Rollback and Recovery Strategies for Computer Programs

Chandy, K. Mani; Ramamoorthy, C. V.

doi:10.1109/tc.1972.5009007

Cited by 131 publications

(52 citation statements)

References 7 publications

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“…Figure 2 presents task definitions from the web browser example. A task definition consists of the task keyword, the task's name, the task's parameter declarations, and t a g p t =new t a g ( p a g e t a g ) ; 4 Page p=new Page ( ) ( add p t ) ; 5 . .…”

Section: Classesmentioning

confidence: 99%

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Recovery Tasks: An Automated Approach to Failure Recovery

Demsky

Zhou

Montaz

2010

Runtime Verification

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Abstract. We present a new approach for developing robust software applications that breaks dependences on the failed parts of an application's execution to allow the rest of the application to continue executing. When a failure occurs, the recovery algorithm uses information from a static analysis to characterize the intended behavior of the application had it not failed. It then uses this characterization to recover as much of the application's execution as possible. We have implemented this approach in the Bristlecone compiler. We have evaluated our implementation on a multiplayer game, a web portal, and a MapReduce framework. We found that in the presence of injected failures, the recovery task version provided substantially better service than the control versions. Moreover, the recovery task version of the game benchmark successfully recovered from a real fault that we accidentally introduced during development, while the same fault caused the two control versions to crash.

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Section: Classesmentioning

confidence: 99%

“…Backward recovery uses a combination of checkpointing and acceptance tests to prevent a software system from entering an incorrect state [5]. Forward recovery uses multiple copies of a computation to recover from transient errors [11].…”

Section: Related Workmentioning

confidence: 99%

Recovery Tasks: An Automated Approach to Failure Recovery

Demsky

Zhou

Montaz

2010

Runtime Verification

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“…The comparison of the new on-line algorithm with the fixed intervals placement strategy is done by comparing the overhead ratio of the on-line algorithm, given in Lemma 2, with the overhead ratio of the fixed intervals placement strategy, given in (2). The values of t 1 and t 2 for the on-line algorithm and the interval length t for the fixed intervals placement strategy are those that minimize the overhead ratio.…”

Section: Comparison With Existing Algorithmsmentioning

confidence: 99%

“…Another approach for placing checkpoints, that takes into account the change of checkpointing overhead over time, can be found in [2]. In that paper, Chandy and Ramamoorthy proposed an algorithm, based on a graph theoretic method, for a placement of checkpoints that allows the programmer to decide where to place checkpoints according to an a priori knowledge about the cost of checkpointing.…”

Section: Introductionmentioning

confidence: 99%

An on-line algorithm for checkpoint placement

Ziv

Bruck

Proceedings of ISSRE '96: 7th International Symposium on Software Reliability Engineering

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Abstract-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.

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“…Chandy [3] discusses costs of rollback and recovery with several assumptions: the checkpointing time is fixed, the time required to reprocess the logged transactions is proportional to the number of transactions recorded since the last checkpoint, and the checkpoint itself is always correct. In [4], Chandy et al propose algorithms which make use of estimates made by the programmers on the maximum amount of processing time to minimize the maximum or expected time spent in checkpointing. These algorithms need some a priori knowledge about the processing time.…”

Section: Related Workmentioning

confidence: 99%