Forecasting mobile broadband traffic: Application of scenario analysis and Delphi method
- Authors
- Lee, Sungjoo; Cho, Chanwoo; Hong, Een-Kee; Yoon, Byungun
- Issue Date
- Feb-2016
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Mobile traffic; Forecast; Mobile devices; Delphi method; Scenario analysis
- Citation
- EXPERT SYSTEMS WITH APPLICATIONS, v.44, pp 126 - 137
- Pages
- 12
- Indexed
- SCIE
SCOPUS
- Journal Title
- EXPERT SYSTEMS WITH APPLICATIONS
- Volume
- 44
- Start Page
- 126
- End Page
- 137
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/24948
- DOI
- 10.1016/j.eswa.2015.09.030
- ISSN
- 0957-4174
1873-6793
- Abstract
- Since the mobile boom has started to cause a traffic jam in mobile broadband networks, forecasts on future traffic needs are urgent information for the provision of high-quality mobile broadband services. Thus, this research aims to forecast mobile broadband traffic, focusing on the Korean case. With the emergence of diverse classes of services, where the available devices for the services and their patterns of use are changing rapidly, most of the existing forecasting methods may not be applicable. Therefore, this study designed a new methodology for traffic forecasts, a device-based forecasting that consider mobile traffic from various devices for mobile services. The proposed approach performs the three-round Delphi process to complement the experts' opinions in forecasting mobile traffic for 10 years. In particular, scenario analysis was applied to reflect uncertainty of future dynamic situations, investigating optimistic, neutral and pessimistic scenarios. In addition, the forecasting performance of the suggested approach was validated by comparing it with that of traditional forecasting tools. The research findings indicate that mobile traffic will increase rapidly, and the patterns of use for mobile devices will change to some extent, which will provide strategic implications for both companies and government. (C) 2015 Elsevier Ltd. All rights reserved.
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Collections - College of Engineering > Department of Industrial and Systems Engineering > 1. Journal Articles

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