Study Wi-Fi as a study sample inspired by wireless networks and consider it as an access point for networks

Authors

  • Israa Falih Muslm Department of Quality Assurance and Academic Performance, University of Babylon, Iraq

Keywords:

Network, Wireless, Wi-Fi networks

Abstract

Wireless network is one of the means of connecting to the Internet that allows the exchange of data without the need to use wires and connections. The research problem was to propose a method to find the optimal location for the access point in Wi-Fi networks inside buildings using a technology inspired by nature. Including low data transfer rate, signal depletion, and poor roaming coverage, which leads to increased costs by adding additional access points. By observing and analyzing the behavior of living organisms that are less intelligent than humans, we have obtained algorithms inspired by nature that have proven successful in solving many engineering problems.

When the building's structural design requires increasing the wireless network capacity by adding more access points close to each other, this is where the proposed method comes in, in order to choose the optimal location to reduce interference and the possibility of Interference between access points. Taking into account the environmental and climatic conditions around the access points, such as the number of people, humidity, and surrounding trees.

References

Li X, et al. A review of industrial wireless networks in the context of industry 4.0. Wireless Netw. 2017;23:23–41.

Cisco. Cisco Visual Networking Index: Forecast and Trends, 2017–2022 [Internet]. 2017 [cited 2020 Jan 10]. Available from: https://www.cisco.com/

Rouse M. Internet of Things (IoT), 2018.

Gubbi J, et al. Internet of Things (IoT): A vision, architectural elements, and future directions. Future Gener Comput Syst. 2013;29:1645–60.

Whitley D. A genetic algorithm tutorial. Stat Comput. 1994;4(2):65–85.

Eberhart R, Kennedy J. Particle swarm optimization. In: Proc IEEE Int Conf Neural Netw, 1995.

Zedadra O, et al. Swarm intelligence and IoT-based smart cities: A review. In: The Internet of Things for Smart Urban Ecosystems. Springer, 2019, p177–200.

Yang XS. Nature-inspired metaheuristic algorithms. Frome, UK: Luniver Press, 2010.

Abdulshahed AM, et al. The application of ANFIS prediction models for thermal error compensation on CNC machine tools. Appl Soft Comput. 2015;27:158–68.

Abdulshahed A, et al. A particle swarm optimisation-based Grey prediction model for thermal error compensation on CNC machine tools. In: Laser Metrology and Machine Performance XI, LAMDAMAP 2015; Huddersfield, 2015, p369–78.

Kaur M, et al. Binary cuckoo search metaheuristic-based supercomputing framework for human behavior analysis in smart home. J Supercomput, 2019, 1–24.

Yang N, Xiong M, et al. A three dimensional indoor positioning algorithm based on the optimization model. In: Proc 13th Int Conf Nat Comput, Fuzzy Syst Knowl Discov (ICNC-FSKD). IEEE, 2017.

Kouhbor S, Ugon J, et al. Optimal placement of access point in WLAN based on a new algorithm. In: Int Conf Mobile Business (ICMB’05). IEEE, 2005.

Vilović I, Burum N. Location optimization of WLAN access points based on a neural network model and evolutionary algorithms. Automatika. 2014;55(3):317–29.

Yigit T, Ersoy M. Testing and design of indoor WLAN using artificial intelligence techniques. Elektron Elektrotech. 2014;20(6):154–7.

Sadowski S, Spachos P. RSSI-based indoor localization with the Internet of Things. IEEE Access. 2018;6:30149–61.

Pahlavan K, Krishnamurthy P. Principles of wireless networks. Upper Saddle River, NJ: Prentice Hall PTR, 2001.

Iskander MF, Yun Z. Propagation prediction models for wireless communication systems. IEEE Trans Microw Theory Tech. 2002;50(3):662–73.

Iskander MF, Yun Z. Propagation prediction models for wireless communication systems. IEEE Trans Microw Theory Tech. 2002;50(3):662–73.

Downloads

Published

2025-04-10

How to Cite

Muslm, I. F. (2025). Study Wi-Fi as a study sample inspired by wireless networks and consider it as an access point for networks. Journal of Advance Multidisciplinary Research, 4(2), 13–19. Retrieved from https://www.synstojournals.com/multi/article/view/166

Issue

Section

Articles