Years and Authors of Summarized Original Work
2003; Bansal, Pruhs
Problem Definition
The problem is concerned with scheduling dynamically arriving jobs in the scenario when the processing requirements of jobs are unknown to the scheduler. The lack of knowledge of how long a job will take to execute is a particularly attractive assumption in real systems where such information might be difficult or impossible to obtain. The goal is to schedule jobs to provide good quality of service to the users. In particular the goal is to design algorithms that have good average performance and are also fair in the sense that no subset of users experiences substantially worse performance than others.
Notations
Let \(\mathcal{J} =\{ 1,2,\ldots,n\}\) denote the set of jobs in the input instance. Each job j is characterized by its release time r j and its processing requirement p j . In the online setting, job j is revealed to the scheduler only at time r j . A further restriction is the non-clairvoyant...
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Bansal N, Dhamdhere K, Konemann J, Sinha A (2004) Non-clairvoyant scheduling for minimizing mean slowdown. Algorithmica 40(4):305–318
Bansal N, Pruhs K (2003) Server scheduling in the Lp norm: a rising tide lifts all boat. In: Symposium on theory of computing (STOC), San Diego, pp 242–250
Bansal N, Pruhs K (2004) Server scheduling in the weighted Lp norm. In: LATIN, Buenos Aires, pp 434–443
Chekuri C, Goel A, Khanna S, Kumar A (2004) Multi-processor scheduling to minimize flow time with epsilon resource augmentation. In: Symposium on theory of computing (STOC), Chicago, pp 363–372
Kalyanasundaram B, Pruhs K (2000) Speed is as powerful as clairvoyance. J ACM 47(4):617–643
Kellerer H, Tautenhahn T, Woeginger GJ (1999) Approximability and nonapproximability results for minimizing total flow time on a single machine. SIAM J Comput 28(4):1155–1166
Motwani R, Phillips S, Torng E (1994) Non-clairvoyant scheduling. Theor Comput Sci 130(1):17–47
Muthukrishnan S, Rajaraman R, Shaheen A, Gehrke J (2004) Online scheduling to minimize average stretch. SIAM J Comput 34(2):433–452
Nutt G (1999) Operating system projects using Windows NT. Addison Wesley, Reading
Tanenbaum AS (1992) Modern operating systems. Prentice-Hall, Englewood Cliffs
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Bansal, N. (2016). Shortest Elapsed Time First Scheduling. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_369
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