Energy-aware VM placement algorithms for the OpenStack Neat consolidation framework

Fikru Feleke Moges,Surafel Lemma Abebe

doi:10.1186/s13677-019-0126-y

Fikru Feleke Moges, Surafel Lemma Abebe

Open Access

https://doi.org/10.1186/s13677-019-0126-y

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Abstract

One of the main challenges in cloud computing is an enormous amount of energy consumed in data-centers. Several researches have been conducted on Virtual Machine(VM) consolidation to optimize energy consumption. Among the proposed VM consolidations, OpenStack Neat is notable for its practicality. OpenStack Neat is an open-source consolidation framework that can seamlessly integrate to OpenStack, one of the most common and widely used open-source cloud management tool. The framework has components for deciding when to migrate VMs and for selecting suitable hosts for the VMs (VM placement). The VM placement algorithm of OpenStack Neat is called Modified Best-Fit Decreasing (MBFD). MBFD is based on a heuristic that handles only minimizing the number of servers. The heuristic is not only less energy efficient but also increases Service Level Agreement (SLA) violation and consequently cause more VM migrations. To improve the energy efficiency, we propose VM placement algorithms based on both bin-packing heuristics and servers’ power efficiency. In addition, we introduce a new bin-packing heuristic called a Medium-Fit (MF) to reduce SLA violation. To evaluate performance of the proposed algorithms we have conducted experiments using CloudSim on three cloud data-center scenarios: homogeneous, heterogeneous and default. Workloads that run in the data-centers are generated from traces of PlanetLab and Bitbrains clouds. The results of the experiment show up-to 67% improvement in energy consumption and up-to 78% and 46% reduction in SLA violation and amount of VM migrations, respectively. Moreover, all improvements are statistically significant with significance level of 0.01.

Highlights

Cloud computing refers to the provisioning of computing capability as a service through the Internet
We address the limitation of Modified Best-Fit Decreasing (MBFD); thereby proposing an enhancement to the OpenStack Neat consolidation to improve energy efficiency, lower Virtual machine (VM) migrations and Service Level Agreement (SLA) violation
Performance of algorithms in the default-scenario In the Default-scenario all proposed algorithms give lower energy consumption, reduced SLA violation and VM migrations compared with baseline algorithms

Summary

Introduction

Cloud computing refers to the provisioning of computing capability as a service through the Internet. Since the algorithm is based on the best-fit decreasing heuristic, it has high efficiency of consolidating VMs to a smaller number of servers. The overload will intern increases SLA violations and the number of VM migrations, and (ii) in a heterogeneous cloud, the MBFD algorithm loses the benefit of favoring power-efficient servers and will be less energy efficient.

Results

Conclusion