Abstract
The cloud computing environments rely heavily on virtualization that enables the physical hardware resources to be shared among cloud users by creating virtual machines (VMs). With an overloaded physical machine, the resource requests by virtual machines may not be fulfilled, which results in Service Level Agreement (SLA) violations. Moreover, the high performance servers in cloud data centers consume large amount of energy. The dynamic VM consolidation techniques use live migration of virtual machines to optimize resource utilization and minimize energy consumption. An excessive migration of virtual machines may however deteriorate application performance due to the overhead incurring at runtime. In this paper, we propose a normalization-based VM consolidation (NVMC) strategy that aims at placing virtual machines in an online manner while minimizing energy consumption, SLA violations, and the number of VM migrations. The proposed strategy uses resource parameters for determining over-utilized hosts in a virtualized cloud environment. The comparative capacity of virtual machines and hosts is incorporated for determining over-utilized hosts, while the cumulative available-to-total ratio (CATR) is used to find under-utilized hosts. For migrating virtual machines to appropriate hosts, the VM placement uses a criteria based on normalized resource parameters of hosts and virtual machines. For evaluating the performance of VM consolidation, we have performed experimentation with a large number of virtual machines using traces from the PlanetLab workloads. The results show that the NVMC approach outperforms other well-known approaches by achieving a significant improvement in energy consumption, SLA violations, and number of VM migrations.
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Data availability
The datasets used for experimentation in this research work are available with the well-known CloudSim simulator that may be accessed from the repository: https://github.com/Cloudslab/cloudsim/releases.
Notes
With upper bound for competitive-ratio being \(1+(m*c/(2*(m+1)))\), where m is the maximum number of virtual machines that may be allocated to a host demanding maximum CPU capacity, and c is the cost of SLA violations.
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Khan, M.A. An efficient energy-aware approach for dynamic VM consolidation on cloud platforms. Cluster Comput 24, 3293–3310 (2021). https://doi.org/10.1007/s10586-021-03341-0
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DOI: https://doi.org/10.1007/s10586-021-03341-0