Mobile Data Offloading: How Much Can WiFi Deliver?
This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 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 u...
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Veröffentlicht in: | IEEE/ACM transactions on networking 2013-04, Vol.21 (2), p.536-550 |
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description | This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 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. |
doi_str_mv | 10.1109/TNET.2012.2218122 |
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We recruited 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.</description><identifier>ISSN: 1063-6692</identifier><identifier>EISSN: 1558-2566</identifier><identifier>DOI: 10.1109/TNET.2012.2218122</identifier><identifier>CODEN: IEANEP</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Cities and towns ; Deadlines ; Delay ; Delayed transmission ; experimental networks ; Gain ; IEEE 802.11 Standards ; Mathematical analysis ; Mobile communication ; Mobile computing ; mobile data offloading ; mobility ; Networks ; Servers ; Simulation ; Statistics ; Studies ; Traffic engineering ; Traffic flow ; Wireless networks</subject><ispartof>IEEE/ACM transactions on networking, 2013-04, Vol.21 (2), p.536-550</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Apr 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c374t-d18d5803ba25974451c6f4839a4587c4fd8b5f160cf96c896b4c5c177863b59c3</citedby><cites>FETCH-LOGICAL-c374t-d18d5803ba25974451c6f4839a4587c4fd8b5f160cf96c896b4c5c177863b59c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6353239$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6353239$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Lee, Kyunghan</creatorcontrib><creatorcontrib>Lee, Joohyun</creatorcontrib><creatorcontrib>Yi, Yung</creatorcontrib><creatorcontrib>Rhee, Injong</creatorcontrib><creatorcontrib>Chong, Song</creatorcontrib><title>Mobile Data Offloading: How Much Can WiFi Deliver?</title><title>IEEE/ACM transactions on networking</title><addtitle>TNET</addtitle><description>This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 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.</description><subject>Cities and towns</subject><subject>Deadlines</subject><subject>Delay</subject><subject>Delayed transmission</subject><subject>experimental networks</subject><subject>Gain</subject><subject>IEEE 802.11 Standards</subject><subject>Mathematical analysis</subject><subject>Mobile communication</subject><subject>Mobile computing</subject><subject>mobile data offloading</subject><subject>mobility</subject><subject>Networks</subject><subject>Servers</subject><subject>Simulation</subject><subject>Statistics</subject><subject>Studies</subject><subject>Traffic engineering</subject><subject>Traffic flow</subject><subject>Wireless networks</subject><issn>1063-6692</issn><issn>1558-2566</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkEtLAzEUhYMoWKs_QNwMuHEzNTfvuBHpQ4XWbiouQyZNNGU6UycdxX_vlBYXru5ZfOdw-RC6BDwAwPp28TJeDAgGMiAEFBByhHrAucoJF-K4y1jQXAhNTtFZSiuMgWIieojM6iKWPhvZrc3mIZS1Xcbq_S57qr-zWes-sqGtsrc4idnIl_HLN_fn6CTYMvmLw-2j18l4MXzKp_PH5-HDNHdUsm2-BLXkCtPCEq4lYxycCExRbRlX0rGwVAUPILALWjilRcEcdyClErTg2tE-utnvbpr6s_Vpa9YxOV-WtvJ1mwwwkEphrGSHXv9DV3XbVN13BqjElGKFVUfBnnJNnVLjg9k0cW2bHwPY7CyanUWzs2gOFrvO1b4Tvfd_vKCcEqrpLyquaa8</recordid><startdate>20130401</startdate><enddate>20130401</enddate><creator>Lee, Kyunghan</creator><creator>Lee, Joohyun</creator><creator>Yi, Yung</creator><creator>Rhee, Injong</creator><creator>Chong, Song</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20130401</creationdate><title>Mobile Data Offloading: How Much Can WiFi Deliver?</title><author>Lee, Kyunghan ; Lee, Joohyun ; Yi, Yung ; Rhee, Injong ; Chong, Song</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c374t-d18d5803ba25974451c6f4839a4587c4fd8b5f160cf96c896b4c5c177863b59c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Cities and towns</topic><topic>Deadlines</topic><topic>Delay</topic><topic>Delayed transmission</topic><topic>experimental networks</topic><topic>Gain</topic><topic>IEEE 802.11 Standards</topic><topic>Mathematical analysis</topic><topic>Mobile communication</topic><topic>Mobile computing</topic><topic>mobile data offloading</topic><topic>mobility</topic><topic>Networks</topic><topic>Servers</topic><topic>Simulation</topic><topic>Statistics</topic><topic>Studies</topic><topic>Traffic engineering</topic><topic>Traffic flow</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Kyunghan</creatorcontrib><creatorcontrib>Lee, Joohyun</creatorcontrib><creatorcontrib>Yi, Yung</creatorcontrib><creatorcontrib>Rhee, Injong</creatorcontrib><creatorcontrib>Chong, Song</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE/ACM transactions on networking</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lee, Kyunghan</au><au>Lee, Joohyun</au><au>Yi, Yung</au><au>Rhee, Injong</au><au>Chong, Song</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mobile Data Offloading: How Much Can WiFi Deliver?</atitle><jtitle>IEEE/ACM transactions on networking</jtitle><stitle>TNET</stitle><date>2013-04-01</date><risdate>2013</risdate><volume>21</volume><issue>2</issue><spage>536</spage><epage>550</epage><pages>536-550</pages><issn>1063-6692</issn><eissn>1558-2566</eissn><coden>IEANEP</coden><abstract>This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 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.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TNET.2012.2218122</doi><tpages>15</tpages></addata></record> |
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subjects | Cities and towns Deadlines Delay Delayed transmission experimental networks Gain IEEE 802.11 Standards Mathematical analysis Mobile communication Mobile computing mobile data offloading mobility Networks Servers Simulation Statistics Studies Traffic engineering Traffic flow Wireless networks |
title | Mobile Data Offloading: How Much Can WiFi Deliver? |
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