Implementation of Greedy Algorithm in Optimal Cellular Masts Hoisting Over Population Coverage

Tamaraebi Ambrose Enisuoh; Okardi Biobele

doi:10.52589/BJCNIT-O5PVTEGT

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Implementation of Greedy Algorithm in Optimal Cellular Masts Hoisting Over Population Coverage

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Publication Date: 2021-07-26

DOI: 10.52589/BJCNIT-O5PVTEGT

Volume/Issue: Volume 4, Issue 1 (2021)

Page No: 68 - 78

Journal: British Journal of Computer, Networking and Information Technology

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Abstract:

The need to meet the demands of subscribers of wireless services is imperative to Global System for Mobile (GSM) Communication companies. These demands, which revolve around the maintenance of good network coverage and improved Quality of Service (QoS), depend largely on the nature of cellular network masts. Greedy Algorithm Model was implemented on network masts for small size populated areas to effectively have optimal network coverage. Object Oriented Analysis and Design Methodology (OOADM) and Java programming language was used for its implementation. The analysis of the results shows that Greedy Algorithm performed optimizing cellular network masts hoisting optimally for small populated areas.

Keywords:Greedy AlgorithmPopulation coverageOptimalMast and Voronoi Diagram

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Authors retain copyright in their articles and have unrestricted rights to reuse, republish, archive, share, and distribute their work after publication.
All articles are published open access under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence, which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, including for commercial purposes, provided appropriate credit is given to the original author(s) and source.

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Copyrights

Authors retain copyright in their articles and have unrestricted rights to reuse, republish, archive, share, and distribute their work after publication.
All articles are published open access under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence, which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, including for commercial purposes, provided appropriate credit is given to the original author(s) and source.