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Autonomic Placement of Mixed Batch and Transactional Workloads
February 2012 (vol. 23 no. 2)
pp. 219-231
ASCII Text
x 
 
David Carrera, Malgorzata Steinder, Ian Whalley, Jordi Torres, Eduard Ayguadé, "Autonomic Placement of Mixed Batch and Transactional Workloads," IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 2, pp. 219-231, February, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TPDS.2011.129,
author = {David Carrera and Malgorzata Steinder and Ian Whalley and Jordi Torres and Eduard Ayguadé},
title = {Autonomic Placement of Mixed Batch and Transactional Workloads},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {23},
number = {2},
issn = {1045-9219},
year = {2012},
pages = {219-231},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.129},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - Autonomic Placement of Mixed Batch and Transactional Workloads
IS - 2
SN - 1045-9219
SP219
EP231
EPD - 219-231
A1 - David Carrera,
A1 - Malgorzata Steinder,
A1 - Ian Whalley,
A1 - Jordi Torres,
A1 - Eduard Ayguadé,
PY - 2012
KW - Performance management
KW - workload management
KW - resource management
KW - cloud computing
KW - virtualization.
VL - 23
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 
David Carrera, Universitat Politècnica de Catalonia and Barcelona Supercomputing Center, Barcelona
Malgorzata Steinder, IBM T.J. Watson Research Center, Hawthorne
Ian Whalley, IBM T.J. Watson Research Center, Hawthorne
Jordi Torres, Universitat Politècnica de Catalonia and Barcelona Supercomputing Center, Barcelona
Eduard Ayguadé, Universitat Politècnica de Catalonia and Barcelona Supercomputing Center, Barcelona
To reduce the cost of infrastructure and electrical energy, enterprise datacenters consolidate workloads on the same physical hardware. Often, these workloads comprise both transactional and long-running analytic computations. Such consolidation brings new performance management challenges due to the intrinsically different nature of a heterogeneous set of mixed workloads, ranging from scientific simulations to multitier transactional applications. The fact that such different workloads have different natures imposes the need for new scheduling mechanisms to manage collocated heterogeneous sets of applications, such as running a web application and a batch job on the same physical server, with differentiated performance goals. In this paper, we present a technique that enables existing middleware to fairly manage mixed workloads: long running jobs and transactional applications. Our technique permits collocation of the workload types on the same physical hardware, and leverages virtualization control mechanisms to perform online system reconfiguration. In our experiments, including simulations as well as a prototype system built on top of state-of-the-art commercial middleware, we demonstrate that our technique maximizes mixed workload performance while providing service differentiation based on high-level performance goals.

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Index Terms:
Performance management, workload management, resource management, cloud computing, virtualization.
Citation:
David Carrera, Malgorzata Steinder, Ian Whalley, Jordi Torres, Eduard Ayguadé, "Autonomic Placement of Mixed Batch and Transactional Workloads," IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 2, pp. 219-231, Feb. 2012, doi:10.1109/TPDS.2011.129
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