Stochastic tail-phase optimization for bag-of-tasks execution in clouds

Proceedings - 2012 IEEE/ACM 5th International Conference on Utility and Cloud Computing, UCC 2012

Volumn , Issue , 2012, Pages 204-208

  Oprescu, Ana Maria ^a   Kielmann, Thilo ^a   Leahu, Haralambie ^a  

^a VU UNIVERSITY AMSTERDAM   (Netherlands)

Author keywords

Budget; Scheduling; Task replication

Indexed keywords

BAG-OF-TASKS; BUDGET; BUDGET CONSTRAINT; COMPUTE RESOURCES; ELASTIC APPLICATIONS; EVALUATION RESULTS; EXECUTION TIME; MAKESPAN; ON DEMANDS; RUNTIMES; STOCHASTIC OPTIMIZATIONS; TASK COMPLETION TIME; TASK REPLICATIONS; TIME INTERVAL;

BUDGET CONTROL; CLOUD COMPUTING; OPTIMIZATION; SCHEDULING; SCHEDULING ALGORITHMS; STATISTICS; STOCHASTIC SYSTEMS;

QUALITY CONTROL;

EID: 84874253218     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/UCC.2012.23     Document Type: Conference Paper

References (16)

1. A.-M. Oprescu, T. Kielmann, and H. Leahu, "Budget estimation and control for bag-of-tasks scheduling in clouds," Parallel Processing Letters, vol. 21, no. 2, pp. 219-243, 2011.
2. A. Iosup, O. Sonmez, S. Anoep, and D. Epema, in HPDC '08.
3. T. N. Minh, L. Wolters, and D. Epema, "A realistic integrated model of parallel system workloads," ser. CCGRID'10.
4. "The First International Data Analysis Challenge for Finding Supernovae," http://www.cluster2008.org/challenge/, held in conjunction with IEEE Cluster/Grid 2008.
5. A.-M. Oprescu and T. Kielmann, "Bag-of-tasks scheduling under budget constraints," in CloudCom 2010, pp. 351-359.
6. M. Mao, J. Li, and M. Humphrey, "Cloud auto-scaling with deadline and budget constraints," in Grid 2010.
7. K. Liu, H. Jin, J. Chen, X. Liu, D. Yuan, and Y. Yang, "A compromised-time-cost scheduling algorithm in swindew-c for instance-intensive cost-constrained workflows on a cloud computing platform," Int. J. High Perform. C., vol. 24, no. 4, pp. 445-456, 2010.
8. D. Kondo, A. A. Chien, and H. Casanova, "Scheduling task parallel applications for rapid turnaround on enterprise desktop grids," J. Grid Comput., vol. 5, no. 4, pp. 379-405, 2007.
9. J. Wingstrom and H. Casanova, "Probabilistic allocation of tasks on desktop grids," in IPDPS'08.
10. T. G. Armstrong, Z. Zhang, D. S. Katz, M. Wilde, and I. T. Foster, "Scheduling many-task workloads on supercomputers: Dealing with trailing tasks," in MTAGS 2010.
11. W. Lu, J. Jackson, J. Ekanayake, R. S. Barga, and N. Araujo, "Performing large science experiments on azure: Pitfalls and solutions," in CloudCom 2010.
12. J. Dean and S. Ghemawat, "Mapreduce: Simplified data processing on large clusters," in OSDI'04.
13. O. A. Ben-Yehuda, A. Schuster, A. Sharov, M. Silberstein, and A. Iosup, "Expert: Pareto-efficient task replication on grids and a cloud," in IPDPS'12.
14. S. Delamare, G. Fedak, D. Kondo, and O. Lodygensky, "Spequlos: A qos service for bot applications using best effort distributed computing infrastructures," in HPDC'12.
15. M. A. Iverson, F. Özgüner, and L. C. Potter, "Statistical prediction of task execution times through analytic benchmarking for scheduling in a heterogeneous environment," IEEE Trans. Computers, vol. 48, no. 12, pp. 1374-1379, 1999.
16. S. Verboven, P. Hellinckx, F. Arickx, and J. Broeckhove, "Runtime prediction based grid scheduling of parameter sweep jobs," in APSCC'08.