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Virtual Machine Placement Jian Tang 02

2. Outline. ReferenceChallengesContributionsProblem FormulationMathematical ProgrammingBin Packaging Problem and AlgorithmsThe Allocation AlgorithmsData PreprocessingSimulation Results. 3. Reference. B. Speitkamp and M. Bichler, A mathematical programming approach for server consolidation

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Virtual Machine Placement Jian Tang 02

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    1. 1 Virtual Machine Placement Jian Tang 02/16/2012

    2. 2 Outline Reference Challenges Contributions Problem Formulation Mathematical Programming Bin Packaging Problem and Algorithms The Allocation Algorithms Data Preprocessing Simulation Results

    3. 3 Reference B. Speitkamp and M. Bichler, A mathematical programming approach for server consolidation problems in virtualized data centers, IEEE Transactions on Services Computing, Vol. 3, No. 4, 2010, pp. 266-278.

    4. 4 Challenges The main purpose of server virtualization is server consolidation. The workload and system requirements for different services are known or can be estimated with a high degree of confidence from historical workload data. The challenge is to find an allocation of Virtual Machines (VMs) to target servers that minimizes costs, considering quality of service (QoS) requirements.

    5. 5 Contributions A mathematical formulation of the server consolidation problems. A complexity analysis showing that the fundamental problem is an NP-hard optimization problem. An LP-relaxation-based heuristic to solve this problem. A data preprocessing method characterizing workload traces.

    6. 6 Problem Formulation How many and which servers are required for a given set of services (VMs). An allocation of services to servers with respect to the objective function. Possibly additional support for decisions that aim to minimize investment and operational costs.

    7. 7 Problem Formulation

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