Spatiotemporal Modeling in Wireless Communication Networks
This study aims to analyze the flow migration of individuals between Iraqi governorates using real anonymized data from Korek Telecom company in Iraq. The purpose of this analysis is to understand the connection structure and the attractiveness of these governorates through examining the flow migra...
| Main Authors: | , , |
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| Format: | Article |
| Language: | Arabic |
| Published: |
College of Science for Women, University of Baghdad
2023-06-01
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| Series: | Baghdad Science Journal |
| Subjects: | |
| Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6848 |
| Summary: | This study aims to analyze the flow migration of individuals between Iraqi governorates using real anonymized data from Korek Telecom company in Iraq. The purpose of this analysis is to understand the connection structure and the attractiveness of these governorates through examining the flow migration and population densities. Hence, they are classified based on the human migration at a particular period. The mobile phone data of type Call Detailed Records (CDRs) have been observed, which fall in a 6-month period during COVID-19 in the year 2020-2021. So, according to the CDRs nature, the well-known spatiotemporal algorithms: the radiation model and the gravity model were applied to analyze these data, and they are turned out to be complementary to each other. However, the results explore the flows of each governorate at two levels of abstraction: The Macroscopic and Mesoscopic. These results found that the spatiotemporal interaction models are complementary to the other, as the determined flows based on the radiation model have been used in the gravitational model. Furthermore, flows summary among all the governorates as well as for each of them has been obtained separately. Thus, based on the total number of flows, the highest attraction rate was between Nineveh and Dhi Qar governorates which reached , while the lowest attraction was between Wasit and Karbala governorates which reached . In addition, the extracted geographical maps showed each governorate ratio. Regarding the color of each governorate that degraded from light to dark, which indicated the low to high attraction respectively. In the future, it is possible to obtain more detailed data, and to use complex network algorithms for analyzing this data.
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| ISSN: | 2078-8665 2411-7986 |