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Issue No. 04 - October-December (2010 vol. 3)
ISSN: 1939-1374
pp: 266-278
Benjamin Speitkamp , Technische Universität München, Munich
Martin Bichler , Technische Universität München, Munich
Today's data centers offer IT services mostly hosted on dedicated physical servers. Server virtualization provides a technical means for server consolidation. Thus, multiple virtual servers can be hosted on a single server. Server consolidation describes the process of combining the workloads of several different servers on a set of target servers. We focus on server consolidation with dozens or hundreds of servers, which can be regularly found in enterprise data centers. Cost saving is among the key drivers for such projects. This paper presents decision models to optimally allocate source servers to physical target servers while considering real-world constraints. Our central model is proven to be an NP-hard problem. Therefore, besides an exact solution method, a heuristic is presented to address large-scale server consolidation projects. In addition, a preprocessing method for server load data is introduced allowing for the consideration of quality-of-service levels. Extensive experiments were conducted based on a large set of server load data from a data center provider focusing on managerial concerns over what types of problems can be solved. Results show that, on average, server savings of 31 percent can be achieved only by taking cycles in the server workload into account.
Management of services delivery, modeling of resources, data center management services, optimization of services systems.

B. Speitkamp and M. Bichler, "A Mathematical Programming Approach for Server Consolidation Problems in Virtualized Data Centers," in IEEE Transactions on Services Computing, vol. 3, no. , pp. 266-278, 2010.
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