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A Multi-Objective Secure Optimal VM Placement in Energy-Efficient Server of Cloud Computing

Sangeetha Ganesan*, Sumathi Ganesan

Department of Information Technology, Sri Venkateswara College of Engineering, Sriperumbudur, 602117, India

* Corresponding Author: Sangeetha Ganesan. Email: email

Intelligent Automation & Soft Computing 2021, 30(2), 387-401.


Cloud Computing has been economically famous for sharing the resources of third-party applications. There may be an increase in the exploitation of the prevailing Cloud resources and their vulnerabilities as a result of the aggressive growth of Cloud Computing. In the Cache Side Channel Attack (CSCA), the attackers can leak sensitive information of a Virtual Machine (VM) which is co-located in a physical machine due to inadequate logical isolation. The Cloud Service Provider (CSP) has to modify either at the hardware level to isolate their VM or at the software, level to isolate their applications. The hardware isolation requires changes in hardware design and it also leads to performance degradation. The existing works challenge to eliminate CSCA. But our solution prevents CSCA by securing the VM placement in the energy-efficient server. This paper proposes a heuristic secure VM placement policy by using different VM placement techniques (Least VM, Multi-Objective Ant Colony System (MOACO), Previously Assigned Physical Host First (PAPHF)) based on user behaviours to prevent co-resident. The Co-Resident Rate for the three VM placement policies (Least VM, MOACO, PAPHF) has been compared with the existing First Fit Decreasing (FFD) algorithm and Discrete Firefly Algorithm-VM Placement (DFA-VMP) policy in the CloudSim environment. The Power Consumption, Resource Wastage, and Co-Resident probability are compared with the existing FFD and DFA-VMP Systems. Our Multi-Objective Secure Optimal VM Placement (MOSOVMP) proposed system proved that the Co-Resident Rate is reduced with improved server utilization.


Cite This Article

S. Ganesan and S. Ganesan, "A multi-objective secure optimal vm placement in energy-efficient server of cloud computing," Intelligent Automation & Soft Computing, vol. 30, no.2, pp. 387–401, 2021.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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