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  Online Scheduling of Jobs with Fixed Start Times on Related Machines

Epstein, L., Jez, L., Sgall, J., & van Stee, R. (2012). Online Scheduling of Jobs with Fixed Start Times on Related Machines. In A. Gupta, K. Jansen, J. Rolim, & R. Servedio (Eds.), Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (pp. 134-145). Berlin: Springer. doi:10.1007/978-3-642-32512-0_12.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0014-BCA6-0 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0023-C09D-D
Genre: Conference Paper

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 Creators:
Epstein, Leah1, Author
Jez, Lukasz1, Author
Sgall, Jiri1, Author
van Stee, Rob2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Algorithms and Complexity, MPI for Informatics, Max Planck Society, ou_24019              

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 Abstract: We consider online preemptive throughput scheduling of jobs with fixed starting times on m uniformly related machines, with the goal of maximizing the profit of the completed jobs. In this problem, jobs are released over time. Every job has a size and a weight associated with it. A newly released job must be either assigned to start running immediately on a machine or otherwise it is dropped. It is also possible to drop an already scheduled job, but only completed jobs contribute their weights to the profit of the algorithm. In the most general setting, no algorithm has bounded competitive ratio, and we consider a number of standard variants. We give a full classification of the variants into cases which admit constant competitive ratio (weighted and unweighted unit jobs, and C-benevolent instances, which is a wide class of instances containing proportional-weight jobs), and cases which admit only a linear competitive ratio (unweighted jobs and D-benevolent instances). In particular, we give a lower bound of m on the competitive ratio for scheduling unit weight jobs with varying sizes, which is tight. For unit size and weight we show that a natural greedy algorithm is 4/3-competitive and optimal on m=2 machines, while for a large m, its competitive ratio is between 1.56 and 2. Furthermore, no algorithm is better than 1.5-competitive.

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Language(s): eng - English
 Dates: 2012-082012
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-642-32512-0_12
BibTex Citekey: EpJeSS12
Other: Local-ID: CA0E53116309F933C1257AB6003C51EB-EpJeSS12
 Degree: -

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Title: 15th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems and 16th International Workshop on Randomization and Computation
Place of Event: Cambridge, MA
Start-/End Date: 2012-08-15 - 2012-08-17

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Title: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
  Subtitle : 15th International Workshop, APPROX 2012 and 16th International Workshop, RANDOM 2012
  Abbreviation : APPROX/RANDOM 2012
Source Genre: Proceedings
 Creator(s):
Gupta, Anupam1, Editor
Jansen, Klaus1, Editor
Rolim, José1, Editor
Servedio, Rocco1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 134 - 145 Identifier: ISBN: 978-3-642-32511-3

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Title: Lecture Notes in Computer Science
  Abbreviation : LNCS
Source Genre: Series
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Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 7408 Sequence Number: - Start / End Page: - Identifier: ISSN: 0302-9743