Multi-objective Optimization Framework for VMI Distribution in Federated Cloud Repositories
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Cloud Federation facilitates the concept of aggregation of multiple services administered by different providers, thus opening the possibility for the customers to profit from lower cost and better performance, while allowing for the cloud providers to offer more sophisticated services. Unfortunately, current state-of-the-art does not provide any substantial means for streamlined adaptation of federated Cloud environments. One of the essential barriers that prevents Cloud federation is the inefficient management of distributed storage repositories for Virtual Machine Images (VMI). In such environments, the VMIs are currently stored by Cloud providers in proprietary centralised repositories without considering application characteristics and their runtime requirements, causing high deployment and instantiation overheads. In this paper, a novel multi-objective optimization framework for VMI placement across distributed repositories in federated Cloud environment has been proposed. Based on the communication performance requirements, VMI use patterns, and structure of images or input data, the framework provides efficient means for transparent optimization of the distribution and placement of VMIs across distributed repositories to significantly lower their provisioning time for complex resource requests and for executing the user applications.
KeywordsFederated Cloud environment Distributed storage repositories Multi-objective optimization
This work is being accomplished as a part of project ENTICE: “dEcentralised repositories for traNsparent and efficienT vIrtual maChine opErations”, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 644179.
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