Survivable Cloud Network Mapping for Disaster Recovery Support
Network virtualization is a key provision for improving the scalability and reliability of cloud computing services. In recent years, various mapping schemes have been developed to reserve VN resources over substrate networks. However, many cloud providers are very concerned about improving service...
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Veröffentlicht in: | IEEE transactions on computers 2015-08, Vol.64 (8), p.2353-2366 |
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creator | Feng Gu Shaban, Khaled Ghani, Nasir Khan, Samee Naeini, Mahshid R. Hayat, Majeed M. Assi, Chadi |
description | Network virtualization is a key provision for improving the scalability and reliability of cloud computing services. In recent years, various mapping schemes have been developed to reserve VN resources over substrate networks. However, many cloud providers are very concerned about improving service reliability under catastrophic disaster conditions yielding multiple system failures. To address this challenge, this work presents a novel failure region-disjoint VN mapping scheme to improve VN mapping survivability. The problem is first formulated as a mixed integer linear programming problem and then two heuristic solutions are proposed to compute a pair of failure region-disjoint VN mappings. The solution also takes into account mapping costs and load balancing concerns to help improve resource efficiencies. The schemes are then analyzed in detail for a variety of networks and their overall performances compared to some existing survivable VN mapping schemes. |
doi_str_mv | 10.1109/TC.2014.2360542 |
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(IEEE) Aug 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c322t-a615d021e6e50c8ecb2c1543ef954a0dbcc67e812642cfe507076d8d2ecff9c63</citedby><cites>FETCH-LOGICAL-c322t-a615d021e6e50c8ecb2c1543ef954a0dbcc67e812642cfe507076d8d2ecff9c63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6911955$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54737</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6911955$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Feng Gu</creatorcontrib><creatorcontrib>Shaban, Khaled</creatorcontrib><creatorcontrib>Ghani, Nasir</creatorcontrib><creatorcontrib>Khan, Samee</creatorcontrib><creatorcontrib>Naeini, Mahshid R.</creatorcontrib><creatorcontrib>Hayat, Majeed M.</creatorcontrib><creatorcontrib>Assi, Chadi</creatorcontrib><title>Survivable Cloud Network Mapping for Disaster Recovery Support</title><title>IEEE transactions on computers</title><addtitle>TC</addtitle><description>Network virtualization is a key provision for improving the scalability and reliability of cloud computing services. In recent years, various mapping schemes have been developed to reserve VN resources over substrate networks. However, many cloud providers are very concerned about improving service reliability under catastrophic disaster conditions yielding multiple system failures. To address this challenge, this work presents a novel failure region-disjoint VN mapping scheme to improve VN mapping survivability. The problem is first formulated as a mixed integer linear programming problem and then two heuristic solutions are proposed to compute a pair of failure region-disjoint VN mappings. The solution also takes into account mapping costs and load balancing concerns to help improve resource efficiencies. The schemes are then analyzed in detail for a variety of networks and their overall performances compared to some existing survivable VN mapping schemes.</description><subject>Bandwidth</subject><subject>Cloud computing</subject><subject>Cloud networking services</subject><subject>Computing time</subject><subject>Disasters</subject><subject>Educational institutions</subject><subject>Failure</subject><subject>Linear programming</subject><subject>Manganese</subject><subject>Mapping</subject><subject>Mathematical models</subject><subject>network virtualization</subject><subject>Networks</subject><subject>Optimization</subject><subject>Reserves</subject><subject>Resource management</subject><subject>Substrates</subject><subject>virtual network mapping</subject><subject>virtual network survivability</subject><subject>Virtualization</subject><issn>0018-9340</issn><issn>1557-9956</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpd0D1PwzAQBmALgUQpzAwskVhY0t45sVMvSCh8SnxItMyW61xQSloHOynqvydVKwamW573dPcydo4wQgQ1nuUjDpiOeCJBpPyADVCILFZKyEM2AMBJrJIUjtlJCAsAkBzUgF1PO7-u1mZeU5TXriuiV2p_nP-KXkzTVKvPqHQ-uq2CCS356J2sW5PfRNOuaZxvT9lRaepAZ_s5ZB_3d7P8MX5-e3jKb55jm3DexkaiKIAjSRJgJ2Tn3KJIEyqVSA0Uc2tlRhPkMuW27E0GmSwmBSdblsrKZMiudnsb7747Cq1eVsFSXZsVuS5ozPp3MpVkSU8v_9GF6_yqv06jVEIJBLlV452y3oXgqdSNr5bGbzSC3vapZ7ne9qn3ffaJi12iIqI_LRWiEiL5BZmOcAk</recordid><startdate>20150801</startdate><enddate>20150801</enddate><creator>Feng Gu</creator><creator>Shaban, Khaled</creator><creator>Ghani, Nasir</creator><creator>Khan, Samee</creator><creator>Naeini, Mahshid R.</creator><creator>Hayat, Majeed M.</creator><creator>Assi, Chadi</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Bandwidth Cloud computing Cloud networking services Computing time Disasters Educational institutions Failure Linear programming Manganese Mapping Mathematical models network virtualization Networks Optimization Reserves Resource management Substrates virtual network mapping virtual network survivability Virtualization |
title | Survivable Cloud Network Mapping for Disaster Recovery Support |
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