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Lee, Kyunghan
Mobile Systems and Networking Lab. (MSN)
Research Interests
  • Low-latency network, cloud computing, 5G network, mobile machine learning

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Mobile Data Offloading: How Much Can WiFi Deliver?

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dc.contributor.author Lee, Kyunghan ko
dc.contributor.author Lee, Joohyun ko
dc.contributor.author Yi, Yung ko
dc.contributor.author Rhee, Injong ko
dc.contributor.author Chong, Song ko
dc.date.available 2014-04-10T01:57:35Z -
dc.date.created 2013-07-04 ko
dc.date.issued 2013-04 -
dc.identifier.citation IEEE-ACM TRANSACTIONS ON NETWORKING, v.21, no.2, pp.536 - 550 ko
dc.identifier.issn 1063-6692 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/3479 -
dc.identifier.uri http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84876288366 ko
dc.description.abstract 97 iPhone users from metropolitan areas and collected statistics on their WiFi connectivity during a two-and-a-half-week period in February 2010. Our trace-driven simulation using the acquired whole-day traces indicates that WiFi already offloads about 65% of the total mobile data traffic and saves 55% of battery power without using any delayed transmission. If data transfers can be delayed with some deadline until users enter a WiFi zone, substantial gains can be achieved only when the deadline is fairly larger than tens of minutes. With 100-s delays, the achievable gain is less than only 2%-3%, whereas with 1 h or longer deadlines, traffic and energy saving gains increase beyond 29% and 20%, respectively. These results are in contrast to the substantial gain (20%-33%) reported by the existing work even for 100-s delayed transmission using traces taken from transit buses or war-driving. In addition, a distribution model-based simulator and a theoretical framework that enable analytical studies of the average performance of offloading are proposed. These tools are useful for network providers to obtain a rough estimate on the average performance of offloading for a given WiFi deployment condition. ko
dc.description.statementofresponsibility close -
dc.language ENG ko
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC ko
dc.subject Analytical studies ko
dc.subject Metropolitan area ko
dc.subject Mobile data offloading ko
dc.subject Mobile data traffic ko
dc.subject Network provider ko
dc.subject Quantitative study ko
dc.subject Theoretical framework ko
dc.subject Trace driven simulation ko
dc.title Mobile Data Offloading: How Much Can WiFi Deliver? ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-84876288366 ko
dc.identifier.wosid 000317925300015 ko
dc.type.rims ART ko
dc.description.scopustc 9 *
dc.date.scptcdate 2014-07-12 *
dc.identifier.doi 10.1109/TNET.2012.2218122 ko
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