Integration of firefly optimization and Pearson service correlation for efficient cloud resource utilization
Summary Cloud Computing (CC) environment presents a simplified, centralized platform or resources to usage while necessitated at minimum cost. In CC, the main processes in is the allocation of resources of web applications. However, with the increasing demands of Cloud User (CU), an efficient resour...
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Veröffentlicht in: | International journal of communication systems 2018-10, Vol.31 (15), p.n/a |
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Cloud Computing (CC) environment presents a simplified, centralized platform or resources to usage while necessitated at minimum cost. In CC, the main processes in is the allocation of resources of web applications. However, with the increasing demands of Cloud User (CU), an efficient resource allocation technique for web applications is required. According to the request made by the user and response obtained, the cost of resources has also to be optimized. To overcome such limitations, Pearson service correlation‐based firefly resource cost optimization (PSC‐FRCO) technique is designed. Pearson service correlation‐based firefly resource cost optimization technique not only improves the performance of cost aware resource allocation but also achieves higher efficiency while rendering services in cloud computing environment for web applications. Pearson service correlation‐based firefly resource cost optimization technique initially uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner. This helps in improving the Response Time (RT) of cloud service provisioning. Next, firefly resource cost optimization algorithm is applied to identify and allocate the cost‐optimized cloud resources to users to afford required service from the cloud server. Thus, PSC‐FRCO technique improves the Resource Utilization Efficiency (RUE) of web applications with minimal computational cost. This technique conducts experimental works on parameters such as RT, Bandwidth Utilization Rate (BUR) computational cost, Energy Consumption (EC), and RUE. Experimental analysis reveals that PSC‐FRCO technique enhances enhances RUE and lessens RT as compared to state‐of‐the‐art works.
To overcome limitations of efficient resource allocation technique for web application, Pearson service correlation‐based firefly resource cost optimization technique is designed. Pearson service correlation‐based firefly resource cost optimization achieves higher efficiency while rendering services in cloud computing which uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner. |
doi_str_mv | 10.1002/dac.3771 |
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Cloud Computing (CC) environment presents a simplified, centralized platform or resources to usage while necessitated at minimum cost. In CC, the main processes in is the allocation of resources of web applications. However, with the increasing demands of Cloud User (CU), an efficient resource allocation technique for web applications is required. According to the request made by the user and response obtained, the cost of resources has also to be optimized. To overcome such limitations, Pearson service correlation‐based firefly resource cost optimization (PSC‐FRCO) technique is designed. Pearson service correlation‐based firefly resource cost optimization technique not only improves the performance of cost aware resource allocation but also achieves higher efficiency while rendering services in cloud computing environment for web applications. Pearson service correlation‐based firefly resource cost optimization technique initially uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner. This helps in improving the Response Time (RT) of cloud service provisioning. Next, firefly resource cost optimization algorithm is applied to identify and allocate the cost‐optimized cloud resources to users to afford required service from the cloud server. Thus, PSC‐FRCO technique improves the Resource Utilization Efficiency (RUE) of web applications with minimal computational cost. This technique conducts experimental works on parameters such as RT, Bandwidth Utilization Rate (BUR) computational cost, Energy Consumption (EC), and RUE. Experimental analysis reveals that PSC‐FRCO technique enhances enhances RUE and lessens RT as compared to state‐of‐the‐art works.
