Protecting Location Privacy for Task Allocation in Ad Hoc Mobile Cloud Computing
Mobile cloud computing (MCC) is an emerging cloud-computing paradigm that integrates cloud computing and mobile computing to enable many useful mobile applications. However, the large-scale deployment of MCC is hindered by the concerns on possible privacy leakage. In this paper, we investigate the p...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on emerging topics in computing 2018-01, Vol.6 (1), p.110-121 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 121 |
|---|---|
| container_issue | 1 |
| container_start_page | 110 |
| container_title | IEEE transactions on emerging topics in computing |
| container_volume | 6 |
| creator | Gong, Yanmin Zhang, Chi Fang, Yuguang Sun, Jinyuan |
| description | Mobile cloud computing (MCC) is an emerging cloud-computing paradigm that integrates cloud computing and mobile computing to enable many useful mobile applications. However, the large-scale deployment of MCC is hindered by the concerns on possible privacy leakage. In this paper, we investigate the privacy issues in the ad hoc MCC, and propose a framework that can protect the location privacy when allocating tasks to mobile devices. Our mechanism is based on differential privacy and geocast, and allows mobile devices to contribute their resources to the ad hoc mobile cloud without leaking their location information. We develop analytical models and task allocation strategies that balance privacy, utility, and system overhead in an ad hoc mobile cloud. We also conduct extensive experiments based on real-world data sets, and the results show that our framework can protect location privacy for mobile devices while providing effective services with low system overhead. |
| doi_str_mv | 10.1109/TETC.2015.2490021 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TETC_2015_2490021</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>7296638</ieee_id><sourcerecordid>2299129386</sourcerecordid><originalsourceid>FETCH-LOGICAL-c406t-52aca33191e003302fb8169642be905e7292370ec6c0f7978bcda79072de85113</originalsourceid><addsrcrecordid>eNpNkNFLwzAQxoMoOHR_gPgS8LnzLlmT5nEUdcLEPcznkKapdHbNTFph_72tm-K93MF9393Hj5AbhBkiqPvNwyafMcB0xuYKgOEZmTAUWSJkCuf_5ksyjXELQ2UolJATsl4H3znb1e07XXlrutq3dB3qL2MPtPKBbkz8oIum-d3VLV2UdOktffFF3TiaN74vae53-368ck0uKtNENz31K_L2OMRbJqvXp-d8sUrsHESXpMxYwzkqdACcA6uKn0hzVjgFqZNMMS7BWWGhkkpmhS2NVCBZ6bIUkV-Ru-PdffCfvYud3vo-tMNLzZhSyBTPxKDCo8oGH2Nwld6HemfCQSPokZ0e2emRnT6xGzy3R0_tnPvTD4GE4Bn_BqTRaEs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2299129386</pqid></control><display><type>article</type><title>Protecting Location Privacy for Task Allocation in Ad Hoc Mobile Cloud Computing</title><source>IEEE Electronic Library (IEL)</source><creator>Gong, Yanmin ; Zhang, Chi ; Fang, Yuguang ; Sun, Jinyuan</creator><creatorcontrib>Gong, Yanmin ; Zhang, Chi ; Fang, Yuguang ; Sun, Jinyuan</creatorcontrib><description>Mobile cloud computing (MCC) is an emerging cloud-computing paradigm that integrates cloud computing and mobile computing to enable many useful mobile applications. However, the large-scale deployment of MCC is hindered by the concerns on possible privacy leakage. In this paper, we investigate the privacy issues in the ad hoc MCC, and propose a framework that can protect the location privacy when allocating tasks to mobile devices. Our mechanism is based on differential privacy and geocast, and allows mobile devices to contribute their resources to the ad hoc mobile cloud without leaking their location information. We develop analytical models and task allocation strategies that balance privacy, utility, and system overhead in an ad hoc mobile cloud. We also conduct extensive experiments based on real-world data sets, and the results show that our framework can protect location privacy for mobile devices while providing effective services with low system overhead.