Overcommitment in Cloud Services: Bin Packing with Chance Constraints

Published Online:https://doi.org/10.1287/mnsc.2018.3091

References

  • Abdelaziz FB, Aouni B, El Fayedh R (2007) Multi-objective stochastic programming for portfolio selection. Eur. J. Oper. Res. 177(3):1811–1823.CrossrefGoogle Scholar
  • Albers S, Souza A (2011) Combinatorial algorithms lecture notes: Bin packing. Accessed August 1, 2017, https://www2.informatik.hu-berlin.de/alcox/lehre/lvws1011/coalg/bin_packing.pdf.Google Scholar
  • Atamtürk A, Narayanan V (2008) Polymatroids and mean-risk minimization in discrete optimization. Oper. Res. Lett. 36(5):618–622.CrossrefGoogle Scholar
  • Bays C (1977) A comparison of next-fit, first-fit, and best-fit. Comm. ACM 20(3):191–192.CrossrefGoogle Scholar
  • Bertsimas D, Popescu I (2005) Optimal inequalities in probability theory: A convex optimization approach. SIAM J. Optim. 15(3):780–804.CrossrefGoogle Scholar
  • Calafiore GC, El Ghaoui L (2006) On distributionally robust chance-constrained linear programs. J. Optim. Theory Appl. 130(1):1–22.CrossrefGoogle Scholar
  • Cardoen B, Demeulemeester E, Beliën J (2010) Operating room planning and scheduling: A literature review. Eur. J. Oper. Res. 201(3):921–932.CrossrefGoogle Scholar
  • Charnes A, Cooper WW (1963) Deterministic equivalents for optimizing and satisfying under chance constraints. Oper. Res. 11(1):18–39.LinkGoogle Scholar
  • Coffman EG Jr, Garey MR, Johnson DS (1996) Approximation algorithms for bin packing: A survey. Approximation Algorithms for NP-Hard Problems (PWS Publishing Co., Boston), 46–93.Google Scholar
  • Coffman EG Jr, So K, Hofri M, Yao A (1980) A stochastic model of bin-packing. Inform. Control 44(2):105–115.CrossrefGoogle Scholar
  • Csirik J, Johnson DS, Kenyon C, Orlin JB, Shor PW, Weber RR (2006) On the sum-of-squares algorithm for bin packing. J. ACM 53(1):1–65.CrossrefGoogle Scholar
  • Delage E, Ye Y (2010) Distributionally robust optimization under moment uncertainty with application to data-driven problems. Oper. Res. 58(3):595–612.LinkGoogle Scholar
  • de La Vega WF, Lueker GS (1981) Bin packing can be solved within 1+ ϵ in linear time. Combinatorica 1(4):349–355.CrossrefGoogle Scholar
  • Delorme M, Iori M, Martello S (2016) Bin packing and cutting stock problems: Mathematical models and exact algorithms. Eur. J. Oper. Res. 255(1):1–20.CrossrefGoogle Scholar
  • Deng Y, Shen S, Denton B (2016) Chance-constrained surgery planning under conditions of limited and ambiguous data. Working paper, University of Michigan, Ann Arbor.Google Scholar
  • Denton BT, Miller AJ, Balasubramanian HJ, Huschka TR (2010) Optimal allocation of surgery blocks to operating rooms under uncertainty. Oper. Res. 58(4, part 1):802–816.LinkGoogle Scholar
  • Dinh HT, Lee C, Niyato D, Wang P (2013) A survey of mobile cloud computing: Architecture, applications, and approaches. Wireless Comm. Mobile Comput. 13(18):1587–1611.CrossrefGoogle Scholar
  • Dósa G (2007) The tight bound of first fit decreasing bin-packing algorithm is ffd≤11/9opt+6/9. Combinatorics, Algorithms, Probabilistic and Experimental Methodologies (Springer, Berlin), 1–11.CrossrefGoogle Scholar
  • Dósa G, Sgall J (2013) First fit bin packing: A tight analysis. Portier N, Wilke T, eds. LIPIcs-Leibniz Internat. Proc. Informatics (Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, Dagstuhl Publishing, Germany), 538–549.Google Scholar
  • El Ghaoui L, Oks M, Oustry F (2003) Worst-case value-at-risk and robust portfolio optimization: A conic programming approach. Oper. Res. 51(4):543–556.LinkGoogle Scholar
  • Fox A, Griffith R, Joseph A, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I (2009) Above the clouds: A Berkeley view of cloud computing. Report No. UCB/EECS 28(13):2009, Department Electrical Engineering and Computer Sciences, University of California, Berkeley.Google Scholar
