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Dolphin partner optimization based secure and qualified virtual machine for resource allocation with streamline security analysis

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Abstract

Cloud computing has mounted itself as an exciting computational version that provides a huge range of Virtual Machine (VM) resources, including CPU, storage, memory, network bandwidth and databases, etc. However, one important problem here is a way to efficiently allocate secure virtual machine for resource allocation that consumes more time. To overcome this problem, an efficient optimization algorithm with security has to be chosen to select most secure and qualified virtual machine for resource allocation. In this venture, this work has proposed Dolphin Partner Optimization based Secure and Qualified Virtual Machine for resource allocation with streamline security. The Energy based Prioritization and Memory aware Optimization is used to select energy based and memory based VMs for security purpose, moreover this work have added hypervisor security to the obtained two sets of VMs. Subsequently, the Dolphin Partner Optimization optimizes the two sets of VMs to produce the best qualified virtual machine for each set. Finally, streamline security is added to improve the security level and the selected virtual machine is virtually best secured one. Proposed methodology is implemented using the CloudSim tool and the experimental results shows that the proposed method gives better security level and less time consumption.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Mar Ephraem College of Engineering and Technology, Elavuvilai-629171, Kanyakumari District, Tamilnadu, India

    D. Dhanya

  2. Department of Mathematics, Anna University, Chennai-600025, Chennai, Tamilnadu, India

    D. Arivudainambi

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  1. D. Dhanya
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  2. D. Arivudainambi
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Dhanya, D., Arivudainambi, D. Dolphin partner optimization based secure and qualified virtual machine for resource allocation with streamline security analysis. Peer-to-Peer Netw. Appl. 12, 1194–1213 (2019). https://doi.org/10.1007/s12083-019-00765-9

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  • DOI: https://doi.org/10.1007/s12083-019-00765-9

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