Abstract

A large number of distributed checkpointing protocols have appeared in the literature. However, to make informed decisions about which protocol performs best for a given environment, one must use an objective measure for comparing them. Obviously, a distributed checkpointing protocol could be the best in a specific environment, but not in another environment. This paper presents an objective measure, called overhead ratio, for evaluating distributed checkpointing protocols. This measure extends previous evaluation schemes by incorporating several additional parameters that are inherent in distributed environments. In particular, we take into account the rollback propagation of the protocol, which impacts the length of the recovery process, and therefore the expected program run-time in executions that involve failures and recoveries. Using the objective measure as an evaluation technique, the paper also analyses several known protocols and compares their overhead ratios.

Keywords: Distributed checkpoint/restart; Rollback propagation; Performance analysis; Markov models

Article Outline

1. Introduction

2. Preliminaries

2.1. System model

2.2. Definitions and notations

2.3. Assumptions and limitations

3. The overhead ratio

3.1. Computing Γ_k using Markov chains

3.1.1. Computing Γ₀

3.1.2. Computing Γ₁

3.1.3. Computing Γ₂

3.1.4. Computing Γ_k

3.2. Computing the overhead ratio

3.3. Numerical results

4. Performance analysis of checkpointing protocols

4.1. Distributed checkpointing protocols

4.1.1. Sync-and-Stop (SaS) [25]

4.1.2. Chandy–Lamport (C–L) [11]

4.1.3. Baldoni, Helary, Mostefaoai and Raynal (BHMR) [7]

4.1.4. Fixed-Dependency-Interval (FDI) [40]

4.1.5. Briatico, Ciuffoletti and Simoncini (BCS) [10]

4.1.6. Baldoni, Quaglia and Ciciani (BQC) [8]

4.1.7. Helary, Mostefaoui and Raynal (HMR) [14]

4.1.8. Manivannan–Singhal (M–S) [17]

4.1.9. d-Bounded Cycles (d-BC) [1]

4.2. Comparing distributed checkpointing protocols

5. Related work

6. Conclusions

Acknowledgements

References

Vitae

This research is supported by the Bar-Nir Bergreen Software Technology Centre of Excellence.