Reducing recovery time in a small recursively restartable system

Candea, George; Cutler, James; Fox, Armando; Doshi, R.; Garg, Priyank; Gowda, Rakesh

doi:10.1109/dsn.2002.1029006

Cited by 49 publications

(29 citation statements)

References 5 publications

(11 reference statements)

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“…Some approaches have focused on automatic restarting of components before or after they have failed [3], [4]. There have also been some works in applying techniques from Markov decision theory to dependability problems [5].…”

Section: Related Workmentioning

confidence: 99%

AESON: A Model-Driven and Fault Tolerant Composite Deployment Runtime for IaaS Clouds

Jayasinghe

Oliveira

et al. 2013

2013 IEEE International Conference on Services Computing

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Abstract-Infrastructure-as-a-Service (IaaS) cloud environments expose to users the infrastructure of a data center while relieving them from the burden and costs associated with its management and maintenance. IaaS clouds provide an interface by means of which users can create, configure, and control a set of virtual machines that will typically host a composite software service. Given the increasing popularity of this computing paradigm, previous work has focused on modeling composite software services to automate their deployment in IaaS clouds. This work is concerned with the runtime state of composite services during and after deployment. We propose AESON, a deployment runtime that automatically detects node (virtual machine) failures and eventually brings the composite service to the desired deployment state by using information describing relationships between the service components. We have designed AESON as a decentralized peer-to-peer publish/subscribe system leveraging IBM's Bulletin Board (BB), a topic-based distributed shared memory service built on top of an overlay network.

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Section: Related Workmentioning

confidence: 99%

AESON: A Model-Driven and Fault Tolerant Composite Deployment Runtime for IaaS Clouds

Jayasinghe

Oliveira

et al. 2013

2013 IEEE International Conference on Services Computing

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“…More recently, two techniques have been presented to improve the performance compared to whole-system rebooting. The first technique is microrebooting [13], [14], which is a fine-grained technique for surgically recovering faulty application components without disturbing the rest of the application. Microrebooting is evaluated in an Internet auction system running on an application server.…”

Section: Implementation Of Watchdog Timers and Past-run Trace Recomentioning

confidence: 99%

r-Kernel: An operating system foundation for highly reliable networked embedded systems

Cao

Wang

et al. 2011

2011 Proceedings IEEE INFOCOM

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Abstract-In this paper, we present r-kernel, an operating system kernel enhancement specifically designed to improve software reliability in networked embedded systems. The key novelty of r-kernel lies in that it exploits the time dimension of software execution to improve robustness. Specifically, r-kernel keeps track of the execution of applications through checkpoints. If one application has been determined to have failed, r-kernel performs rollback operations to restore its state to one of those checkpoints created earlier. For the second round of operation, r-kernel provides a safe mode environment to avoid triggering the same bugs, by dynamically redirecting system calls made by the application. Finally, if the whole system is crashed, r-kernel relies on watchdog timers to reset the node, and develops a technique called past-run reconstruction to locate and report the thread that had caused the system failure. We have implemented r-kernel based on the LiteOS operating system kernel running on the popular MicaZ platform. We demonstrate that it achieves desired goals with acceptable overhead.

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“…Restarts of individual components for recovery, pro-actively as well as reactively have been seen in software rejuvenation [25] and recovery-oriented computing [13,4]. While the latter used fast restarts of individual components in a system as a tool to improve system availability, our work assumes a recovery time and maintains timely operation in the presence of restarts thus increasing the MTTF of the system aiding both reliability and availability.…”

Section: Related Workmentioning

confidence: 99%

Fault Tolerance in Networked Control Systems Through Real-Time Restarts

Graham¹

2004

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Reducing recovery time in a small recursively restartable system

Abstract: We present ideas on how to structure software systems for high availability by considering MTTR/MTTF

Cited by 49 publications

References 5 publications

AESON: A Model-Driven and Fault Tolerant Composite Deployment Runtime for IaaS Clouds

AESON: A Model-Driven and Fault Tolerant Composite Deployment Runtime for IaaS Clouds

r-Kernel: An operating system foundation for highly reliable networked embedded systems

Fault Tolerance in Networked Control Systems Through Real-Time Restarts

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