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Autonomic performance-per-watt management (APM) of cloud resources and services

Authors:

Youssif Al-Nashif,

Salim HaririAuthors Info & Claims

CAC '13: Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference

Article No.: 2, Pages 1 - 10

https://doi.org/10.1145/2494621.2494624

Published: 09 August 2013 Publication History

Abstract

With the rapid growth of data centers and clouds, the power cost and power consumption of their computing and storage resources become critically important to be managed efficiently. Several research studies have shown that data servers typically operate at a low utilization of 10% to 15%, while their power consumption is close to those at peak loads. With this significant fluctuation in the workloads, an elastic delivery of computing services with an efficient power provisioning mechanism becomes an important design goal. Live workload migrations and virtualization are important techniques to optimize power and performance in large-scale data centers [5], [25] This paper presents an application specific autonomic adaptive power and performance management system that utilizes AppFlow-based reasoning to configure dynamically datacenter resources and workload allocations. This system will continuously monitor the workload to determine the current operating point of both workloads and the virtual machines (VMs) running these workloads and then predict the next operating points for these VMs. This enables the system to allocate the appropriate amount of hardware resources that can run efficiently the VM workloads with minimum power consumption. We have experimented with and evaluated our approach to manage the VMs running RUBiS bidding application. Our experimental results showed that our approach can reduce the VMs' power consumption up to 84% compared to static resource allocation and up to 30% compared to other methods with minimum performance degradation.

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Cited By

Fargo FVissapragada SSury S(2019)CONCORD: Improving Communication using Consumer-Count Detection2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA47632.2019.9035220(1-11)Online publication date: Nov-2019
https://doi.org/10.1109/AICCSA47632.2019.9035220
Fargo FFranza OTunc CHariri S(2019)Autonomic Resource Management for Power, Performance, and Security in Cloud Environment2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA47632.2019.9035213(1-4)Online publication date: Nov-2019
https://doi.org/10.1109/AICCSA47632.2019.9035213
Ozdemir ATunc CHariri S(2017)Autonomic Fall Detection System2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W)10.1109/FAS-W.2017.142(166-170)Online publication date: Sep-2017
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Index Terms

Autonomic performance-per-watt management (APM) of cloud resources and services
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
2. General and reference
  1. Cross-computing tools and techniques
    1. Performance
    2. Reliability

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cover image ACM Other conferences

CAC '13: Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference

August 2013

247 pages

ISBN:9781450321723

DOI:10.1145/2494621

General Chair:
Salim Hariri
University of Arizona
,
Program Chair:
Alan Sill
Texas Tech University

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Arizona: University of Arizona
OGF: Open Grid Forum
Florida Intl University: Florida International Univeristy

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Association for Computing Machinery

New York, NY, United States

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Published: 09 August 2013

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CAC '13: ACM Cloud and Autonomic Computing Conference

August 5 - 9, 2013

Florida, Miami, USA

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Cited By

Fargo FVissapragada SSury S(2019)CONCORD: Improving Communication using Consumer-Count Detection2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA47632.2019.9035220(1-11)Online publication date: Nov-2019
https://doi.org/10.1109/AICCSA47632.2019.9035220
Fargo FFranza OTunc CHariri S(2019)Autonomic Resource Management for Power, Performance, and Security in Cloud Environment2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA47632.2019.9035213(1-4)Online publication date: Nov-2019
https://doi.org/10.1109/AICCSA47632.2019.9035213
Ozdemir ATunc CHariri S(2017)Autonomic Fall Detection System2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W)10.1109/FAS-W.2017.142(166-170)Online publication date: Sep-2017
https://doi.org/10.1109/FAS-W.2017.142
Tunc CFargo FAl-Nashif YHariri S(2017)Autonomic Cross-Layer Management of Cloud Systems2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W)10.1109/FAS-W.2017.141(160-165)Online publication date: Sep-2017
https://doi.org/10.1109/FAS-W.2017.141
Tunc CMachovec DKumbhare NAkoglu AHariri SKhemka BSiegel H(2017)Value of service based resource management for large-scale computing systemsCluster Computing10.1007/s10586-017-0901-920:3(2013-2030)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1007/s10586-017-0901-9
Machovec DTunc CKumbhare NKhemka BAkoglu AHariri SSiegel HChard KCostan ANicolae BZhao D(2016)Value-Based Resource Management in High-Performance Computing SystemsProceedings of the ACM 7th Workshop on Scientific Cloud Computing10.1145/2913712.2913716(19-26)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1145/2913712.2913716
Tunc CKumbhare NAkoglu AHariri SMachovec DSiegel H(2016)Value of Service Based Task Scheduling for Cloud Computing Systems2016 International Conference on Cloud and Autonomic Computing (ICCAC)10.1109/ICCAC.2016.22(1-11)Online publication date: Sep-2016
https://doi.org/10.1109/ICCAC.2016.22
Kumbhare NTunc CHariri SDjordjevic IAkoglu ASiegel H(2016)Just In Time Architecture (JITA) for dynamically composable data centers2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)10.1109/AICCSA.2016.7945778(1-8)Online publication date: Nov-2016
https://doi.org/10.1109/AICCSA.2016.7945778
Rosa Righi RCosta CRodrigues VRostirolla G(2016)Joint-analysis of performance and energy consumption when enabling cloud elasticity for synchronous HPC applicationsConcurrency and Computation: Practice & Experience10.1002/cpe.371028:5(1548-1571)Online publication date: 10-Apr-2016
https://dl.acm.org/doi/10.1002/cpe.3710
Singh SChana I(2015)QoS-Aware Autonomic Resource Management in Cloud ComputingACM Computing Surveys10.1145/284388948:3(1-46)Online publication date: 22-Dec-2015
https://dl.acm.org/doi/10.1145/2843889
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