  • Gilmore PC, Gomory RE (1961) A linear programming approach to the cutting-stock problem. Oper. Res. 9(6):849–859.LinkGoogle Scholar
  • Goemans MX, Harvey NJ, Iwata S, Mirrokni V (2009) Approximating submodular functions everywhere. Mathieu C, ed. Proc. 20th Ann. ACM-SIAM Sympos. on Discrete Algorithms (Brown University, Providence, RI), 535–544.CrossrefGoogle Scholar
  • Goyal V, Ravi R (2010) A PTAS for the chance-constrained knapsack problem with random item sizes. Oper. Res. Lett. 38(3):161–164.CrossrefGoogle Scholar
  • Gupta V, Radovanovic A (2015) Lagrangian-based online stochastic bin packing. ACM SIGMETRICS Perform. Eval. Rev. 43(1):467–468.CrossrefGoogle Scholar
  • Han J, Lee K, Lee C, Choi KS, Park S (2016) Robust optimization approach for a chance-constrained binary knapsack problem. Math. Programming 157(1):277–296.CrossrefGoogle Scholar
  • Johnson DS (1974) Fast algorithms for bin packing. J. Comput. System Sci. 8(3):272–314.CrossrefGoogle Scholar
  • Keller G, Tighe M, Lutfiyya H, Bauer M (2012) An analysis of first fit heuristics for the virtual machine relocation problem. Lobo J, Owezarski P, Zhang H, Medhi D, eds. Proc. 8th Internat. Conf. Network Service Management (IEEE, New York), 406–413.Google Scholar
  • Kenyon C, et al.. (1996) Best-fit bin-packing with random order. Proc. 7th Ann. ACM-SIAM Sympos. Discrete Algorithms (SODA), (Society for Industrial and Applied Mathematics, Philadelphia), 359–364.Google Scholar
  • Kim U (2015) This one chart shows the vicious price war going on in Cloud computing. Bus. Insider (January 14), http://www.businessinsider.com/cloud-computing-price-war-in-one-chart-2015-1.Google Scholar
  • Kleinberg J, Rabani Y, Tardos É (2000) Allocating bandwidth for bursty connections. SIAM J. Comput. 30(1):191–217.CrossrefGoogle Scholar
  • Lee S, Panigrahy R, Prabhakaran V, Ramasubramanian V, Talwar K, Uyeda L, Wieder U (2011) Validating heuristics for virtual machines consolidation. Technical Report, Microsoft Research Silicon Valley, Mountain View, CA.Google Scholar
  • Luedtke J, Ahmed S, Nemhauser GL (2010) An integer programming approach for linear programs with probabilistic constraints. Math. Programming 122(2):247–272.CrossrefGoogle Scholar
  • Lueker GS (1983) Bin packing with items uniformly distributed over intervals [a, b]. Proc. 24th Ann. Sympos. Foundations Computer Sci. (IEEE, New York), 289–297.CrossrefGoogle Scholar
  • Nemirovski A, Shapiro A (2006) Convex approximations of chance constrained programs. SIAM J Optim. 17(4):969–996.CrossrefGoogle Scholar
  • Pisinger D, Sigurd M (2005) The two-dimensional bin packing problem with variable bin sizes and costs. Discrete Optim. 2(2):154–167.CrossrefGoogle Scholar
  • Roytman A, Kansal A, Govindan S, Liu J, Nath S (2013) Algorithm design for performance aware vm consolidation. Technical Report, Microsoft Research, Redmond, WA.Google Scholar
  • Shylo OV, Prokopyev OA, Schaefer AJ (2012) Stochastic operating room scheduling for high-volume specialties under block booking. INFORMS J. Comput. 25(4):682–692.LinkGoogle Scholar
  • Stolyar AL, Zhong Y (2015) Asymptotic optimality of a greedy randomized algorithm in a large-scale service system with general packing constraints. Queueing Systems 79(2):117–143.CrossrefGoogle Scholar
  • Svitkina Z, Fleischer L (2011) Submodular approximation: Sampling-based algorithms and lower bounds. SIAM J Comput. 40(6):1715–1737.CrossrefGoogle Scholar
  • Verma A, Pedrosa L, Korupolu MR, Oppenheimer D, Tune E, Wilkes J (2015) Large-scale cluster management at Google with Borg. Proc. European Conf. Computer Systems (EuroSys, Bordeaux, France), 1–17.CrossrefGoogle Scholar
  • Zhang Y, Jiang R, Shen S (2016) Distributionally robust chance-constrained bin packing. Working paper, University of Michigan, Ann Arbor.Google Scholar
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