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The Robust Tenant Placement and Migration Problem

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Multi Tenancy for Cloud-Based In-Memory Column Databases

Part of the book series: In-Memory Data Management Research ((IMDM))

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Abstract

In this chapter, we introduce the problem of assigning tenants to servers so that performance SLOs are enforced and server cost is minimized. We call this problem the Robust Tenant Placement and Migration Problem (RTP).

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Notes

  1. 1.

    Technically, the response time in the 99-th percentile has been measured and transformed into load using Eq. (3.6).

  2. 2.

    Another conceivable option would be to copy the tenant from a shared filesystem. We focus on shared-nothing architectures in this dissertation (cf. Chap. 2).

Bibliography

  1. C. Curino, E.P.C. Jones, S. Madden, H. Balakrishnan, Workload-aware database monitoring and consolidation, in Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2011, Athens, 12–16 June 2011 (ACM, 2011), pp. 313–324

    Google Scholar 

  2. J. Duggan, U. Çetintemel, O. Papaemmanouil, E. Upfal, Performance prediction for concurrent database workloads, in Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2011, Athens, 12–16 June 2011 (ACM, 2011), pp. 337–348

    Google Scholar 

  3. L. Epstein, A. Levin, On bin packing with conflicts. SIAM J. Optim. 19(3), 1270–1298 (2008)

    Article  Google Scholar 

  4. F. Färber, S.K. Cha, J. Primsch, C. Bornhövd, S. Sigg, W. Lehner, SAP HANA database: data management for modern business applications. SIGMOD Rec. 40(4), 45–51 (2011)

    Article  Google Scholar 

  5. M.R. Garey, D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness (W. H. Freeman, San Francisco, 1979). ISBN:0-7167-1044-7

    Google Scholar 

  6. L. Hedegard, J. Dietz, The benefits of enabling fallback in the active data warehouse. Teradata Mag. Online 7(1) (2007). http://apps.teradata.com/tdmo/v07n01/tech2tech/asktheexpert/benefitsoffallback.aspx (Online). Accessed 13 Dec 2012

  7. D.S. Johnson, Approximation algorithms for combinatorial problems. J. Comput. Syst. Sci. 9(3), 256–278 (1974)

    Article  Google Scholar 

  8. V. Kaibel, M.E. Pfetsch, Packing and partitioning orbitopes. Math. Program. 114, 1–36 (2008)

    Article  Google Scholar 

  9. J. Krüger, C. Kim, M. Grund, N. Satish, D. Schwalb, J. Chhugani, H. Plattner, P. Dubey, A. Zeier, Fast updates on read-optimized databases using multi-core CPUs. PVLDB 5(1), 61–72 (2011)

    Google Scholar 

  10. W. Lang, S. Shankar, J.M. Patel, A. Kalhan, Towards multi-tenant performance SLOs, in IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, DC (Arlington, VA), 1–5 Apr 2012 (IEEE Computer Society, 2012), pp. 702–713

    Google Scholar 

  11. W. Leinberger, G. Karypis, V. Kumar, Multi-capacity bin packing algorithms with applications to job scheduling under multiple constraints, in ICPP, Aizu-Wakamatsu City, 1999, pp. 404–412

    Google Scholar 

  12. SAP, BusinessObjects BI OnDemand (2012), http://www.biondemand.com/businessintelligence (Online). Accessed 13 Dec 2012

  13. J.M. Valério de Carvalho, Exact solution of bin-packing problems using column generation and branch-and-bound. Ann. Oper. Res. 86, 629–659 (1999)

    Article  Google Scholar 

  14. F. Yang, J. Shanmugasundaram, R. Yerneni, A scalable data platform for a large number of small applications, in CIDR 2009, Fourth Biennial Conference on Innovative Data Systems Research, Asilomar, 4–7 Jan 2009. Online Proceedings, 2009, www.cidrdb.org

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Schaffner, J. (2014). The Robust Tenant Placement and Migration Problem. In: Multi Tenancy for Cloud-Based In-Memory Column Databases. In-Memory Data Management Research. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00497-6_4

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