To overcome limitations of efficient resource allocation technique for web application, Pearson service correlation‐based firefly resource cost optimization technique is designed. Pearson service correlation‐based firefly resource cost optimization achieves higher efficiency while rendering services in cloud computing which uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner.</description><identifier>ISSN: 1074-5351</identifier><identifier>EISSN: 1099-1131</identifier><identifier>DOI: 10.1002/dac.3771</identifier><language>eng</language><publisher>Chichester: Wiley Subscription Services, Inc</publisher><subject>Applications programs ; bandwidth ; Cloud computing ; cloud resource ; Computational efficiency ; Computing costs ; Correlation ; Cost analysis ; Cost engineering ; energy ; Energy consumption ; firefly resource cost optimization ; Minimum cost ; Optimization ; Optimization techniques ; Pearson service correlation ; Performance enhancement ; Provisioning ; Resource allocation ; Resource utilization ; Response time (computers) ; user request ; Webs</subject><ispartof>International journal of communication systems, 2018-10, Vol.31 (15), p.n/a</ispartof><rights>2018 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2931-3e80fa71776db14e0757ef4f42c4b7c3f42aff9d044926a12fdf13a5be00ac6a3</citedby><cites>FETCH-LOGICAL-c2931-3e80fa71776db14e0757ef4f42c4b7c3f42aff9d044926a12fdf13a5be00ac6a3</cites><orcidid>0000-0002-4958-9632</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fdac.3771$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fdac.3771$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Gokulraj, S.</creatorcontrib><creatorcontrib>Geetha, B.G.</creatorcontrib><title>Integration of firefly optimization and Pearson service correlation for efficient cloud resource utilization</title><title>International journal of communication systems</title><description>Summary
Cloud Computing (CC) environment presents a simplified, centralized platform or resources to usage while necessitated at minimum cost. In CC, the main processes in is the allocation of resources of web applications. However, with the increasing demands of Cloud User (CU), an efficient resource allocation technique for web applications is required. According to the request made by the user and response obtained, the cost of resources has also to be optimized. To overcome such limitations, Pearson service correlation‐based firefly resource cost optimization (PSC‐FRCO) technique is designed. Pearson service correlation‐based firefly resource cost optimization technique not only improves the performance of cost aware resource allocation but also achieves higher efficiency while rendering services in cloud computing environment for web applications. Pearson service correlation‐based firefly resource cost optimization technique initially uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner. This helps in improving the Response Time (RT) of cloud service provisioning. Next, firefly resource cost optimization algorithm is applied to identify and allocate the cost‐optimized cloud resources to users to afford required service from the cloud server. Thus, PSC‐FRCO technique improves the Resource Utilization Efficiency (RUE) of web applications with minimal computational cost. This technique conducts experimental works on parameters such as RT, Bandwidth Utilization Rate (BUR) computational cost, Energy Consumption (EC), and RUE. Experimental analysis reveals that PSC‐FRCO technique enhances enhances RUE and lessens RT as compared to state‐of‐the‐art works.
To overcome limitations of efficient resource allocation technique for web application, Pearson service correlation‐based firefly resource cost optimization technique is designed. Pearson service correlation‐based firefly resource cost optimization achieves higher efficiency while rendering services in cloud computing which uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner.</description><subject>Applications programs</subject><subject>bandwidth</subject><subject>Cloud computing</subject><subject>cloud resource</subject><subject>Computational efficiency</subject><subject>Computing costs</subject><subject>Correlation</subject><subject>Cost analysis</subject><subject>Cost engineering</subject><subject>energy</subject><subject>Energy consumption</subject><subject>firefly resource cost optimization</subject><subject>Minimum cost</subject><subject>Optimization</subject><subject>Optimization techniques</subject><subject>Pearson service correlation</subject><subject>Performance enhancement</subject><subject>Provisioning</subject><subject>Resource allocation</subject><subject>Resource utilization</subject><subject>Response time (computers)</subject><subject>user request</subject><subject>Webs</subject><issn>1074-5351</issn><issn>1099-1131</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kE9PwzAMxSMEEmMg8REiceHSESdt0x6n8W_SJDjAOcpSB2XqmpG0oPHpyeiunPxk__RsP0Kugc2AMX7XaDMTUsIJmQCr6wxAwOlByzwrRAHn5CLGDWOs4mUxIe2y6_Ej6N75jnpLrQto2z31u95t3c_Y111DX1GHmHTE8OUMUuNDwHacWx8oWuuMw66npvVDQwNGP4QEDr1rj0aX5MzqNuLVsU7J--PD2-I5W708LRfzVWZ4LSATWDGrJUhZNmvIkclCos1tzk2-lkYkoa2tG5bnNS81cNtYELpYI2PalFpMyc3ouwv-c8DYq026pUsrFQfGOVQVsETdjpQJPsb0ttoFt9Vhr4CpQ5YqZakOWSY0G9Fv1-L-X07dzxd__C_Y8nds</recordid><startdate>201810</startdate><enddate>201810</enddate><creator>Gokulraj, S.