| Minimizing total flow time and total completion time with immediate dispatching |
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ACM Symposium on Parallel Algorithms and Architectures
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Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and architectures
table of contents
San Diego, California, USA
SESSION: Scheduling I
table of contents
Pages: 11 - 18
Year of Publication: 2003
ISBN:1-58113-661-7
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Downloads (6 Weeks): 3, Downloads (12 Months): 33, Citation Count: 12
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ABSTRACT
We consider the problem of scheduling jobs arriving over time in a multiprocessor setting, with immediate dispatching, disallowing job migration. The goal is to minimize both the total flow time (total time in the system) and the total completion time.Previous studies have shown that while preemption (interrupt a job and later continue its execution) is inherent to make a scheduling algorithm efficient, migration (continue the execution on a different machine) is not. Still, the current non-migratory online algorithms suffer from a need for a central queue of unassigned jobs which is a "no option" in large computing system, such as the Web.We introduce a simple online non-migratory algorithm IMD, which employs immediate dispatching, i.e., it immediately assigns released jobs to one of the machines. We show that the performance of this algorithm is within a logarithmic factor of the optimal migratory offline algorithm, with respect to the total flow time, and within a small constant factor of the optimal migratory offline algorithm, with respect to the total completion time. This solves an open problem suggested by Awerbuch et al [STOC99].
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Foto Afrati , Evripidis Bampis , Chandra Chekuri , David Karger , Claire Kenyon , Sanjeev Khanna , Ioannis Milis , Maurice Queyranne , Martin Skutella , Cliff Stein , Maxim Sviridenko, Approximation Schemes for Minimizing Average Weighted Completion Time with Release Dates, Proceedings of the 40th Annual Symposium on Foundations of Computer Science, p.32, October 17-18, 1999
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Baruch Awerbuch , Yossi Azar , Stefano Leonardi , Oded Regev, Minimizing the flow time without migration, Proceedings of the thirty-first annual ACM symposium on Theory of computing, p.198-205, May 01-04, 1999, Atlanta, Georgia, United States
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K.R. Baker. Introduction to Sequencing and Scheduling. Wiley, 1974.
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C. Chekuri , R. Motwani , B. Natarajan , C. Stien, Approximation techniques for average completion time scheduling, Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms, p.609-618, January 05-07, 1997, New Orleans, Louisiana, United States
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Leslie A. Hall , David B. Shmoys , Joel Wein, Scheduling to minimize average completion time: off-line and on-line algorithms, Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms, p.142-151, January 28-30, 1996, Atlanta, Georgia, United States
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Hans Kellerer , Thomas Tautenhahn , Gerhard J. Woeginger, Approximability and nonapproximability results for minimizing total flow time on a single machine, Proceedings of the twenty-eighth annual ACM symposium on Theory of computing, p.418-426, May 22-24, 1996, Philadelphia, Pennsylvania, United States
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E.L. Lawler, J.K Lenstra, A.H.G. Rinnooy Kan, and D.B. Shmoys. Sequencing and scheduling: algorithms and complexity. In Handbooks in operations research and management science, volume 4, pages 445--522. North Holland, 1993.
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CITED BY 12
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Chandra Chekuri , Ashish Goel , Sanjeev Khanna , Amit Kumar, Multi-processor scheduling to minimize flow time with ε resource augmentation, Proceedings of the thirty-sixth annual ACM symposium on Theory of computing, June 13-16, 2004, Chicago, IL, USA
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