Abstract

The management strategy of a data center needs access to sufficient resources in order to handle different requests of applications, while minimizing the consumed energy. With regard to high and varying resource demands, Virtual Machines (VM) management necessitates dynamic strategies. Dynamic management of VMs includes VM placement and VM migration. The management approach presented in this paper aimed to reduce the energy consumption and the violation of service level agreements (SLA) simultaneously in data centers. The simulation results indicate that proposed approach improved the VM management 40% compared to the previous single-goal approaches based on the energy consumption and SLA violation rates.

Highlights

  • Nowadays, computing tends to handle large-scale data centers and provides the resources for client applications as pay-per-use

  • This paper focuses on two important issues in dynamic management of virtual machines: service level agreements (SLA) violations reduction, and energy consumption reduction

  • Evaluation of pernormal and slavnormal in Energy-reduction and SLAV-reduction dynamic run-time replacement (ESDR) Switching between two approaches Energy-Reduction and SLAV-Reduction in ESDR occurs when the metrics related to the goal of active approach is within the normal/acceptable range considering the threshold values

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Summary

Introduction

Nowadays, computing tends to handle large-scale data centers and provides the resources for client applications as pay-per-use. The resource allocation can be handled statically by assigning the peak number of required resources to the application. Such allocation may lead to overprovisioning [1], which results in wasting of data centers’ resources. Even if the peak amount of demanded resources is allocated to the application, still some resources of physical machine may be underutilized. Resource utilization can be improved by allocating only necessary resources to handle the typical demands. This may result in resource access competition between VMs in high demand conditions

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