</creator><creator>Geetha, B.G.</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-4958-9632</orcidid></search><sort><creationdate>201810</creationdate><title>Integration of firefly optimization and Pearson service correlation for efficient cloud resource utilization</title><author>Gokulraj, S. ; Geetha, B.G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2931-3e80fa71776db14e0757ef4f42c4b7c3f42aff9d044926a12fdf13a5be00ac6a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Applications programs</topic><topic>bandwidth</topic><topic>Cloud computing</topic><topic>cloud resource</topic><topic>Computational efficiency</topic><topic>Computing costs</topic><topic>Correlation</topic><topic>Cost analysis</topic><topic>Cost engineering</topic><topic>energy</topic><topic>Energy consumption</topic><topic>firefly resource cost optimization</topic><topic>Minimum cost</topic><topic>Optimization</topic><topic>Optimization techniques</topic><topic>Pearson service correlation</topic><topic>Performance enhancement</topic><topic>Provisioning</topic><topic>Resource allocation</topic><topic>Resource utilization</topic><topic>Response time (computers)</topic><topic>user request</topic><topic>Webs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gokulraj, S.</creatorcontrib><creatorcontrib>Geetha, B.G.</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>International journal of communication systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gokulraj, S.</au><au>Geetha, B.G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integration of firefly optimization and Pearson service correlation for efficient cloud resource utilization</atitle><jtitle>International journal of communication systems</jtitle><date>2018-10</date><risdate>2018</risdate><volume>31</volume><issue>15</issue><epage>n/a</epage><issn>1074-5351</issn><eissn>1099-1131</eissn><abstract>Summary
Cloud Computing (CC) environment presents a simplified, centralized platform or resources to usage while necessitated at minimum cost. In CC, the main processes in is the allocation of resources of web applications. However, with the increasing demands of Cloud User (CU), an efficient resource allocation technique for web applications is required. According to the request made by the user and response obtained, the cost of resources has also to be optimized. To overcome such limitations, Pearson service correlation‐based firefly resource cost optimization (PSC‐FRCO) technique is designed. Pearson service correlation‐based firefly resource cost optimization technique not only improves the performance of cost aware resource allocation but also achieves higher efficiency while rendering services in cloud computing environment for web applications. Pearson service correlation‐based firefly resource cost optimization technique initially uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner. This helps in improving the Response Time (RT) of cloud service provisioning. Next, firefly resource cost optimization algorithm is applied to identify and allocate the cost‐optimized cloud resources to users to afford required service from the cloud server. Thus, PSC‐FRCO technique improves the Resource Utilization Efficiency (RUE) of web applications with minimal computational cost. This technique conducts experimental works on parameters such as RT, Bandwidth Utilization Rate (BUR) computational cost, Energy Consumption (EC), and RUE. Experimental analysis reveals that PSC‐FRCO technique enhances enhances RUE and lessens RT as compared to state‐of‐the‐art works.
To overcome limitations of efficient resource allocation technique for web application, Pearson service correlation‐based firefly resource cost optimization technique is designed. Pearson service correlation‐based firefly resource cost optimization achieves higher efficiency while rendering services in cloud computing which uses Pearson service correlation in which the user‐required service is identified by correlating the available services provided by cloud owner.</abstract><cop>Chichester</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/dac.3771</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0002-4958-9632</orcidid></addata></record> |
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subjects | Applications programs bandwidth Cloud computing cloud resource Computational efficiency Computing costs Correlation Cost analysis Cost engineering energy Energy consumption firefly resource cost optimization Minimum cost Optimization Optimization techniques Pearson service correlation Performance enhancement Provisioning Resource allocation Resource utilization Response time (computers) user request Webs |
title | Integration of firefly optimization and Pearson service correlation for efficient cloud resource utilization |
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