Routing Using Genetic Algorithm in a Wireless Sensor Network

Muruganantham, N.; El-Ocla, Hosam

doi:10.1007/s11277-019-07011-8

Cited by 19 publications

(11 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Muruganantham and El-Ocla deploy sensor nodes in the monitoring area and use radio imaging positioning techniques to track targets. The location of the target is rendered by the target motion and the received signal strength fluctuation [8].…”

Section: Literature Reviewmentioning

confidence: 99%

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

Zhang

2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

For smart city wireless sensing network construction needs, a network positioning algorithm based on genetic algorithm is proposed. The genetic algorithm uses a real number encoding, and the positioning model is constructed by analyzing the communication constraint between unknown nodes and a small amount of anchor nodes and constructs the positioning model, and the model is solved. The results show that when the ranging error is 50%, the positioning error is only increased by approximately 15% compared to the nonranging error. In a more harsh environment, if the ranging error is equal to the node wireless range, the ranging error is 100%, and the positioning error and the positioning ratio are not significantly changed. The scheme obtained by this algorithm can be well approarded with an ideal limit. In the case where the sensor node is given, the algorithm can obtain the maximum coverage.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

Zhang

2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…In many articles, researchers have used genetic algorithms to route WSNs 48–50 . In Anand and Pandey, 48 GA is used for clustering and then the data are sent to BS by PSO algorithm.…”

Section: Previous Studiesmentioning

confidence: 99%

A novel approach for clustering and routing in WSN using genetic algorithm and equilibrium optimizer

Heidari

Movaghar

Motameni

et al. 2022

Int J Communication

View full text Add to dashboard Cite

show abstract

“…Both protocols are much helpful for the calculation of the lifetime and energy consumption in the network. The routing algorithm is maximizing based on the quality [15] of WSN. Authors compared the network based on different algorithms such as AODV, Genetic algorithm (GA) based AODV, Dijkstra algorithm, and GA based Dijkstra algorithm.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware

Gupta¹,

Vaisla²,

Jain³

et al. 2022

Computer Systems Science and Engineering

View full text Add to dashboard Cite

Wireless sensor network (WSN) is a group of interconnected sensor nodes that work wirelessly to capture the information of surroundings. The routing of the network is a challenging task. The routing of WSN is classified as proactive, reactive, and hybrid. Adhoc on-demand distance vector (AODV) routing is an example of reactive routing based on the demand route formations among different nodes in the network. The research article emphasizes the design and simulation of the AODV routing hardware chip using very-high-speed integrated circuit hardware description language (VHDL) programming in Xilinx integrated synthesis environment (ISE) 14.7 software. The performance of the chip is studied based on the field-programmable gate array (FPGA) hardware parameters such as slices, lookup table (LUTs), input/output block (IOB), flipflops, and memory for the different configurations of the network (N = 10, 20 ….100). The delay and frequency are also estimated on the Virtex-5 FPGA. The performance of the WSN with AODV routing is also analyzed based on the packet delivery ratio, throughput, delay, and control overhead. The simulation test cases verified the 8-bit, 64-bit, and 128-bit data communication within the nodes.

show abstract

Routing Using Genetic Algorithm in a Wireless Sensor Network

Cited by 19 publications

References 18 publications

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

A novel approach for clustering and routing in WSN using genetic algorithm and equilibrium optimizer

Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware

Contact Info

Product

Resources

About