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Resource Scheduling And Service Matching Research Under Cloud Bank Environment

Posted on:2017-03-15Degree:MasterType:Thesis
Country:ChinaCandidate:C M ZhangFull Text:PDF
GTID:2309330488464358Subject:Systems analysis and integration
Abstract/Summary:PDF Full Text Request
Resource integration and redistribution was implemented by cloud computing effectively. And web service was applied to deliver computing power of cloud computing to remote users. Now more and more cloud providers emerged with the development of cloud computing. Cloud consumers will never be limited in a single cloud. They are trending to get combinational resources that are lesser cost, more reliable and more abundant from multi clouds. Broker-based use mode in multi-cloud is able to help users getting best fit combinational solution for resources and services. Business model of commercial bank is transplant into broker-based multi-cloud use mode and developed a new model called cloud bank model. There are many differences on resource scheduling and service selection between broker-based multi-cloud and cloud bank model. For better matches between resources and user requirements, this paper concentrates on modeling work of resource, service and user requirement based on environment of cloud bank. Based on built models designed a match rules between user requirement and resources. A unique mechanism for user requirement deployment in cloud bank is improved. And it will get lower cost on premise of all QoS requirements are met.The innovational points of this paper are:Network characteristic and cost between clouds is introduced in resource model of cloud bank. In users’ requirement model, connection constraints between different nodes were considered. Some nodes that are beyond user requirement but have relation with user requirement are also brought into discussion. Nodes in requirement are classified into different cases and dealt with each case on its merits.Make analyze and comparison on global and local resource combination situation in cloud bank. Based on this, improved a unique mechanism for user requirement deployment. At last a simple simulation experiment is conduct and the result proved it can get lower cost when this strategy is used.
Keywords/Search Tags:Cloud bank, requirement model, resource model, resource combination
PDF Full Text Request
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