used in various experiments. The outcome of these results indicated that GOA outperformed existing methodologies. Lastly, the application of GOA in the flying ad-hoc network (FANET) domain was also proposed for next-generation networks.

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Indoor positioning system based on received signal strength: RSS

PsycEXTRA Dataset ◽

10.1037/e518112013-018 ◽

2012 ◽

Author(s):

Phongchai Nilas ◽

Burin Baitoei

Keyword(s):

Signal Strength ◽

Indoor Positioning ◽

Received Signal Strength ◽

Positioning System ◽

Indoor Positioning System

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An Evaluation of a Plasma Fractionation System

Thrombosis and Haemostasis ◽

10.1055/s-0038-1654486 ◽

1960 ◽

Vol 4 (01) ◽

pp. 031-044

Author(s):

George Y. Shinowara ◽

E. Mary Ruth

Keyword(s):

Biological Activity ◽

Ionic Strength ◽

Plasma Proteins ◽

High Concentration ◽

Significant Evidence ◽

Native Proteins ◽

Mobility Data ◽

Fractionation Procedure ◽

The Individual ◽

Low Ionic Strength

SummaryFour primary fractions comprising at least 97 per cent of the plasma proteins have been critically appraised for evidence of denaturation arising from a low temperature—low ionic strength fractionation system. The results in addition to those referable to the recovery of mass and biological activity include the following: The high solubilities of these fractions at pH 7.3 and low ionic strengths; the compatibility of the electrophoretic and ultracentrifugal data of the individual fractions with those of the original plasma; and the recovery of hemoglobin, not hematin, in fraction III obtained from specimens contaminated with this pigment. However, the most significant evidence for minimum alterations of native proteins was that the S20, w and the electrophoretic mobility data on the physically recombined fractions were identical to those found on whole plasma.The fractionation procedure examined here quantitatively isolates fibrinogen, prothrombin and antithrombin in primary fractions. Results have been obtained demonstrating its significance in other biological systems. These include the following: The finding of 5 S20, w classes in the 4 primary fractions; the occurrence of more than 90 per cent of the plasma gamma globulins in fraction III; the 98 per cent pure albumin in fraction IV; and, finally, the high concentration of beta lipoproteins in fraction II.

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