Abstract

Internet of Things (IoT) coupled with big data analytics is emerging as the core of smart and sustainable systems which bolsters economic, environmental and social sustainability. Cloud-based data centers provide high performance computing power to analyze voluminous IoT data to provide invaluable insights to support decision making. However, multifarious servers in data centers appear to be the black hole of superfluous energy consumption that contributes to 23% of the global carbon dioxide (CO2) emissions in ICT (Information and Communication Technology) industry. IoT-related energy research focuses on low-power sensors and enhanced machine-to-machine communication performance. To date, cloud-based data centers still face energy–related challenges which are detrimental to the environment. Virtual machine (VM) consolidation is a well-known approach to affect energy-efficient cloud infrastructures. Although several research works demonstrate positive results for VM consolidation in simulated environments, there is a gap for investigations on real, physical cloud infrastructure for big data workloads. This research work addresses the gap of conducting real physical cloud infrastructure-based experiments. The primary goal of setting up a real physical cloud infrastructure is for the evaluation of dynamic VM consolidation approaches which include integrated algorithms from existing relevant research. An open source VM consolidation framework, Openstack NEAT is adopted and experiments are conducted on a Multi-node Openstack Cloud with Apache Spark as the big data platform. Open sourced Openstack has been deployed because it enables rapid innovation, and boosts scalability as well as resource utilization. Additionally, this research work investigates the performance based on service level agreement (SLA) metrics and energy usage of compute hosts. Relevant results concerning the best performing combination of algorithms are presented and discussed.

Highlights

  • Internet of Things (IoT) is the outcome of the emanating third wave of the Internet of Everything

  • This research work focuses on energy-related challenges and state-of-the-art energy efficient cloud systems. It encompasses the investigation of Virtual machine (VM) consolidation impact on power usage characteristics of compute hosts in a physical private cloud infrastructure. This is followed by conducting appropriate experiments which focus on VM consolidation algorithms evaluation using service level agreement (SLA) and energy consumption-related metrics

  • Power usage effective (PUE) is a ratio of energy consumed by the data center to the energy supplied to the computing equipment

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Summary

Introduction

Internet of Things (IoT) is the outcome of the emanating third wave of the Internet of Everything. Cloud-based data center facilities that house physical networked computers and infrastructure play a crucial role in providing elastic computing resources to create an illusion of infinite resources [4] Such high performance and responsive computing systems consume a lot of energy. This research work focuses on energy-related challenges and state-of-the-art energy efficient cloud systems It encompasses the investigation of VM consolidation impact on power usage characteristics of compute hosts in a physical private cloud infrastructure. This is followed by conducting appropriate experiments which focus on VM consolidation algorithms evaluation using SLA and energy consumption-related metrics

Related Work and Underlying Concepts
Cloud-Based Data Centers
Energy-Efficient Computing Systems
Cloud Resource Management
Results and Discussion
Performance Evaluation

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