Scheduling trade-off of dynamic multiple parallel workflows on heterogeneous distributed computing systems

Concurrency and Computation: Practice and Experience

Volumn 29, Issue 2, 2017, Pages

  Xie, Guoqi ^a   Liu, Liangjiao ^a   Yang, Liu ^b   Li, Renfa ^a  

^a HUNAN UNIVERSITY   (China)

^b Development and Reform Commission of Hunan Province   (China)

Author keywords

dynamic; tradeoff; workflows

Indexed keywords

COPYRIGHTS; DISTRIBUTED COMPUTER SYSTEMS; DYNAMICS; ECONOMIC AND SOCIAL EFFECTS; SCHEDULING;

COMPUTATIONAL GRIDS; DISTRIBUTED COMPUTING SYSTEMS; EXPERIMENTAL EVALUATION; PERFORMANCE OF SYSTEMS; PRIORITY-BASED SCHEDULING; RESOURCE PROVIDERS; TRADEOFF; WORK-FLOWS;

LARGE SCALE SYSTEMS;

EID: 85007197232     PISSN: 15320626     EISSN: 15320634     Source Type: Journal    
DOI: 10.1002/cpe.3782     Document Type: Conference Paper

References (21)

1. Berriman G, Good J, Laity A, Bergou A, Jacob J, Katz D, Deelman E, Kesselman C, Singh G, Su M-H, Williams R. Montage: a grid enabled image mosaic service for the national virtual observatory. Astronomical Data Analysis Software and Systems (ADASS) XIII, Vol. 314, Pasadena, California, USA, 2004; 593–596.
2. Deelman E, Callaghan S, Field E, Francoeur H, Graves R, Gupta N, Gupta V, Jordan T. H, Kesselman C, Maechling P, Mehringer J, Mehta G, Okaya D, Vahi K, Zhao L. Managing large-scale workflow execution from resource provisioning to provenance tracking: the cybershake example. Second IEEE International Conference on e-Science and Grid Computing, 2006. e-Science'06, IEEE, Washington, DC, USA, 2006; 14–14.
3. Yu Z, Shi W. A planner-guided scheduling strategy for multiple workflow applications. International Conference on Parallel Processing-Workshops, 2008. ICPP-W'08, Portland, Oregon, USA, 2008; 1–8.
4. Hsu C-C, Huang K-C, Wang F-J. Online scheduling of workflow applications in grid environments. Future Generation Computer Systems 2011; 27(6):860–870.
5. Arabnejad H, Barbosa J. Fairness resource sharing for dynamic workflow scheduling on heterogeneous systems. 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications (ISPA), Leganes, Madrid, Spain, 2012; 633–639.
6. Augonnet C, Thibault S, Namyst R, Wacrenier P-A. Starpu: a unified platform for task scheduling on heterogeneous multicore architectures. Concurrency and Computation: Practice and Experience 2011; 23(2):187–198.
7. Topcuoglu H, Hariri S, Wu M-y. Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Transactions on Parallel and Distributed Systems 2002; 13(3):260–274.
8. Kim SC, Lee S, Hahm J. Push-pull: deterministic search-based DAG scheduling for heterogeneous cluster systems. IEEE Transactions on Parallel and Distributed Systems 2007; 18(11):1489–1502.
9. Bajaj R, Agrawal DP. Improving scheduling of tasks in a heterogeneous environment. IEEE Transactions on Parallel and Distributed Systems 2004; 15(2):107–118.
10. Zhao H, Sakellariou R. Scheduling multiple DAGs onto heterogeneous systems. 20th International Parallel and Distributed Processing Symposium, 2006. IPDPS 2006, Chicago, USA, 2006; 159–172.
11. Hönig U, Schiffmann W. A meta-algorithm for scheduling multiple DAGs in homogeneous system environments. Proceedings of the Eighteenth IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS06), Dallas, USA, 2006; 147–152.
12. Li T, Baumberger D, Hahn S. Efficient and scalable multiprocessor fair scheduling using distributed weighted round-robin. In ACM Sigplan Notices, Vol. 44, No. 4. ACM: New York, USA 2009; 65–74.
13. Mohanty R, Behera H, Patwari K, Dash M, Prasanna ML. Priority based dynamic round robin (PBDRR) algorithm with intelligent time slice for soft real time systems. arXiv preprint arXiv:1105.1736, 2011.
14. Melnyk A. Multiple DAGs scheduling with deadline driven coordinator in grid. Second International Conference Cluster Computing, Lviv, Ukraine, 2013; 3–5.
15. Topcuoglu H, Hariri S, Wu M-y. Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Transactions on Parallel and Distributed Systems 2002; 13(3):260–274.
16. Khan MA. Scheduling for heterogeneous systems using constrained critical paths. Parallel Computing 2012; 38(4):175–193.
17. Xie G, Li R, Xiao X, Chen Y. A high-performance DAG task scheduling algorithm for heterogeneous networked embedded systems. 2014 IEEE 28th International Conference on Advanced Information Networking and Applications (AINA), Victoria, Canada, 2014; 1011–1016.
18. Zhu L, Sun Z, Guo W, Jin Y, Sun W, Hu W. Dynamic multi DAG scheduling algorithm for optical grid environment. In Asia-Pacific Optical Communications. International Society for Optics and Photonics: Wuhan, China, 2007; 67841F–67841F.
19. Bittencourt LF, Madeira ER. Towards the scheduling of multiple workflows on computational grids. Journal of Grid Computing 2010; 8(3):419–441.
20. Hagras T, Janeček J. A high performance, low complexity algorithm for compile-time task scheduling in heterogeneous systems. Parallel Computing 2005; 31(7):653–670.
21. Manolache S, Eles P, Peng Z. Task mapping and priority assignment for soft real-time applications under deadline miss ratio constraints. ACM Transactions on Embedded Computing Systems (TECS) 2008; 7(2):1–19:35.