Link Loss Rate Inference Using Success Rate Cumulant Generating Function
Inference of the internal link state is an important and challenging issue for operating and evaluating networks. This paper presents a method to infer internal link loss characteristics based on end-to-end measurement. Our method uses cumulant generating function (CGF) inference algorithm. The main...
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| creator | Chengbo Huang Yongsheng Liang Yilong Xu Guisheng Yi |
| description | Inference of the internal link state is an important and challenging issue for operating and evaluating networks. This paper presents a method to infer internal link loss characteristics based on end-to-end measurement. Our method uses cumulant generating function (CGF) inference algorithm. The main contribution of our approach is that we use the success rate CGF instead of the loss rate CGF, because the loss rate CGF cannot be constructed directly. We construct the path success rate CGF first, then the link success rate CGF can be inferred, and the link success rate can be obtained. Employing the relationship between the link loss rate and the link success rate, we can get the link loss rate. The simulation results demonstrate that this method is efficient. |
| doi_str_mv | 10.1109/ICFN.2009.19 |
| format | Conference Proceeding |
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This paper presents a method to infer internal link loss characteristics based on end-to-end measurement. Our method uses cumulant generating function (CGF) inference algorithm. The main contribution of our approach is that we use the success rate CGF instead of the loss rate CGF, because the loss rate CGF cannot be constructed directly. We construct the path success rate CGF first, then the link success rate CGF can be inferred, and the link success rate can be obtained. Employing the relationship between the link loss rate and the link success rate, we can get the link loss rate. The simulation results demonstrate that this method is efficient.</description><identifier>ISBN: 0769535674</identifier><identifier>ISBN: 9780769535678</identifier><identifier>DOI: 10.1109/ICFN.2009.19</identifier><identifier>LCCN: 2008942479</identifier><language>eng</language><publisher>IEEE</publisher><subject>Communication networks ; cumulant generating function (CGF) ; Educational institutions ; Inference algorithms ; Information technology ; IP networks ; Loss measurement ; loss rate inference ; Maximum likelihood estimation ; network measurement ; Probes ; Routing ; Tomography</subject><ispartof>2009 International Conference on Future Networks, 2009, p.157-160</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5189919$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5189919$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chengbo Huang</creatorcontrib><creatorcontrib>Yongsheng Liang</creatorcontrib><creatorcontrib>Yilong Xu</creatorcontrib><creatorcontrib>Guisheng Yi</creatorcontrib><title>Link Loss Rate Inference Using Success Rate Cumulant Generating Function</title><title>2009 International Conference on Future Networks</title><addtitle>ICFN</addtitle><description>Inference of the internal link state is an important and challenging issue for operating and evaluating networks. This paper presents a method to infer internal link loss characteristics based on end-to-end measurement. Our method uses cumulant generating function (CGF) inference algorithm. The main contribution of our approach is that we use the success rate CGF instead of the loss rate CGF, because the loss rate CGF cannot be constructed directly. We construct the path success rate CGF first, then the link success rate CGF can be inferred, and the link success rate can be obtained. Employing the relationship between the link loss rate and the link success rate, we can get the link loss rate. The simulation results demonstrate that this method is efficient.</description><subject>Communication networks</subject><subject>cumulant generating function (CGF)</subject><subject>Educational institutions</subject><subject>Inference algorithms</subject><subject>Information technology</subject><subject>IP networks</subject><subject>Loss measurement</subject><subject>loss rate inference</subject><subject>Maximum likelihood estimation</subject><subject>network measurement</subject><subject>Probes</subject><subject>Routing</subject><subject>Tomography</subject><isbn>0769535674</isbn><isbn>9780769535678</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1jMFOwzAQRC2hStDSGzcu-YEEr-2Ns0cUkbZSBBLQc2XMGhlaF8XJgb-nCJjLSG-eRogrkBWApJtN291XSkqqgM7EXNqaUGNtzUzMT7gho4ylc7HM-V2eYlDZBi7Euo_po-iPORePbuRikwIPnDwX2xzTW_E0ec__Yzsdpr1LY7HixIMbf4RuSn6Mx3QpZsHtMy__eiG23d1zuy77h9Wmve3LCBbHEj2D9GBfTCBiR0yv3kDw1qNkg6hrx5awkQplCAQKSFl0ppbOac1aL8T1729k5t3nEA9u-NohNERA-htKyErE</recordid><startdate>200903</startdate><enddate>200903</enddate><creator>Chengbo Huang</creator><creator>Yongsheng Liang</creator><creator>Yilong Xu</creator><creator>Guisheng Yi</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200903</creationdate><title>Link Loss Rate Inference Using Success Rate Cumulant Generating Function</title><author>Chengbo Huang ; Yongsheng Liang ; Yilong Xu ; Guisheng Yi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-5ce10c17b4f99ea9e9dc41fc7c50e45536ae79580250ff91219275a460aa33e33</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Communication networks</topic><topic>cumulant generating function (CGF)</topic><topic>Educational institutions</topic><topic>Inference algorithms</topic><topic>Information technology</topic><topic>IP networks</topic><topic>Loss measurement</topic><topic>loss rate inference</topic><topic>Maximum likelihood estimation</topic><topic>network measurement</topic><topic>Probes</topic><topic>Routing</topic><topic>Tomography</topic><toplevel>online_resources</toplevel><creatorcontrib>Chengbo Huang</creatorcontrib><creatorcontrib>Yongsheng Liang</creatorcontrib><creatorcontrib>Yilong Xu</creatorcontrib><creatorcontrib>Guisheng Yi</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chengbo Huang</au><au>Yongsheng Liang</au><au>Yilong Xu</au><au>Guisheng Yi</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Link Loss Rate Inference Using Success Rate Cumulant Generating Function</atitle><btitle>2009 International Conference on Future Networks</btitle><stitle>ICFN</stitle><date>2009-03</date><risdate>2009</risdate><spage>157</spage><epage>160</epage><pages>157-160</pages><isbn>0769535674</isbn><isbn>9780769535678</isbn><abstract>Inference of the internal link state is an important and challenging issue for operating and evaluating networks. This paper presents a method to infer internal link loss characteristics based on end-to-end measurement. Our method uses cumulant generating function (CGF) inference algorithm. The main contribution of our approach is that we use the success rate CGF instead of the loss rate CGF, because the loss rate CGF cannot be constructed directly. We construct the path success rate CGF first, then the link success rate CGF can be inferred, and the link success rate can be obtained. Employing the relationship between the link loss rate and the link success rate, we can get the link loss rate. The simulation results demonstrate that this method is efficient.</abstract><pub>IEEE</pub><doi>10.1109/ICFN.2009.19</doi><tpages>4</tpages></addata></record> |
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| subjects | Communication networks cumulant generating function (CGF) Educational institutions Inference algorithms Information technology IP networks Loss measurement loss rate inference Maximum likelihood estimation network measurement Probes Routing Tomography |
| title | Link Loss Rate Inference Using Success Rate Cumulant Generating Function |
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