In scientific workflows, temporal constraints are crucial for ensuring timely completion of tasks and efficient resource utilization. This study addresses the challenge of optimizing these constraints within localized scientific workflows. We propose a framework that integrates techniques for identifying, managing, and optimizing temporal constraints to enhance the overall performance and reliability of scientific workflows. Our approach involves analyzing task dependencies, resource availability, and execution times to localize constraints effectively. Through case studies and simulations, we demonstrate how our framework can reduce workflow execution times and improve resource allocation. The results show significant improvements in workflow efficiency and effectiveness, providing a robust solution for managing complex temporal requirements in scientific research.

Temporal constraints, scientific workflows, optimization

W.M.P. van der Aalst, A.H.M. ter Hofstede, B. Kiepuszewski, A.P. Barros, Workflow patterns, Distrib. Parallel Databases 14 (1) (2003) 5–51.

A.Abramson, J. Kommineni, J.L. McGregor, J. Katzfey, An atmospheric sciences workflow and its implementation with Web services, Future Generation Comput. Syst. 21 (1) (2005) 69–78.

J.Alhiyafi, C. Sabesan, S. Lu, J.L. Ram, RECOMBFLOW: A scientific workflow environment for Intragenomic Gene Conversion analysis in bacterial genomes, including the pathogen Streptococcus pyogenes, Int. J. Bioinform. Res. Appl. 5 (1) (2009) 1–19.

I.Brandic, S. Pllana, S. Benkner, Specification, planning, and execution of QoS-aware Grid workflows within the Amadeus environment, Concurrency Computation: Practice & Experience 20 (4) (2008) 331–345.

J.Chen, Y. Yang, Multiple states based temporal consistency for dynamic verification of fixed-time constraints in Grid workflow systems, Concurrency Computation: Practice & Experience 19 (7) (2007) 965–982.

J.Chen, Y. Yang, Activity completion duration based checkpoint selection for dynamic verification of temporal constraints in Grid workflow systems, Int. J. High Performance Comput. Appl. 22 (3) (2008) 319–329.

J.Chen, Y. Yang, Adaptive selection of necessary and sufficient checkpoints for dynamic verification of temporal constraints in Grid workflow systems, ACM Trans. Autonomous Adaptive Syst. 2 (2) (2007), Article 6.

J.Chen, Y. Yang, Temporal dependency based checkpoint selection for dynamic verification of temporal constraints in scientific workflow systems, ACM Trans. Software Engrg. Methodol., in press (accepted on 17 June 2009), http://www.swinflow.org/papers/TOSEM.pdf, accessed on 20 July 2009.

S.Chinn, G. Madey, Temporal representation and reasoning for workflow in engineering design change review, IEEE Trans. Eng. Manage. 47 (4) (2000) 485–492.

D.Cybok, A Grid workflow infrastructure, Concurrency Comput. Pract. Ex. 18 (10) (2006) 1243–1254, special issue on workflow in Grid systems.

K.Daisuke, C. Runyue, C.H. Luis, Gravitational stability of circumnuclear disks in elliptical galaxies, Astrophysical J. 669 (1) (2007) 232–240.

E.Deelman, A.L. Chervenak, Data management challenges of data-intensive scientific workflows, in: Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid, May 2008, Lyon, France, IEEE CS Press, pp. 687–692.

J.Eder, E. Panagos, M. Rabinovich, Time constraints in workflow systems, in: Proceedings of the 11th International Conference on Advanced Information Systems Engineering, Heidelberg, Germany, June 1999, in: Lecture Notes in Comput. Sci., vol. 1626, Springer-Verlag, 1999, pp. 286–300.

Y.Gil, E. Deelman, M. Ellisman, T. Fahringer, G. Fox, D. Gannon, C. Goble, M. Livny, L. Moreau, J. Myers, Examining the challenges of scientific workflows, IEEE Comput. 40 (12) (2007) 24–32.

C.Hagen, G. Alonso, Exception handling in workflow management systems, IEEE Trans. Software Eng. 26 (10) (2000) 943–958.