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Flow-Aware Workload Migration in Data Centers

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Abstract

In data centers, subject to workloads with heterogeneous (and sometimes short) lifetimes, workload migration is a way of attaining a more efficient utilization of the underlying physical machines. To not introduce performance degradation, such workload migration must take into account not only machine resources, and per-task resource requirements, but also application dependencies in terms of network communication. This paper presents a workload migration model capturing all of these constraints. A linear programming framework is developed allowing accurate representation of per-task resources requirements and inter-task network demands. Using this, a multi-objective problem is formulated to compute a re-allocation of tasks that (1) maximizes the total inter-task throughput, while (2) minimizing the cost incurred by migration and (3) allocating the maximum number of new tasks. A baseline algorithm, solving this multi-objective problem using the \(\varepsilon\)-constraint method is proposed, in order to generate the set of Pareto-optimal solutions. As this algorithm is compute-intensive for large topologies, a heuristic, which computes an approximation of the Pareto front, is then developed, and evaluated on different topologies and with different machine load factors. These evaluations show that the heuristic can provide close-to-optimal solutions, while reducing the solving time by one to two order of magnitudes.

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Notes

  1. For instance, the size of RAM plus storage for a virtual machine.

  2. This term is used generically to refer to any forwarding node in the network, regardless of its actually being a router or a switch.

  3. \({\mathbf{z}}^{t-1}\) is obtained by starting from a random state and solving (15) where only the throughput objective is considered, with the additional constraint that all tasks must be allocated.

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Authors and Affiliations

  1. École Polytechnique, 91128, Palaiseau, France

    Yoann Desmouceaux & Thomas Clausen

  2. Cisco Systems Paris Innovation and Research Laboratory (PIRL), 92782, Issy-les-Moulineaux, France

    Yoann Desmouceaux

  3. Université Paris-Dauphine, PSL Research University, LAMSADE, CNRS UMR 7243, 75016, Paris, France

    Sonia Toubaline

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  1. Yoann Desmouceaux
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  2. Sonia Toubaline
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Correspondence to Yoann Desmouceaux.

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Desmouceaux, Y., Toubaline, S. & Clausen, T. Flow-Aware Workload Migration in Data Centers. J Netw Syst Manage 26, 1034–1057 (2018). https://doi.org/10.1007/s10922-018-9452-5

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