Using Runtime Verification to Design a Reliable Execution Framework for Scientific Workflows


In this paper, we describe the design of a scientific workflow execution framework that integrates runtime verification to monitor its execution and checking it against the formal specifications. For controlling workflow execution, this framework provides for data provenance, execution tracking and online monitoring of each work flow task, also referred to as participants. The sequence of participants is described in an abstract parameterized view, which is used to generate concrete data dependency based sequence of participants with defined arguments. As participants belonging to a workflow are mapped onto machines and executed, periodic and on-demand monitoring of vital health parameters on allocated nodes is enabled according to pre-specified invariant conditions with actions to be taken upon violation of invariants.

2009 Sixth IEEE Conference and Workshops on Engineering of Autonomic and Autonomous Systems