Exploring Design Alternatives for RAMP Transactions Through Statistical Model Checking

  • Si Liu
  • Peter Csaba Ölveczky
  • Jatin Ganhotra
  • Indranil Gupta
  • José Meseguer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10610)

Abstract

Arriving at a mature distributed system design through implementation and experimental validation is a labor-intensive task. This limits the number of design alternatives that can be explored in practice. In this work we use formal modeling with probabilistic rewrite rules and statistical model checking to explore and extend the design space of the RAMP (Read Atomic Multi-Partition) transaction system for large-scale partitioned data stores. Specifically, we formally model in Maude eight RAMP designs, only two of which were previously implemented and evaluated by the RAMP developers; and we analyze their key consistency and performance properties by statistical model checking. Our results: (i) are consistent with the experimental evaluations of the two implemented designs; (ii) are also consistent with conjectures made by the RAMP developers for other unimplemented designs; and (iii) uncover some promising new designs that seem attractive for some applications.

Notes

Acknowledgments

We thank the anonymous reviewers for helpful comments on a previous version of this paper. This work was partially supported by NSF CNS 1409416, AFOSR/AFRL FA8750-11-2-0084, and NSF CNS 1319527.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Si Liu
    • 1
  • Peter Csaba Ölveczky
    • 1
    • 2
  • Jatin Ganhotra
    • 3
  • Indranil Gupta
    • 1
  • José Meseguer
    • 1
  1. 1.University of IllinoisUrbana-ChampaignUSA
  2. 2.University of OsloOsloNorway
  3. 3.IBM ResearchNew YorkUSA

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