NDLI: An adaptive power management framework for autonomic resource configuration in cloud computing infrastructures

Content Provider	IEEE Xplore Digital Library
Author	Ziming Zhang Qiang Guan Song Fu
Copyright Year	2012
Description	Author affiliation: Department of Computer Science and Engineering, University of North Texas, Denton, Texas 76203-5017 (Ziming Zhang; Qiang Guan; Song Fu)
Abstract	Power is becoming an increasingly important concern for large-scale cloud computing systems. Meanwhile, cloud service providers leverage virtualization technologies to facilitate service consolidation and enhance resource utilization. However, the introduction of virtualization makes the cloud infrastructure more complex, and thus challenges cloud power management. In a virtualized environment, resource needs to be configured at runtime at the cloud, server and virtual machine levels to achieve high power efficiency. In addition, cloud power management should guarantee high users' SLA (service level agreement) satisfaction. In this paper, we present an adaptive power management framework in the cloud to achieve autonomic resource configuration. We propose a software and lightweight approach to accurately estimate the power usage of virtual machines and cloud servers. It explores hypervisor-observable performance metrics to build the power usage model. To configure cloud resources, we consider both the system power usage and the SLA requirements, and leverage learning techniques to achieve autonomic resource allocation and optimal power efficiency. We implement a prototype of the proposed power management system and test it on a cloud testbed. Experimental results show the high accuracy (over 90%) of our power usage estimation mechanism and our resource configuration approach achieves the lowest energy usage among the compared four approaches.
Starting Page	51
Ending Page	60
File Size	271635
Page Count	10
File Format	PDF
ISBN	9781467348812
ISSN	10972641
e-ISBN	9781467348836
DOI	10.1109/PCCC.2012.6407738
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power demand Servers Virtual machining Hardware Resource management Estimation Measurement Energy efficiency Cloud computing Power management Resource allocation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Energy efficient architectural framework for virtual machine management in IaaS clouds

Multi-objective Optimization Based Virtual Resource Allocation Strategy for Cloud Computing

AFD: Adaptive failure detection system for cloud computing infrastructures

An Effective Approach for Allocating VMs to Reduce the Power Consumption of Virtualized Cloud Environment

Elastic Resource Allocation in the Cloud

Energy Saving Virtual Machine Allocation in Cloud Computing

Proposing a load balancing method based on Cuckoo Optimization Algorithm for energy management in cloud computing infrastructures

Autonomic Allocation of Communicating Virtual Machines in Hierarchical Cloud Data Centers

Double threshold energy aware load balancing in cloud computing

An adaptive power management framework for autonomic resource configuration in cloud computing infrastructures

Similar Documents

Energy efficient architectural framework for virtual machine management in IaaS clouds

Multi-objective Optimization Based Virtual Resource Allocation Strategy for Cloud Computing

AFD: Adaptive failure detection system for cloud computing infrastructures

An Effective Approach for Allocating VMs to Reduce the Power Consumption of Virtualized Cloud Environment

Elastic Resource Allocation in the Cloud

Energy Saving Virtual Machine Allocation in Cloud Computing

Proposing a load balancing method based on Cuckoo Optimization Algorithm for energy management in cloud computing infrastructures

Autonomic Allocation of Communicating Virtual Machines in Hierarchical Cloud Data Centers

Double threshold energy aware load balancing in cloud computing

An adaptive power management framework for autonomic resource configuration in cloud computing infrastructures