Rafiq, M. N., Farooq, H., Zoha, A. and Imran, A. (2018) Can Temperature be Used as a Predictor of Data Traffic? A Real Network Big Data Analysis. In: 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT), Zurich, Switzerland, 17-20 Dec 2018, pp. 167-173. ISBN 9781538655023 (doi: 10.1109/BDCAT.2018.00028)
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Abstract
The proliferation of mobile devices and big data has made it possible to understand the human movements and forecasts of precise and intelligent short and long-term data consumption of services like call, sms, or internet data which has interesting and promising applications in modern cellular networks. Human nature and moods are known to be synonymous with the physical attributes of mother nature such as temperature. The change in those physical features affects the human routines and activities such as cellular data consumptions. The future of telecommunication lies in the exploration of heap of information and data available to companies and inferring the valuable results through extensive analysis. In this paper, we analyze three main traits of cellular activity: sms, call, and internet. This paper investigates whether the relationship between the temperature and the cellular data consumption exits or not. This work introduces a novel approach to identify the strength of relationship between the temperature and cellular activity (sms, call, internet) and discuss the methods to quantify the relationship using correlation method. The real network CDR big data set - Milano Grid data set is used to analyze the behavior of the cellular activity with respect to temperature.
| Item Type: | Conference Proceedings |
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| Additional Information: | This material is based upon work supported by the National Science Foundation under Grant Numbers 1619346, 1559483, 1730650 and 1718956. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Zoha, Dr Ahmed |
| Authors: | Rafiq, M. N., Farooq, H., Zoha, A., and Imran, A. |
| College/School: | College of Science and Engineering > School of Engineering > Systems Power and Energy |
| ISBN: | 9781538655023 |
| Published Online: | 10 January 2019 |
| Copyright Holders: | Copyright © 2018 IEEE |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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