Position-Time Pattern Based Method for Analyzing Users’ Mobility

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00368061" target="_blank" >RIV/68407700:21230/23:00368061 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/VTC2023-Spring57618.2023.10201211" target="_blank" >http://dx.doi.org/10.1109/VTC2023-Spring57618.2023.10201211</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/VTC2023-Spring57618.2023.10201211" target="_blank" >10.1109/VTC2023-Spring57618.2023.10201211</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Position-Time Pattern Based Method for Analyzing Users’ Mobility

Popis výsledku v původním jazyce

Mobile network users’ movements analysis has increasingly importance with the mobile networks evolution. Time-spatial information about current and previous locations can contribute in optimizing mobile network performance. Extracting features from this information is the most common method in analyzing users’ mobility. In this paper, a new position-time pattern based method is proposed to analyze the mobility by translating time-spatial records of each user to target-oriented image. Dataset provided from an ISP in Shanghai city for one month is used in our work. The proposed method is deducing user’ mobility behavior by visualizing serving base stations positions vs time according to unified rules for all users. Mobility pattern ambiguity resulting from neighboring base stations is processed. Moreover, K-Nearest Neighbors based method is suggested to predict base stations neighborhood. Results shows that visualizing time-spatial dataset, with proper processing of neighboring base stations issue, provide better understanding of users’ mobility data analysis.

Název v anglickém jazyce

Position-Time Pattern Based Method for Analyzing Users’ Mobility

Popis výsledku anglicky

Mobile network users’ movements analysis has increasingly importance with the mobile networks evolution. Time-spatial information about current and previous locations can contribute in optimizing mobile network performance. Extracting features from this information is the most common method in analyzing users’ mobility. In this paper, a new position-time pattern based method is proposed to analyze the mobility by translating time-spatial records of each user to target-oriented image. Dataset provided from an ISP in Shanghai city for one month is used in our work. The proposed method is deducing user’ mobility behavior by visualizing serving base stations positions vs time according to unified rules for all users. Mobility pattern ambiguity resulting from neighboring base stations is processed. Moreover, K-Nearest Neighbors based method is suggested to predict base stations neighborhood. Results shows that visualizing time-spatial dataset, with proper processing of neighboring base stations issue, provide better understanding of users’ mobility data analysis.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2023 IEEE 97th Vehicular Technology Conference

ISBN

979-8-3503-1114-3

ISSN

2577-2465

e-ISSN

2577-2465

Počet stran výsledku

5

Strana od-do

1-5

Název nakladatele

IEEE Industrial Electronic Society

Místo vydání

Vienna

Místo konání akce

Florence

Datum konání akce

20. 6. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001054797203009