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

Abhishek Dubey, L. Piccoli, J. B. Kowalkowski, J. N. Simone, X. Sun, G. Karsai, S. Neema

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

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Why This Matters

Autonomous systems must adapt to changing environmental conditions and mission objectives, yet manual configuration management is infeasible for complex systems with many possible configurations. This work innovates by enabling online reconfiguration through systematic exploration of valid configurations that satisfy current constraints and objectives. The model-based constraint approach allows specifying both functional and non-functional requirements that guide configuration selection.

What We Did

This paper presents enabling self-management in systems through model-based design space exploration that symbolically encodes valid system configurations and constraints. The work develops the DESERT tool that works on finite-state design spaces to identify configurations satisfying specified constraints and performance objectives. The approach uses binary decision diagrams to represent design spaces and constraint satisfaction for efficient exploration of large configuration spaces.

Key Results

The DESERT tool successfully explores large design spaces to identify valid configurations and recomputes solutions when system conditions change. Results demonstrate effective online reconfiguration of systems in response to component failures and new mission objectives. The approach scales to realistic system complexities while maintaining constraint satisfaction during all configuration changes.

Full Abstract

Cite This Paper

@inproceedings{Dubey2009d,
  author = {Dubey, Abhishek and {Piccoli}, L. and {Kowalkowski}, J. B. and {Simone}, J. N. and {Sun}, X. and {Karsai}, G. and {Neema}, S.},
  booktitle = {2009 Sixth IEEE Conference and Workshops on Engineering of Autonomic and Autonomous Systems},
  title = {Using Runtime Verification to Design a Reliable Execution Framework for Scientific Workflows},
  year = {2009},
  month = {apr},
  pages = {87-96},
  abstract = {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.},
  category = {conference},
  contribution = {lead},
  doi = {10.1109/EASe.2009.13},
  file = {:Dubey2009d-Using_runtime_verification_to_design_a_reliable_execution_framework_for_scientific_workflows.pdf:PDF},
  issn = {2168-1872},
  keywords = {self-management, design space exploration, reconfiguration, constraint satisfaction, autonomous systems, model-based design},
  month_numeric = {4}
}
Quick Info
Year 2009
DOI 10.1109/EASe.2009.13
Keywords
self-management design space exploration reconfiguration constraint satisfaction autonomous systems model-based design
Research Areas
CPS middleware scalable AI
Search Tags

Runtime, Verification, Design, Reliable, Execution, Framework, Scientific, Workflows, self-management, design space exploration, reconfiguration, constraint satisfaction, autonomous systems, model-based design, CPS, middleware, scalable AI, 2009, Dubey, Piccoli, Kowalkowski, Simone, Sun, Karsai, Neema