VMSAGE: A Virtual Machine Scheduling Algorithm based on the Gravitational Effect for Green Cloud Computing

Xiaolong Xu, Qitong Zhang, Stathis Maneas, Stelios Sotiriadis, Collette Gavan, Nik Bessis

Research output: Contribution to journalArticle

1 Citation (Scopus)
4 Downloads (Pure)

Abstract

The area of sustainable green smart computing highlights key challenges to wards reducing cost and carbon dioxide emissions due to the high-energy consumption of Cloud data centres. Here, we focus on the Cloud virtual machine (VM) scheduling that is usually based on simple algorithms, e.g. VM placement on nodes with low memory usage. This approach fails to consider the actual configuration of nodes inside the server rack resulting in local overheating of Cloud data centres. To solve this, we propose a VM scheduling algorithm based on the gravitational effect, called VMSAGE, to optimize energy efficiency of Cloud computing systems. Inspired by the physical gravitation model, we define the thermal repulsion and logical gravitation factors between physical nodes and VMs. To achieve optimized VM scheduling, we propose a gravitation function that refers to the calculation of the logical quality of each VM, host and rack through the algorithm, so as to draw the attractiveness between them. Based on the concept of dimension reduction, VMSAGE conducts the two-dimensional plane target selection twice to reduce the computational cost. Additionally, VMSAGE evaluates attributes of the computer room to carry out the VM deployment. To demonstrate the effectiveness of our solution, we compare it with the Best Fit Heuristic (BFH) and the dynamic voltage and frequency scaling (DVFS) algorithms. The results indicate that our algorithm achieves 10% and 20% optimized energy consumption respectively. The experimental results highlight our contribution, in where VMSAGE can significantly reduce energy consumption rates and VM migration times.
Original languageEnglish
Pages (from-to)87-103
JournalSimulation Modelling Practice and Theory
Volume93
Early online date17 Oct 2018
DOIs
Publication statusE-pub ahead of print - 17 Oct 2018

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Machine Scheduling
Virtual Machine
Cloud computing
Scheduling algorithms
Cloud Computing
Scheduling Algorithm
Gravitation
Energy Consumption
Rack
Energy utilization
Data Center
Scheduling
Dimension Reduction
Carbon Dioxide
Vertex of a graph
Virtual machine
Placement
Migration
High Energy
Computational Cost

Keywords

  • Virtual MachineScheduling AlgorithmEnergy EfficiencyGravitation EffectCloud Computing

Cite this

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title = "VMSAGE: A Virtual Machine Scheduling Algorithm based on the Gravitational Effect for Green Cloud Computing",
abstract = "The area of sustainable green smart computing highlights key challenges to wards reducing cost and carbon dioxide emissions due to the high-energy consumption of Cloud data centres. Here, we focus on the Cloud virtual machine (VM) scheduling that is usually based on simple algorithms, e.g. VM placement on nodes with low memory usage. This approach fails to consider the actual configuration of nodes inside the server rack resulting in local overheating of Cloud data centres. To solve this, we propose a VM scheduling algorithm based on the gravitational effect, called VMSAGE, to optimize energy efficiency of Cloud computing systems. Inspired by the physical gravitation model, we define the thermal repulsion and logical gravitation factors between physical nodes and VMs. To achieve optimized VM scheduling, we propose a gravitation function that refers to the calculation of the logical quality of each VM, host and rack through the algorithm, so as to draw the attractiveness between them. Based on the concept of dimension reduction, VMSAGE conducts the two-dimensional plane target selection twice to reduce the computational cost. Additionally, VMSAGE evaluates attributes of the computer room to carry out the VM deployment. To demonstrate the effectiveness of our solution, we compare it with the Best Fit Heuristic (BFH) and the dynamic voltage and frequency scaling (DVFS) algorithms. The results indicate that our algorithm achieves 10{\%} and 20{\%} optimized energy consumption respectively. The experimental results highlight our contribution, in where VMSAGE can significantly reduce energy consumption rates and VM migration times.",
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VMSAGE: A Virtual Machine Scheduling Algorithm based on the Gravitational Effect for Green Cloud Computing. / Xu, Xiaolong; Zhang, Qitong; Maneas, Stathis; Sotiriadis, Stelios; Gavan, Collette; Bessis, Nik.

In: Simulation Modelling Practice and Theory, Vol. 93, 17.10.2018, p. 87-103.

Research output: Contribution to journalArticle

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AU - Zhang, Qitong

AU - Maneas, Stathis

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AU - Gavan, Collette

AU - Bessis, Nik

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