An uncoordinated asynchronous checkpointing model for hierarchical scientific workflows

  • Authors:

  • Rafael Tolosana-Calasanz;José Ángel Baòares;Pedro Álvarez;Joaquín Ezpeleta;Omer Rana

  • Affiliations:

  • Computer Science and Systems Engineering Department, Aragón Institute of Engineering Research (I3A), Universidad de Zaragoza, Spain;Computer Science and Systems Engineering Department, Aragón Institute of Engineering Research (I3A), Universidad de Zaragoza, Spain;Computer Science and Systems Engineering Department, Aragón Institute of Engineering Research (I3A), Universidad de Zaragoza, Spain;Computer Science and Systems Engineering Department, Aragón Institute of Engineering Research (I3A), Universidad de Zaragoza, Spain;School of Computer Science, Cardiff University, United Kingdom

  • Venue:
  • Journal of Computer and System Sciences
  • Year:
  • 2010

Quantified Score

Hi-index 0.08

Visualization

Abstract

Scientific workflow systems often operate in unreliable environments, and have accordingly incorporated different fault tolerance techniques. One of them is the checkpointing technique combined with its corresponding rollback recovery process. Different checkpointing schemes have been developed and at various levels: task- (or activity-) level and workflow-level. At workflow-level, the usually adopted approach is to establish a checkpointing frequency in the system which determines the moment at which a global workflow checkpoint - a snapshot of the whole workflow enactment state at normal execution (without failures) - has to be accomplished. We describe an alternative workflow-level checkpointing scheme and its corresponding rollback recovery process for hierarchical scientific workflows in which every workflow node in the hierarchy accomplishes its own local checkpoint autonomously and in an uncoordinated way after its enactment. In contrast to other proposals, we utilise the Reference net formalism for expressing the scheme. Reference nets are a particular type of Petri nets which can more effectively provide the abstractions to support and to express hierarchical workflows and their dynamic adaptability.