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2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Satisfying Service Level Objectices in a Self-Managing Resource Pool
San Francisco, California, USA
September 14-September 18
ISBN: 978-0-7695-3794-8
ASCII Text
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Daniel Gmach, Jerry Rolia, Lucy Cherkasova, "Satisfying Service Level Objectices in a Self-Managing Resource Pool," 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems, pp. 243-253, 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2009.
 
 
BibTex
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@article{ 10.1109/SASO.2009.27,
author = {Daniel Gmach and Jerry Rolia and Lucy Cherkasova},
title = {Satisfying Service Level Objectices in a Self-Managing Resource Pool},
journal ={2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems},
volume = {0},
year = {2009},
isbn = {978-0-7695-3794-8},
pages = {243-253},
doi = {http://doi.ieeecomputersociety.org/10.1109/SASO.2009.27},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems
TI - Satisfying Service Level Objectices in a Self-Managing Resource Pool
SN - 978-0-7695-3794-8
SP243
EP253
A1 - Daniel Gmach,
A1 - Jerry Rolia,
A1 - Lucy Cherkasova,
PY - 2009
KW - Resource Pool Management
KW - Enterprise Workload Analysis
KW - Differentiated Service
KW - Quality of Service
VL - 0
JA - 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems
ER -
 
We consider a self-managing, self-organizing pool of virtualized computer servers that provides infrastructure as a service (IaaS) for enterprise computing workloads. A global controller automatically manages the pool in a top down manner by periodically varying the number of servers used and re-assigning workloads to different servers. It aims to use as few servers as possible to minimize power usage while satisfying per-workload service level requirements. Each server is self-organizing. It has a local workload manager that dynamically varies the capacity allocated to each workload to satisfy per-workload service level objectives. This paper evaluates the impact of four alternative workload manager policies on the quality of service provided by the resource pool. The policies include: i) a non-work-conserving feedback controller, ii) a work-conserving feedback controller, iii) a work-conserving feedback controller with fixed per-workload scheduling weights to support differentiated service, and iv) a work-conserving feedback controller with dynamic per-workload weight to provide differentiated service while minimizing penalties. A case study involving three months of data for 138 SAP applications shows that the work-conserving policy significantly outperforms the non-work-conserving policy. The dynamic weight policy is better able to minimize penalties than the other policies while treating workloads fairly. Our study offers insights into the trade-offs between performance isolation, efficient resource sharing, and quality of service.
Index Terms:
Resource Pool Management, Enterprise Workload Analysis, Differentiated Service, Quality of Service
Citation:
Daniel Gmach, Jerry Rolia, Lucy Cherkasova, "Satisfying Service Level Objectices in a Self-Managing Resource Pool," saso, pp.243-253, 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2009
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