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Optimal deployment of eventually-serializable data services

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Abstract

Providing consistent and fault-tolerant distributed object services is among the fundamental problems in distributed computing. To achieve fault-tolerance and to increase throughput, objects are replicated at different networked nodes. However, replication induces significant communication costs to maintain replica consistency. Eventually-Serializable Data Service (ESDS) has been proposed to reduce these costs and enable fast operations on data, while still providing guarantees that the replicated data will eventually be consistent. This paper reconsiders the deployment phase of ESDS, in which a particular implementation of communicating software components must be mapped onto a physical architecture. This deployment aims at minimizing the overall communication costs, while satisfying the constraints imposed by the protocol. Both MIP (Mixed Integer Programming) and CP (Constraint Programming) models are presented and applied to realistic ESDS instances. The experimental results indicate that both models can find optimal solutions and prove optimality. The CP model, however, provides orders of magnitude improvements in efficiency. The limitations of the MIP model and the critical aspects of the CP model are discussed. Symmetry breaking and parallel computing are also shown to bring significant benefits.

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References

  • Aguilera, M. (2007). Hewlett-Packard. Personal communication.

  • Bastarrica, M. C. (2000). Architectural specification and optimal deployment of distributed systems. Ph.D. thesis, University of Connecticut.

  • Bastarrica, M., Demurjian, S., & Shvartsman, A. (1998). Software architectural specification for optimal object distribution. In SCCC’98: Proc. of the XVIII int-l conf. of the Chilean computer science society, Washington, DC, USA.

  • Behrmann, G., David, A., Larsen, K., Möller, O., Pettersson, P., & Yi, W. (2001). Uppaal—present and future. In Proceedings of the 40th IEEE conference on decision and control (CDC’2001) (pp. 2881–2886).

  • Boysen, N. (2010). Truck scheduling at zero-inventory cross docking terminals. Computers and Operations Research, 37(1), 32–41. http://dx.doi.org/10.1016/j.cor.2009.03.010.

    Article  Google Scholar 

  • Cheiner, O., & Shvartsman, A. (1999). Implementing an eventually-serializable data service as a distributed system building block. Networks in Distributed Computing, 45, 43–71.

    Google Scholar 

  • Fekete, A., Gupta, D., Luchangco, V., Lynch, N., & Shvartsman, A. (1996). Eventually-serializable data services. In PODC’96: Proceedings of the fifteenth annual ACM symposium on principles of distributed computing (pp. 300–309).

  • Gilbert, S., Lynch, N. A., & Shvartsman, A. A. (2003). Rambo ii: rapidly reconfigurable atomic memory for dynamic networks. In DSN (p. 259). Los Alamitos: IEEE Comput. Soc.

    Google Scholar 

  • IETF (1990). Domain name system, rfc 1034 and rfc 1035.

  • Kaynar, D. K., Lynch, N., Segala, R., & Vaandrager, F. (2006). The theory of timed I/O automata (Synthesis lectures in computer science). San Rafaell: Morgan & Claypool Publishers.

    Google Scholar 

  • Larsen, K. G., Pettersson, P., & Yi, W. (1997). UPPAAL in a nutshell. International Journal on Software Tools for Technology Transfer, 1(1–2), 134–152.

    Google Scholar 

  • Li, Y., Lim, A., & Rodrigues, B. (2004). Crossdocking—JIT scheduling with time windows. Journal of the Operational Research Society, 55(12), 1342–1351.

    Article  Google Scholar 

  • Lim, A., Ma, H., & Miao, Z. (2006). Lecture notes in computer science: Vol. 3982. Truck dock assignment problem with time windows and capacity constraint in transshipment network through crossdocks (p. 688).

  • Lynch, N., & Shvartsman, A. (2002). Rambo: a reconfigurable atomic memory service for dynamic networks. In Proceedings of the 16th international symposium on distributed computing (pp. 173–190).

  • Lynch, N., & Tuttle, M. (1989). An introduction to Input/Output Automata. CWI-Quarterly, 2(3), 219–246.

    Google Scholar 

  • Lynch, N. A., Garland, S., Kaynar, D., Michel, L., & Shvartsman, A. (2007). The tempo language user guide and reference manual. http://www.veromodo.com, VeroModo Inc., December 2007.

  • Miao, Z., Lim, A., & Ma, H. (2009). Truck dock assignment problem with operational time constraint within crossdocks. European Journal of Operational Research, 192(1), 105–115.

    Article  Google Scholar 

  • Michel, L., See, A., & Van Hentenryck, P. (2007). Parallelizing constraint programs transparently. In Proceedings of the 13th international conference on the principles and practice of constraint programming (CP-2007), Providence.

  • Michel, L., Van Hentenryck, P., Sonderegger, E., Shvartsman, A., & Moraal, M. (2009). Bandwidth-limited optimal de ployment of eventually-serializable data services. In Integration of AI and OR techniques in constraint programming for combinatorial optimization problems: 6th international conference, CPAIOR 2009 (p. 193), Pittsburgh, PA, USA, May 27–31, 2009. Berlin: Springer.

    Chapter  Google Scholar 

  • Pardalos, P. M., & Wolkowicz, H. (Eds.) (1994). DIMACS series in discrete mathematics and theoretical computer science : Vol. 16. Quadratic assignment and related problems: DIMACS workshop, May 20–21, 1993. Providence: American Mathematical Society.

    Google Scholar 

  • Owre, S., Rajan, S., Rushby, J. M., Shankar, N., & Srivas, M. K. (1996). PVS: combining specification, proof checking, and model checking. In Proceedings of the eighth international conference on computer aided verification CAV (Vol. 1102, pp. 411–414), New Brunswick, NJ, USA.

  • Saito, Y., Frølund, S., Veitch, A. C., Merchant, A., & Spence, S. (2004). Fab: building distributed enterprise disk arrays from commodity components. In Mukherjee, S., & McKinley, K. S. (Eds.), ASPLOS (pp. 48–58). New York: ACM.

    Google Scholar 

  • Van Hentenryck, P., Flener, P., Pearson, J., & Ågren, M. (2003). Tractable symmetry breaking for csps with interchangeable values. In International joint conference on artificial intelligence (IJCAI’03).

  • Yu, W., & Egbelu, P. (2008). Scheduling of inbound and outbound trucks in cross docking systems with temporary storage. European Journal of Operational Research, 184(1), 377–396.

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Connecticut, Storrs, CT, 06269-2155, USA

    L. Michel, A. Shvartsman & E. Sonderegger

  2. Brown University, Box 1910, Providence, RI, 02912, USA

    P. Van Hentenryck

Authors
  1. L. Michel
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  2. A. Shvartsman
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  3. E. Sonderegger
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  4. P. Van Hentenryck
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Correspondence to L. Michel.

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Michel, L., Shvartsman, A., Sonderegger, E. et al. Optimal deployment of eventually-serializable data services. Ann Oper Res 184, 273–294 (2011). https://doi.org/10.1007/s10479-010-0684-3

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  • DOI: https://doi.org/10.1007/s10479-010-0684-3

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