Online Scheduling on Identical Machines using SRPT

Fox, Kyle; Moseley, Benjamin

doi:10.1137/1.9781611973082.10

Cited by 28 publications

(19 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Theoretical Approaches: Several theoretical works tackle scheduling in multi-server systems -a recent example is the work by Moseley and Fox [29]. These works, which are elegant and important contributions to the domain, provide performance bounds and optimality results based on simplifying assumptions on the execution system (e.g., jobs with a single phase).…”

Section: Related Workmentioning

confidence: 99%

HFSP: Size-based scheduling for Hadoop

Pastorelli

Barbuzzi

Carra

et al. 2013

2013 IEEE International Conference on Big Data

View full text Add to dashboard Cite

Abstract-Size-based scheduling with aging has, for long, been recognized as an effective approach to guarantee fairness and near-optimal system response times. We present HFSP, a scheduler introducing this technique to a real, multi-server, complex and widely used system such as Hadoop.Size-based scheduling requires a priori job size information, which is not available in Hadoop: HFSP builds such knowledge by estimating it on-line during job execution.Our experiments, which are based on realistic workloads generated via a standard benchmarking suite, pinpoint at a significant decrease in system response times with respect to the widely used Hadoop Fair scheduler, and show that HFSP is largely tolerant to job size estimation errors.

show abstract

Section: Related Workmentioning

confidence: 99%

HFSP: Size-based scheduling for Hadoop

Pastorelli

Barbuzzi

Carra

et al. 2013

2013 IEEE International Conference on Big Data

View full text Add to dashboard Cite

show abstract

“…Theoretical Approaches: Several theoretical works tackle scheduling in multi-server systems -a recent example is the work by Moseley and Fox [34]. These works, which are elegant and important contributions to the domain, provide performance bounds and optimality results based on simplifying assumptions on the execution system (e.g.,, jobs with a single phase).…”

Section: Related Workmentioning

confidence: 99%

HFSP: Bringing Size-Based Scheduling To Hadoop

Pastorelli¹,

Carra

Dell’Amico³

et al. 2017

IEEE Trans. Cloud Comput.

View full text Add to dashboard Cite

Abstract-Size-based scheduling with aging has been recognized as an effective approach to guarantee fairness and nearoptimal system response times. We present HFSP, a scheduler introducing this technique to a real, multi-server, complex and widely used system such as Hadoop.Size-based scheduling requires a priori job size information, which is not available in Hadoop: HFSP builds such knowledge by estimating it on-line during job execution.Our experiments, which are based on realistic workloads generated via a standard benchmarking suite, pinpoint at a significant decrease in system response times with respect to the widely used Hadoop Fair scheduler, without impacting the fairness of the scheduler, and show that HFSP is largely tolerant to job size estimation errors.

show abstract

“…Here P is the ratio of the maximum to minimum processing time of a job. Assuming resource augmentation a series of works [3,[12][13][14]18] has culminated in a (1 + )-speed O(1/ )-competitive algorithm for unrelated machines.…”

Section: Related Workmentioning

confidence: 99%

Scheduling in Bandwidth Constrained Tree Networks

Moseley

2015

Proceedings of the 27th ACM Symposium on Parallelism in Algorithms and Architectures

Self Cite

View full text Add to dashboard Cite

In this paper we introduce a new network scheduling model. Here jobs need to be sent via routers on a tree to machines to be scheduled, and the communication is constrained by network bandwidth. The scheduler coordinates network communication and job machine scheduling. This type of scheduler is highly desirable in practice; yet few works have considered combing networking with job processing. We consider the popular objective of total flow time in the online setting. We give a (1+ )-speed O( 1 7 )-competitive algorithm when all routers are identical and all machines are identical for any fixed > 0. Then we go on to show a (2 + )-speed O( 1 7 )-competitive algorithm when the routers are identical and the machines are unrelated. To show these results we introduce an interesting combination of potential function and dual fitting techniques as well as a reduction of general tree scheduling to a special case of trees.

show abstract

Online Scheduling on Identical Machines using SRPT

Cited by 28 publications

References 14 publications

HFSP: Size-based scheduling for Hadoop

HFSP: Size-based scheduling for Hadoop

HFSP: Bringing Size-Based Scheduling To Hadoop

Scheduling in Bandwidth Constrained Tree Networks

Contact Info

Product

Resources

About