Minimizing completion time of a program by checkpointing and rejuvenation

Garg, Sachin; Huang, Yennun; Kintala, Chandra M. R.; Trivedi, Kishor S.

doi:10.1145/233008.233050

Cited by 60 publications

(44 citation statements)

References 12 publications

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“…Micro-reboot, checkpoint and recovery, and software rejuvenation address non-deterministic failures by rebooting the components that caused the failure (micro-reboot), by rolling back to the latest consistent state and re-executing the failing operations (checkpoint and recovery), and by regularly restarting the system to prevent failures due to software age (rejuvenation) [4,11,12]. Similar to these approaches, Qin et al propose the Rx method that partially re-executes the failing program under modified environment conditions [18].…”

Section: Related Workmentioning

confidence: 99%

Automatic workarounds for web applications

Carzaniga

Gorla

Perino

et al. 2010

Proceedings of the Eighteenth ACM SIGSOFT International Symposium on Foundations of Software Engineering

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We present a technique that finds and executes workarounds for faulty Web applications automatically and at runtime. Automatic workarounds exploit the inherent redundancy of Web applications, whereby a functionality of the application can be obtained through different sequences of invocations of Web APIs. In general, runtime workarounds are applied in response to a failure, and require that the application remain in a consistent state before and after the execution of a workaround. Therefore, they are ideally suited for interactive Web applications, since those allow the user to act as a failure detector with minimal effort, and also either use read-only state or manage their state through a transactional data store. In this paper we focus on faults found in the access libraries of widely used Web applications such as Google Maps. We start by classifying a number of reported faults of the Google Maps and YouTube APIs that have known workarounds. From those we derive a number of general and API-specific program-rewriting rules, which we then apply to other faults for which no workaround is known. Our experiments show that workarounds can be readily deployed within Web applications, through a simple client-side plug-in, and that program-rewriting rules derived from elementary properties of a common library can be effective in finding valid and previously unknown workarounds.

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Section: Related Workmentioning

confidence: 99%

Automatic workarounds for web applications

Carzaniga

Gorla

Perino

et al. 2010

Proceedings of the Eighteenth ACM SIGSOFT International Symposium on Foundations of Software Engineering

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“…In [20] Chakravorty and Kale explain how pro-active fault tolerance based on processor failure information can lead to migration of tasks from faulty processors to healthy nodes. Software rejuvenation along with checkpointing has been used in [21] to minimize the application execution time pro-actively. The FT policy of proactive combined with reactive policy is relatively less explored.…”

Section: B Related Workmentioning

confidence: 99%

Evaluation of fault-tolerant policies using simulation

Tikotekar

Vallée

Naughton

et al. 2007

2007 IEEE International Conference on Cluster Computing

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Abstract-Various mechanisms for fault-tolerance (FT) are used today in order to reduce the impact of failures on application execution. In the case of system failure, standard FT mechanisms are checkpoint/restart (for reactive FT) and migration (for pro-active FT). However, each of these mechanisms create an overhead on application execution, overhead that for instance becomes critical on large-scale systems where previous studies have shown that applications may spend more time checkpointing state than performing useful work.In order to decrease this overhead, researchers try to both optimize existing FT mechanisms and implement new FT policies. For instance, combining reactive and pro-active approaches in order to decrease the number of checkpoints that must be performed during the application's execution. However, currently no solutions exist which enable the evaluation of these FT approaches through simulation, instead experimentations must be done using real platforms. This increases complexity and limits experimentation into alternate solutions. This paper presents a simulation framework that evaluates different FT mechanisms and policies. The framework uses system failure logs for the simulation with a default behavior based on logs taken from the ASCI White at Lawrence Livermore National Laboratory. We evaluate the accuracy of our simulator comparing simulated results with those taken from experiments done on a 32-node compute cluster. Therefore such a simulator can be used to develop new FT policies and/or to tune existing policies.

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“…In [65] it is proposed and analyzed the combination of software rejuvenation (preventive fault treatment) with checkpointing and recovery to reduce the chances of activating a fault and simultaneously minimizing the loss of computation when there is a failure.…”

Section: Checkpointing and Recoverymentioning

confidence: 99%