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Design and Implementation of a Fault Tolerant Job Flow Manager Using Job Flow Patterns and Recovery Policies

  • Selim Kalayci
  • Onyeka Ezenwoye
  • Balaji Viswanathan
  • Gargi Dasgupta
  • S. Masoud Sadjadi
  • Liana Fong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5364)

Abstract

Currently, many grid applications are developed as job flows that are composed of multiple jobs. The execution of job flows requires the support of a job flow manager and a job scheduler. Due to the long running nature of job flows, the support for fault tolerance and recovery policies is especially important. This support is inherently complicated due to the sequencing and dependency of jobs within a flow, and the required coordination between workflow engines and job schedulers. In this paper, we describe the design and implementation of a job flow manager that supports fault tolerance. First, we identify and label job flow patterns within a job flow during deployment time. Next, at runtime, we introduce a proxy that intercepts and resolves faults using job flow patterns and their corresponding fault-recovery policies. Our design has the advantages of separation of the job flow and fault handling logic, requiring no manipulation at the modeling time, and providing flexibility with respect to fault resolution at runtime. We validate our design with a prototypical implementation based on the ActiveBPEL workflow engine and GridWay Meta-scheduler, and Montage application as the case study.

Keywords

Recovery Action Deployment Time Fault Handling Recovery Policy Montage Application 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Selim Kalayci
    • 1
  • Onyeka Ezenwoye
    • 2
  • Balaji Viswanathan
    • 3
  • Gargi Dasgupta
    • 3
  • S. Masoud Sadjadi
    • 1
  • Liana Fong
    • 4
  1. 1.Florida International UniversityMiamiUSA
  2. 2.South Dakota State UniversityBrookingsUSA
  3. 3.IBM India Research LabNew DelhiIndia
  4. 4.IBM Watson Research Center, HawthorneNYUSA

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