Checkpoint Placement Research Articles

A variational calculus approach to optimal checkpoint placement

Checkpointing is an effective fault-tolerant technique for improving system availability and reliability. However, a blind checkpointing placement can result in either performance degradation or expensive recovery cost. By means of the calculus of variations, we derive an explicit formula that links the optimal checkpointing frequency with a general failure rate, with the objective of globally minimizing the total expected cost of checkpointing and recovery. Theoretical result shows that the optimal checkpointing frequency is proportional to the square root of the failure rate and can be uniquely determined by the failure rate (time-varying or constant) if the recovery function is strictly increasing and the failure rate is /spl lambda/(/spl infin/)>0. J.L. Bruno and E.G. Coffman (1997) suggest that optimal checkpointing by its nature is a function of system failure rate, i.e., the time-varying failure rate demands time-varying checkpointing in order to meet the criteria of certain optimality. The results obtained in this paper agree with their viewpoint.

An optimal checkpointing-strategy for real-time control systems under transient faults

Real-time computer systems are often used in harsh environments, such as aerospace, and in industry. Such systems are subject to many transient faults while in operation. Checkpointing enables a reduction in the recovery time from a transient fault by saving intermediate states of a task in a reliable storage facility, and then, on detection of a fault, restoring from a previously stored state. The interval between checkpoints affects the execution time of the task. Whereas inserting more checkpoints and reducing the interval between them reduces the reprocessing time after faults, checkpoints have associated execution costs, and inserting extra checkpoints increases the overall task execution time. Thus, a trade-off between the reprocessing time and the checkpointing overhead leads to an optimal checkpoint placement strategy that optimizes certain performance measures. Real-time control systems are characterized by a timely, and correct, execution of iterative tasks within deadlines. The reliability is the probability that a system functions according to its specification over a period of time. This paper reports on the reliability of a checkpointed real-time control system, where any errors are detected at the checkpointing time. The reliability is used as a performance measure to find the optimal checkpointing strategy. For a single-task control system, the reliability equation over a mission time is derived using the Markov model. Detecting errors at the checkpointing time makes reliability jitter with the number of checkpoints. This forces the need to apply other search algorithms to find the optimal number of checkpoints. By considering the properties of the reliability jittering, a simple algorithm is provided to find the optimal checkpoints effectively. Finally, the reliability model is extended to include multiple tasks by a task allocation algorithm.

Checkpoint Placement for Fault-Tolerant Real-Time Systems

The objective of this paper is to analyze the worst case timing requirement of real-time tasks with checkpointing and to provide the optimal checkpoint placement scheme for fault-tolerant real-time systems. The proposed scheme aims at minimizing the worst case timing requirement of a task which has up to n checkpoints to tolerate a finite permissible number of failures. Simulation result shows that, though it does not increase the average case timing requirement of a task too much, it reduces the worst case timing requirement of a task by about 7% to 26% compared with modified equidistant scheme. The timing information derived in this paper makes checkpointing applicable to real-time systems while keeping the validity of schedulability check developed in the past.

An on-line algorithm for checkpoint placement

Checkpointing enables us to reduce the time to recover from a fault by saving intermediate states of the program in a reliable storage. The length of the intervals between checkpoints affects the execution time of programs. On one hand, long intervals lead to long reprocessing time, while, on the other hand, too frequent checkpointing leads to high checkpointing overhead. In this paper, we present an on-line algorithm for placement of checkpoints. The algorithm uses knowledge of the current cost of a checkpoint when it decides whether or not to place a checkpoint. The total overhead of the execution time when the proposed algorithm is used is smaller than the overhead when fixed intervals are used. Although the proposed algorithm uses only on-line knowledge about the cost of checkpointing, its behavior is close to the off-line optimal algorithm that uses a complete knowledge of checkpointing cost.

Reliability of checkpointed real-time systems using time redundancy

Real-time computers are often used in embedded, life-critical applications where high reliability is important. A common approach to making such systems dependable is to vote on redundant processors executing multiple copies of the same task is described. The processors which make up such voted systems are subjected not only to independently occurring permanent and transient failure, but also to correlated transients brought about by electromagnetic interference from the operating environment. To counteract these transients, checkpointing and time redundancy are required, in addition to processor redundancy. This work analyzes the use of time and device redundancy in systems subject to correlated failure. The tradeoffs in checkpoint placement in such a system are found to be considerably different from those for non-redundant systems without real-time constraints. The authors compare fault-tolerant designs and without a rollback capability, accounting for the increased hardware-failure rate due to processor duplication when faults are detected in hardware, and the doubled execution times when detection is implemented in software. >

Optimal Checkpointing of Real-Time Tasks

Analytical models for the design and evaluation of checkpointing of real-time tasks are developed. First, the execution of a real-time task is modeled under a common assumption of perfect coverage of on-line detection mechanisms (which is termed a basic model). Then, the model is generalized (to an extended model) to include more realistic cases, i.e., imperfect coverages of on-line detection mechanisms and acceptance tests. Finally, we determine an optimal placement of checkpoints to minimize the mean task execution time while the probability of an unreliable result (or lack of confidence) is kept below a specified level. In the basic model, it is shown that equidistant intercheckpoint intervals are optimal, whereas this is not necessarily true in the extended model. An algorithm for calculating the optimal number of checkpoints and intercheckpoint intervals is presented with some numerical examples for the extended model.

Optimization criteria for checkpoint placement

Mean response time and availability as optimization criteria for checkpoint placement are better replaced by workable formulas that calculate the ratio between the marginal gain accrued to users who experience system failure and the (presumably slight) loss suffered on average by all users.