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Issue No. 02 - February (2012 vol. 23)
ISSN: 1045-9219
pp: 219-231
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
David Carrera , Universitat Politècnica de Catalonia and Barcelona Supercomputing Center, Barcelona
Eduard Ayguadé , Universitat Politècnica de Catalonia and Barcelona Supercomputing Center, Barcelona
ABSTRACT
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.
INDEX TERMS
Performance management, workload management, resource management, cloud computing, virtualization.
CITATION
Malgorzata Steinder, Ian Whalley, Jordi Torres, David Carrera, Eduard Ayguadé, "Autonomic Placement of Mixed Batch and Transactional Workloads", IEEE Transactions on Parallel & Distributed Systems, vol. 23, no. , pp. 219-231, February 2012, doi:10.1109/TPDS.2011.129
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