</description><identifier>ISSN: 2168-6750</identifier><identifier>EISSN: 2168-6750</identifier><identifier>DOI: 10.1109/TETC.2015.2490021</identifier><identifier>CODEN: ITETBT</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Applications programs ; Cloud computing ; Electronic devices ; location privacy ; Mobile cloud computing ; Mobile communication ; Mobile computing ; Mobile handsets ; Noise measurement ; Privacy ; reputation ; Resource management ; Servers ; task allocation</subject><ispartof>IEEE transactions on emerging topics in computing, 2018-01, Vol.6 (1), p.110-121</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c406t-52aca33191e003302fb8169642be905e7292370ec6c0f7978bcda79072de85113</citedby><cites>FETCH-LOGICAL-c406t-52aca33191e003302fb8169642be905e7292370ec6c0f7978bcda79072de85113</cites><orcidid>0000-0002-4543-6663</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7296638$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27610,27901,27902,54733,54908</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7296638$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Gong, Yanmin</creatorcontrib><creatorcontrib>Zhang, Chi</creatorcontrib><creatorcontrib>Fang, Yuguang</creatorcontrib><creatorcontrib>Sun, Jinyuan</creatorcontrib><title>Protecting Location Privacy for Task Allocation in Ad Hoc Mobile Cloud Computing</title><title>IEEE transactions on emerging topics in computing</title><addtitle>TETC</addtitle><description>Mobile cloud computing (MCC) is an emerging cloud-computing paradigm that integrates cloud computing and mobile computing to enable many useful mobile applications. However, the large-scale deployment of MCC is hindered by the concerns on possible privacy leakage. In this paper, we investigate the privacy issues in the ad hoc MCC, and propose a framework that can protect the location privacy when allocating tasks to mobile devices. Our mechanism is based on differential privacy and geocast, and allows mobile devices to contribute their resources to the ad hoc mobile cloud without leaking their location information. We develop analytical models and task allocation strategies that balance privacy, utility, and system overhead in an ad hoc mobile cloud. We also conduct extensive experiments based on real-world data sets, and the results show that our framework can protect location privacy for mobile devices while providing effective services with low system overhead.</description><subject>Applications programs</subject><subject>Cloud computing</subject><subject>Electronic devices</subject><subject>location privacy</subject><subject>Mobile cloud computing</subject><subject>Mobile communication</subject><subject>Mobile computing</subject><subject>Mobile handsets</subject><subject>Noise measurement</subject><subject>Privacy</subject><subject>reputation</subject><subject>Resource management</subject><subject>Servers</subject><subject>task allocation</subject><issn>2168-6750</issn><issn>2168-6750</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkNFLwzAQxoMoOHR_gPgS8LnzLlmT5nEUdcLEPcznkKapdHbNTFph_72tm-K93MF9393Hj5AbhBkiqPvNwyafMcB0xuYKgOEZmTAUWSJkCuf_5ksyjXELQ2UolJATsl4H3znb1e07XXlrutq3dB3qL2MPtPKBbkz8oIum-d3VLV2UdOktffFF3TiaN74vae53-368ck0uKtNENz31K_L2OMRbJqvXp-d8sUrsHESXpMxYwzkqdACcA6uKn0hzVjgFqZNMMS7BWWGhkkpmhS2NVCBZ6bIUkV-Ru-PdffCfvYud3vo-tMNLzZhSyBTPxKDCo8oGH2Nwld6HemfCQSPokZ0e2emRnT6xGzy3R0_tnPvTD4GE4Bn_BqTRaEs</recordid><startdate>20180101</startdate><enddate>20180101</enddate><creator>Gong, Yanmin</creator><creator>Zhang, Chi</creator><creator>Fang, Yuguang</creator><creator>Sun, Jinyuan</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>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-4543-6663</orcidid></search><sort><creationdate>20180101</creationdate><title>Protecting Location Privacy for Task Allocation in Ad Hoc Mobile Cloud Computing</title><author>Gong, Yanmin ; Zhang, Chi ; Fang, Yuguang ; Sun, Jinyuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c406t-52aca33191e003302fb8169642be905e7292370ec6c0f7978bcda79072de85113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Applications programs</topic><topic>Cloud computing</topic><topic>Electronic devices</topic><topic>location privacy</topic><topic>Mobile cloud computing</topic><topic>Mobile communication</topic><topic>Mobile computing</topic><topic>Mobile handsets</topic><topic>Noise measurement</topic><topic>Privacy</topic><topic>reputation</topic><topic>Resource management</topic><topic>Servers</topic><topic>task allocation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gong, Yanmin</creatorcontrib><creatorcontrib>Zhang, Chi</creatorcontrib><creatorcontrib>Fang, Yuguang</creatorcontrib><creatorcontrib>Sun, Jinyuan</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>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><jtitle>IEEE transactions on emerging topics in computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gong, Yanmin</au><au>Zhang, Chi</au><au>Fang, Yuguang</au><au>Sun, Jinyuan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Protecting Location Privacy for Task Allocation in Ad Hoc Mobile Cloud Computing</atitle><jtitle>IEEE transactions on emerging topics in computing</jtitle><stitle>TETC</stitle><date>2018-01-01</date><risdate>2018</risdate><volume>6</volume><issue>1</issue><spage>110</spage><epage>121</epage><pages>110-121</pages><issn>2168-6750</issn><eissn>2168-6750</eissn><coden>ITETBT</coden><abstract>Mobile cloud computing (MCC) is an emerging cloud-computing paradigm that integrates cloud computing and mobile computing to enable many useful mobile applications. However, the large-scale deployment of MCC is hindered by the concerns on possible privacy leakage. In this paper, we investigate the privacy issues in the ad hoc MCC, and propose a framework that can protect the location privacy when allocating tasks to mobile devices. Our mechanism is based on differential privacy and geocast, and allows mobile devices to contribute their resources to the ad hoc mobile cloud without leaking their location information. We develop analytical models and task allocation strategies that balance privacy, utility, and system overhead in an ad hoc mobile cloud. We also conduct extensive experiments based on real-world data sets, and the results show that our framework can protect location privacy for mobile devices while providing effective services with low system overhead.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TETC.2015.2490021</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-4543-6663</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2168-6750 |
| ispartof | IEEE transactions on emerging topics in computing, 2018-01, Vol.6 (1), p.110-121 |
| issn | 2168-6750 2168-6750 |
| language | eng |
| recordid | cdi_crossref_primary_10_1109_TETC_2015_2490021 |
| source | IEEE Electronic Library (IEL) |
| subjects | Applications programs Cloud computing Electronic devices location privacy Mobile cloud computing Mobile communication Mobile computing Mobile handsets Noise measurement Privacy reputation Resource management Servers task allocation |
| title | Protecting Location Privacy for Task Allocation in Ad Hoc Mobile Cloud Computing |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T11%3A17%3A02IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Protecting%20Location%20Privacy%20for%20Task%20Allocation%20in%20Ad%20Hoc%20Mobile%20Cloud%20Computing&rft.jtitle=IEEE%20transactions%20on%20emerging%20topics%20in%20computing&rft.au=Gong,%20Yanmin&rft.date=2018-01-01&rft.volume=6&rft.issue=1&rft.spage=110&rft.epage=121&rft.pages=110-121&rft.issn=2168-6750&rft.eissn=2168-6750&rft.coden=ITETBT&rft_id=info:doi/10.1109/TETC.2015.2490021&rft_dat=%3Cproquest_RIE%3E2299129386%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2299129386&rft_id=info:pmid/&rft_ieee_id=7296638&rfr_iscdi=true |