LEADER 02398oam 2200409zu 450 001 9910873184603321 005 20241212220155.0 035 $a(CKB)2670000000140226 035 $a(SSID)ssj0000669734 035 $a(PQKBManifestationID)12229068 035 $a(PQKBTitleCode)TC0000669734 035 $a(PQKBWorkID)10715828 035 $a(PQKB)10542675 035 $a(NjHacI)992670000000140226 035 $a(EXLCZ)992670000000140226 100 $a20160829d2011 uy 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$a2011 Fourth IEEE International Conference on Utility and Cloud Computing (UCC) 210 31$a[Place of publication not identified]$cIEEE$d2011 215 $a1 online resource (xxvi, 478 pages) 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9781457721168 311 08$a1457721163 330 $aEnterprises use design best practices to build applications that leverage the linear scalability of the cloud. These include methods like data sharding, application sharding, denormalized data stores, thin binary images etc. The design practices itself involve reengineering an application to the cloud. Enterprises view reengineering activities as a business risk and a costly affair. As Service oriented applications increasingly get migrated to the cloud, it is imperative to utilize the power of the multicore based host hardware, and maintain or improve the performance of these applications in cloud. This paper presents a methodology, through a connection oriented framework, to smoothly migrate and tune a web service based enterprise application to the cloud. This methodology itself is a three step process - that helps measure, analyze and identify tuning parameters for the web services and configure the system - without initial reengineering effort. This approach, through a replicated enterprise application on a test bed, validates up to 30% performance gain for the application, while reducing the risk of the enterprise applications migration to the cloud. 606 $aCloud computing 615 0$aCloud computing. 676 $a004.6782 702 $aIEEE Staff 801 0$bPQKB 906 $aPROCEEDING 912 $a9910873184603321 996 $a2011 Fourth IEEE International Conference on Utility and Cloud Computing (UCC)$92503864 997 $aUNINA