Clustering optimisation techniques in mobile networks

Rozaki, Eleni ORCID: https://orcid.org/0000-0002-1229-4013 2016. Clustering optimisation techniques in mobile networks. International Journal on Recent and Innovation Trends in Computing and Communication 4 (2) , pp. 22-29.

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Abstract

The use of mobile phones has exploded over the past years, abundantly through the introduction of smartphones and the rapidly expanding use of mobile data. This has resulted in a spiraling problem of ensuring quality of service for users of mobile networks. Hence, mobile carriers and service providers need to determine how to prioritise expansion decisions and optimise network faults to ensure customer satisfaction and optimal network performance. To assist in that decision-making process, this research employs data mining classification of different Key Performance Indicator datasets to develop a monitoring scheme for mobile networks as a means of identifying the causes of network malfunctions. Then, the data are clustered to observe the characteristics of the technical areas with the use of k-means clustering. The data output is further trained with decision tree classification algorithms. The end result was that this method of network optimisation allowed for significantly improved fault detection performance

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher:	Auricle Technologies
ISSN:	2321-8169
Date of First Compliant Deposit:	12 September 2016
Date of Acceptance:	9 February 2016
Last Modified:	24 Nov 2024 04:00
URI:	https://orca.cardiff.ac.uk/id/eprint/94447

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