JOURNAL ARTICLE

Energy-Aware Virtual Machine Consolidation for Cloud Data Centers

Abstract

One of the issues in virtual machine consolidation (VMC) in cloud data centers is categorizing different workloads to classify the state of physical servers. In this paper, we propose a new scheme of host's load categorization in energy-performance VMC framework to reduce energy consumption while meeting the quality of service (QoS) requirement. Specifically the under loaded hosts are classified into three further states, i.e., Under loaded, normal and critical by applying the under load detection algorithm. We also design overload detection and virtual machine (VM) selection policies. The simulation results show that the proposed policies outperform the existing policies in Cloud Sim in terms of both energy and service level agreements violation (SLAV) reduction.

Keywords:
Computer science Cloud computing Virtual machine Server Quality of service Energy consumption Virtualization Distributed computing Operating system Computer network Engineering

Metrics

34
Cited By
5.65
FWCI (Field Weighted Citation Impact)
12
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Software-Defined Networks and 5G
Physical Sciences →  Computer Science →  Computer Networks and Communications

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